diff --git a/sdk/ml/azure-ai-ml/README.md b/sdk/ml/azure-ai-ml/README.md
index e67bcc71fbc3..42fd438b5363 100644
--- a/sdk/ml/azure-ai-ml/README.md
+++ b/sdk/ml/azure-ai-ml/README.md
@@ -125,11 +125,11 @@ This project has adopted the [Microsoft Open Source Code of Conduct][code_of_con
[ml_conda]: https://anaconda.org/microsoft/azure-ai-ml/
[ml_ref_docs]: https://learn.microsoft.com/python/api/azure-ai-ml/?view=azure-python
[ml_samples]: https://github.com/Azure/azureml-examples/tree/main/sdk/python
-[product_documentation]: https://docs.microsoft.com/azure/machine-learning/
+[product_documentation]: https://learn.microsoft.com/azure/machine-learning/
[azure_subscription]: https://azure.microsoft.com/free/
-[workspace]: https://docs.microsoft.com/azure/machine-learning/concept-workspace
+[workspace]: https://learn.microsoft.com/azure/machine-learning/concept-workspace
[python_logging]: https://docs.python.org/3/library/logging.html
-[sdk_logging_docs]: https://docs.microsoft.com/azure/developer/python/azure-sdk-logging
+[sdk_logging_docs]: https://learn.microsoft.com/azure/developer/python/azure-sdk-logging
[azure_core_readme]: https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/core/azure-core/README.md
[pip_link]: https://pypi.org/project/pip/
[azure_core_ref_docs]: https://aka.ms/azsdk-python-core-policies
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_artifacts/_constants.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_artifacts/_constants.py
index f007f731baa5..8c9e97ea84c5 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_artifacts/_constants.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_artifacts/_constants.py
@@ -7,7 +7,7 @@
PROCESSES_PER_CORE = 2
# number of parallel connections to be used for uploads > 64MB and downloads
# pylint: disable=line-too-long
-# (Azure Storage param: https://docs.microsoft.com/python/api/azure-storage-blob/azure.storage.blob.blobclient?view=azure-python#upload-blob-data--blob-type--blobtype-blockblob---blockblob----length-none--metadata-none----kwargs-)
+# (Azure Storage param: https://learn.microsoft.com/python/api/azure-storage-blob/azure.storage.blob.blobclient?view=azure-python#upload-blob-data--blob-type--blobtype-blockblob---blockblob----length-none--metadata-none----kwargs-)
MAX_CONCURRENCY = 16
ARTIFACT_ORIGIN = "LocalUpload"
@@ -30,7 +30,7 @@
FILE_SIZE_WARNING = (
"Your file exceeds 100 MB. If you experience low speeds, latency, or broken connections, we recommend using "
"the AzCopyv10 tool for this file transfer.\n\nExample: azcopy copy '{source}' '{destination}' " # cspell:disable-line
- "\n\nSee https://docs.microsoft.com/azure/storage/common/storage-use-azcopy-v10 for more information."
+ "\n\nSee https://learn.microsoft.com/azure/storage/common/storage-use-azcopy-v10 for more information."
)
INVALID_MLTABLE_METADATA_SCHEMA_MSG = "Invalid MLTable metadata schema"
INVALID_MLTABLE_METADATA_SCHEMA_ERROR = (
@@ -54,7 +54,7 @@
"{0}\n{1}\n"
"This SAS token is derived from an account key, but key-based authentication is not permitted "
"for this storage account. To update workspace properties, please see the documentation: "
- "https://review.learn.microsoft.com/en-us/azure/machine-learning/how-to-disable-local-auth-storage?view="
+ "https://review.learn.microsoft.com/azure/machine-learning/how-to-disable-local-auth-storage?view="
"azureml-api-2&branch=pr-en-us-278974&tabs=cli#update-an-existing-workspace"
)
KEY_AUTHENTICATION_ERROR_CODE = "KeyBasedAuthenticationNotPermitted"
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_azure_environments.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_azure_environments.py
index 8e75587c520c..51673b141ad1 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_azure_environments.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_azure_environments.py
@@ -303,7 +303,7 @@ def _get_clouds_by_metadata_url(metadata_url: str) -> Dict[str, Dict[str, str]]:
"SDK requires outbound access to Azure Resource Manager. Please contact your networking team "
"to configure outbound access to Azure Resource Manager on both Network Security Group and "
"Firewall. For more details on required configurations, see "
- "https://docs.microsoft.com/azure/machine-learning/how-to-access-azureml-behind-firewall.",
+ "https://learn.microsoft.com/azure/machine-learning/how-to-access-azureml-behind-firewall.",
metadata_url,
ex,
)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/runhistory/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/runhistory/models/_models.py
index 618c174eb983..398700eefc69 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/runhistory/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/runhistory/models/_models.py
@@ -1493,7 +1493,7 @@ class ExperimentQueryParams(msrest.serialization.Model):
:ivar filter: Allows for filtering the collection of resources.
The expression specified is evaluated for each resource in the collection, and only items
where the expression evaluates to true are included in the response.
- See https://docs.microsoft.com/en-us/azure/search/query-odata-filter-orderby-syntax for
+ See https://learn.microsoft.com/azure/search/query-odata-filter-orderby-syntax for
details on the expression syntax.
:vartype filter: str
:ivar continuation_token: The continuation token to use for getting the next set of resources.
@@ -1526,7 +1526,7 @@ def __init__(
:keyword filter: Allows for filtering the collection of resources.
The expression specified is evaluated for each resource in the collection, and only items
where the expression evaluates to true are included in the response.
- See https://docs.microsoft.com/en-us/azure/search/query-odata-filter-orderby-syntax for
+ See https://learn.microsoft.com/azure/search/query-odata-filter-orderby-syntax for
details on the expression syntax.
:paramtype filter: str
:keyword continuation_token: The continuation token to use for getting the next set of
@@ -2727,7 +2727,7 @@ class QueryParams(msrest.serialization.Model):
:ivar filter: Allows for filtering the collection of resources.
The expression specified is evaluated for each resource in the collection, and only items
where the expression evaluates to true are included in the response.
- See https://docs.microsoft.com/en-us/azure/search/query-odata-filter-orderby-syntax for
+ See https://learn.microsoft.com/azure/search/query-odata-filter-orderby-syntax for
details on the expression syntax.
:vartype filter: str
:ivar continuation_token: The continuation token to use for getting the next set of resources.
@@ -2756,7 +2756,7 @@ def __init__(
:keyword filter: Allows for filtering the collection of resources.
The expression specified is evaluated for each resource in the collection, and only items
where the expression evaluates to true are included in the response.
- See https://docs.microsoft.com/en-us/azure/search/query-odata-filter-orderby-syntax for
+ See https://learn.microsoft.com/azure/search/query-odata-filter-orderby-syntax for
details on the expression syntax.
:paramtype filter: str
:keyword continuation_token: The continuation token to use for getting the next set of
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/runhistory/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/runhistory/models/_models_py3.py
index 7156aeeff13a..4b482905d5ae 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/runhistory/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/runhistory/models/_models_py3.py
@@ -1671,7 +1671,7 @@ class ExperimentQueryParams(msrest.serialization.Model):
:ivar filter: Allows for filtering the collection of resources.
The expression specified is evaluated for each resource in the collection, and only items
where the expression evaluates to true are included in the response.
- See https://docs.microsoft.com/en-us/azure/search/query-odata-filter-orderby-syntax for
+ See https://learn.microsoft.com/azure/search/query-odata-filter-orderby-syntax for
details on the expression syntax.
:vartype filter: str
:ivar continuation_token: The continuation token to use for getting the next set of resources.
@@ -1710,7 +1710,7 @@ def __init__(
:keyword filter: Allows for filtering the collection of resources.
The expression specified is evaluated for each resource in the collection, and only items
where the expression evaluates to true are included in the response.
- See https://docs.microsoft.com/en-us/azure/search/query-odata-filter-orderby-syntax for
+ See https://learn.microsoft.com/azure/search/query-odata-filter-orderby-syntax for
details on the expression syntax.
:paramtype filter: str
:keyword continuation_token: The continuation token to use for getting the next set of
@@ -3041,7 +3041,7 @@ class QueryParams(msrest.serialization.Model):
:ivar filter: Allows for filtering the collection of resources.
The expression specified is evaluated for each resource in the collection, and only items
where the expression evaluates to true are included in the response.
- See https://docs.microsoft.com/en-us/azure/search/query-odata-filter-orderby-syntax for
+ See https://learn.microsoft.com/azure/search/query-odata-filter-orderby-syntax for
details on the expression syntax.
:vartype filter: str
:ivar continuation_token: The continuation token to use for getting the next set of resources.
@@ -3075,7 +3075,7 @@ def __init__(
:keyword filter: Allows for filtering the collection of resources.
The expression specified is evaluated for each resource in the collection, and only items
where the expression evaluates to true are included in the response.
- See https://docs.microsoft.com/en-us/azure/search/query-odata-filter-orderby-syntax for
+ See https://learn.microsoft.com/azure/search/query-odata-filter-orderby-syntax for
details on the expression syntax.
:paramtype filter: str
:keyword continuation_token: The continuation token to use for getting the next set of
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2021_10_01_dataplanepreview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2021_10_01_dataplanepreview/models/_models.py
index 965198e8618e..267544ef65cd 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2021_10_01_dataplanepreview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2021_10_01_dataplanepreview/models/_models.py
@@ -2078,7 +2078,7 @@ class ComponentContainerDetails(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -2262,7 +2262,7 @@ class ComponentVersionDetails(AssetBase):
.. raw:: html
.
:vartype component_spec: any
"""
@@ -2294,7 +2294,7 @@ def __init__(self, **kwargs):
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -2971,7 +2971,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -2980,7 +2980,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -3045,7 +3045,7 @@ def __init__(self, **kwargs):
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2021_10_01_dataplanepreview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2021_10_01_dataplanepreview/models/_models_py3.py
index 535b207a6991..7bdbecc36dad 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2021_10_01_dataplanepreview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2021_10_01_dataplanepreview/models/_models_py3.py
@@ -2279,7 +2279,7 @@ class ComponentContainerDetails(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -2484,7 +2484,7 @@ class ComponentVersionDetails(AssetBase):
.. raw:: html
.
:vartype component_spec: any
"""
@@ -2526,7 +2526,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -3255,7 +3255,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -3264,7 +3264,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -3345,7 +3345,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_02_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_02_01_preview/models/_models.py
index d121442ea70f..4ec94735e1b9 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_02_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_02_01_preview/models/_models.py
@@ -3286,7 +3286,7 @@ class ComponentContainerDetails(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -3435,7 +3435,7 @@ class ComponentVersionDetails(AssetBase):
.. raw:: html
.
:vartype component_spec: any
"""
@@ -3470,7 +3470,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -4965,7 +4965,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -4974,7 +4974,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -5035,7 +5035,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -6110,9 +6110,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -6150,7 +6150,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -6159,7 +6159,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -6272,7 +6272,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -6281,7 +6281,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -6363,9 +6363,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -6403,7 +6403,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -6412,7 +6412,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -6542,7 +6542,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -6551,7 +6551,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -6621,9 +6621,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -6661,7 +6661,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -6670,7 +6670,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -6848,7 +6848,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -6857,7 +6857,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -6967,7 +6967,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -7020,7 +7020,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -7030,7 +7030,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -7164,7 +7164,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -7174,7 +7174,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -7253,7 +7253,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -7306,7 +7306,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -7316,7 +7316,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -7467,7 +7467,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -7477,7 +7477,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -7539,7 +7539,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -7592,7 +7592,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -7602,7 +7602,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -7802,7 +7802,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -7812,7 +7812,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_02_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_02_01_preview/models/_models_py3.py
index 7d13ec5c1d65..ea53ffbdb36e 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_02_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_02_01_preview/models/_models_py3.py
@@ -3536,7 +3536,7 @@ class ComponentContainerDetails(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -3695,7 +3695,7 @@ class ComponentVersionDetails(AssetBase):
.. raw:: html
.
:vartype component_spec: any
"""
@@ -3737,7 +3737,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -5335,7 +5335,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -5344,7 +5344,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -5416,7 +5416,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -6578,9 +6578,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -6618,7 +6618,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -6627,7 +6627,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -6770,7 +6770,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -6779,7 +6779,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -6861,9 +6861,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -6901,7 +6901,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -6910,7 +6910,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -7074,7 +7074,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -7083,7 +7083,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -7153,9 +7153,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -7193,7 +7193,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -7202,7 +7202,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -7423,7 +7423,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -7432,7 +7432,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -7542,7 +7542,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -7595,7 +7595,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -7605,7 +7605,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -7774,7 +7774,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -7784,7 +7784,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -7863,7 +7863,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -7916,7 +7916,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -7926,7 +7926,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -8116,7 +8116,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -8126,7 +8126,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -8188,7 +8188,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -8241,7 +8241,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -8251,7 +8251,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -8499,7 +8499,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -8509,7 +8509,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_05_01/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_05_01/models/_models.py
index 4661879e61a9..f195106ee819 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_05_01/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_05_01/models/_models.py
@@ -3688,7 +3688,7 @@ class ComponentContainerDetails(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -3837,7 +3837,7 @@ class ComponentVersionDetails(AssetBase):
.. raw:: html
.
:vartype component_spec: any
"""
@@ -3872,7 +3872,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -6797,7 +6797,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -6806,7 +6806,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -6867,7 +6867,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_05_01/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_05_01/models/_models_py3.py
index e6f1eefc98a4..d66af5653b57 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_05_01/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_05_01/models/_models_py3.py
@@ -3980,7 +3980,7 @@ class ComponentContainerDetails(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -4139,7 +4139,7 @@ class ComponentVersionDetails(AssetBase):
.. raw:: html
.
:vartype component_spec: any
"""
@@ -4181,7 +4181,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -7322,7 +7322,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -7331,7 +7331,7 @@ class EnvironmentVersionDetails(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -7403,7 +7403,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01/models/_models.py
index 75467891c4b6..fd44c8cb5b08 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01/models/_models.py
@@ -4614,7 +4614,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -4763,7 +4763,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
"""
@@ -4798,7 +4798,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -5848,7 +5848,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -5885,7 +5885,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -5910,7 +5910,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -5948,7 +5948,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8062,7 +8062,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -8071,7 +8071,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -8136,7 +8136,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -9746,9 +9746,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -9786,7 +9786,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -9795,7 +9795,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -9903,7 +9903,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -9912,7 +9912,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -9989,9 +9989,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -10029,7 +10029,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -10038,7 +10038,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -10163,7 +10163,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -10172,7 +10172,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -10238,9 +10238,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -10278,7 +10278,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -10287,7 +10287,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -10460,7 +10460,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -10469,7 +10469,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -10575,7 +10575,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -10622,7 +10622,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -10632,7 +10632,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -10754,7 +10754,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -10764,7 +10764,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -10837,7 +10837,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -10884,7 +10884,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -10894,7 +10894,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -11033,7 +11033,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -11043,7 +11043,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11101,7 +11101,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -11148,7 +11148,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -11158,7 +11158,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -11346,7 +11346,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -11356,7 +11356,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15442,7 +15442,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -15487,7 +15487,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01/models/_models_py3.py
index bd73e43e3900..9265fff1d6da 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01/models/_models_py3.py
@@ -4972,7 +4972,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -5131,7 +5131,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
"""
@@ -5173,7 +5173,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -6304,7 +6304,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6345,7 +6345,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -6370,7 +6370,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6413,7 +6413,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8671,7 +8671,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -8680,7 +8680,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -8757,7 +8757,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -10506,9 +10506,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -10546,7 +10546,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -10555,7 +10555,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -10692,7 +10692,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -10701,7 +10701,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -10778,9 +10778,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -10818,7 +10818,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -10827,7 +10827,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -10985,7 +10985,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -10994,7 +10994,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11060,9 +11060,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11100,7 +11100,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11109,7 +11109,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -11324,7 +11324,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -11333,7 +11333,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11439,7 +11439,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -11486,7 +11486,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -11496,7 +11496,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -11651,7 +11651,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -11661,7 +11661,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11734,7 +11734,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -11781,7 +11781,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -11791,7 +11791,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -11967,7 +11967,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -11977,7 +11977,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12035,7 +12035,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12082,7 +12082,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12092,7 +12092,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -12326,7 +12326,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -12336,7 +12336,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16754,7 +16754,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -16806,7 +16806,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01_preview/models/_models.py
index 5777e945622e..44231122f8a4 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01_preview/models/_models.py
@@ -5208,7 +5208,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -5366,7 +5366,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -5410,7 +5410,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -6502,7 +6502,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -6524,7 +6524,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -6554,7 +6554,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6591,7 +6591,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -6616,7 +6616,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6654,7 +6654,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9123,7 +9123,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -9132,7 +9132,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -9199,7 +9199,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -11013,9 +11013,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11053,7 +11053,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11062,7 +11062,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -11170,7 +11170,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -11179,7 +11179,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11256,9 +11256,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11296,7 +11296,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11305,7 +11305,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -11430,7 +11430,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -11439,7 +11439,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11505,9 +11505,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11545,7 +11545,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11554,7 +11554,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -11727,7 +11727,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -11736,7 +11736,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11842,7 +11842,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -11889,7 +11889,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -11899,7 +11899,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -12021,7 +12021,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -12031,7 +12031,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12104,7 +12104,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12151,7 +12151,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12161,7 +12161,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -12300,7 +12300,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -12310,7 +12310,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12368,7 +12368,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12415,7 +12415,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12425,7 +12425,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -12613,7 +12613,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -12623,7 +12623,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17766,7 +17766,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -17794,7 +17794,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -17870,7 +17870,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -17915,7 +17915,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01_preview/models/_models_py3.py
index c47780374ad4..0906058e44d8 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_10_01_preview/models/_models_py3.py
@@ -5606,7 +5606,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -5774,7 +5774,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -5825,7 +5825,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -7003,7 +7003,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -7029,7 +7029,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -7059,7 +7059,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -7100,7 +7100,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -7125,7 +7125,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -7168,7 +7168,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9806,7 +9806,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -9815,7 +9815,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -9893,7 +9893,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -11867,9 +11867,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11907,7 +11907,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11916,7 +11916,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -12053,7 +12053,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -12062,7 +12062,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12139,9 +12139,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -12179,7 +12179,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -12188,7 +12188,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -12346,7 +12346,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -12355,7 +12355,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12421,9 +12421,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -12461,7 +12461,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -12470,7 +12470,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -12685,7 +12685,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -12694,7 +12694,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12800,7 +12800,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12847,7 +12847,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12857,7 +12857,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -13012,7 +13012,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -13022,7 +13022,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -13095,7 +13095,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -13142,7 +13142,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -13152,7 +13152,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -13328,7 +13328,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -13338,7 +13338,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -13396,7 +13396,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -13443,7 +13443,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -13453,7 +13453,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -13687,7 +13687,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -13697,7 +13697,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -19257,7 +19257,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -19291,7 +19291,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -19372,7 +19372,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -19424,7 +19424,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_12_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_12_01_preview/models/_models.py
index f356eacab583..ee6cd0648ca6 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_12_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_12_01_preview/models/_models.py
@@ -5272,7 +5272,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -5430,7 +5430,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -5474,7 +5474,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -6606,7 +6606,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6643,7 +6643,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -6668,7 +6668,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6706,7 +6706,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9199,7 +9199,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -9208,7 +9208,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -9279,7 +9279,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -11256,9 +11256,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11296,7 +11296,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11305,7 +11305,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -11413,7 +11413,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -11422,7 +11422,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11499,9 +11499,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11539,7 +11539,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11548,7 +11548,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -11673,7 +11673,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -11682,7 +11682,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11748,9 +11748,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11788,7 +11788,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11797,7 +11797,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -11970,7 +11970,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -11979,7 +11979,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12085,7 +12085,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12132,7 +12132,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12142,7 +12142,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -12264,7 +12264,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -12274,7 +12274,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12347,7 +12347,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12394,7 +12394,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12404,7 +12404,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -12543,7 +12543,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -12553,7 +12553,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12611,7 +12611,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12658,7 +12658,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12668,7 +12668,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -12856,7 +12856,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -12866,7 +12866,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18385,7 +18385,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -18430,7 +18430,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_12_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_12_01_preview/models/_models_py3.py
index 23ce50459383..3b0b4eebd05f 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_12_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2022_12_01_preview/models/_models_py3.py
@@ -5680,7 +5680,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -5848,7 +5848,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -5899,7 +5899,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -7122,7 +7122,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -7163,7 +7163,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -7188,7 +7188,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -7231,7 +7231,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9901,7 +9901,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -9910,7 +9910,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -9993,7 +9993,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -12145,9 +12145,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -12185,7 +12185,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -12194,7 +12194,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -12331,7 +12331,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -12340,7 +12340,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12417,9 +12417,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -12457,7 +12457,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -12466,7 +12466,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -12624,7 +12624,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -12633,7 +12633,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12699,9 +12699,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
`
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -12739,7 +12739,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -12748,7 +12748,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -12963,7 +12963,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -12972,7 +12972,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -13078,7 +13078,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -13125,7 +13125,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -13135,7 +13135,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -13290,7 +13290,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -13300,7 +13300,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -13373,7 +13373,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -13420,7 +13420,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -13430,7 +13430,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -13606,7 +13606,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -13616,7 +13616,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -13674,7 +13674,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -13721,7 +13721,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -13731,7 +13731,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -13965,7 +13965,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -13975,7 +13975,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -19945,7 +19945,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -19997,7 +19997,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_02_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_02_01_preview/models/_models.py
index cc1e5c306263..b4e41749877c 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_02_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_02_01_preview/models/_models.py
@@ -5295,7 +5295,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -5444,7 +5444,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -5485,7 +5485,7 @@ def __init__(self, **kwargs):
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -6529,7 +6529,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6561,7 +6561,7 @@ def __init__(self, **kwargs):
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -6586,7 +6586,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6621,7 +6621,7 @@ def __init__(self, **kwargs):
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8991,7 +8991,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -9000,7 +9000,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -9068,7 +9068,7 @@ def __init__(self, **kwargs):
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -11653,9 +11653,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+ https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11693,7 +11693,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11702,7 +11702,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -11807,7 +11807,7 @@ def __init__(self, **kwargs):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -11816,7 +11816,7 @@ def __init__(self, **kwargs):
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11893,9 +11893,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+ https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11933,7 +11933,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11942,7 +11942,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -12064,7 +12064,7 @@ def __init__(self, **kwargs):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -12073,7 +12073,7 @@ def __init__(self, **kwargs):
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12139,9 +12139,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+ https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -12179,7 +12179,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -12188,7 +12188,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -12358,7 +12358,7 @@ def __init__(self, **kwargs):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -12367,7 +12367,7 @@ def __init__(self, **kwargs):
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12473,7 +12473,7 @@ def __init__(self, **kwargs):
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12520,7 +12520,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12530,7 +12530,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -12649,7 +12649,7 @@ def __init__(self, **kwargs):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -12659,7 +12659,7 @@ def __init__(self, **kwargs):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12732,7 +12732,7 @@ def __init__(self, **kwargs):
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12779,7 +12779,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12789,7 +12789,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -12925,7 +12925,7 @@ def __init__(self, **kwargs):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -12935,7 +12935,7 @@ def __init__(self, **kwargs):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12993,7 +12993,7 @@ def __init__(self, **kwargs):
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -13040,7 +13040,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -13050,7 +13050,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -13235,7 +13235,7 @@ def __init__(self, **kwargs):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -13245,7 +13245,7 @@ def __init__(self, **kwargs):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18750,7 +18750,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -18792,7 +18792,7 @@ def __init__(self, **kwargs):
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_02_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_02_01_preview/models/_models_py3.py
index a93bc6dcd7c1..ec36e0e8877e 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_02_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_02_01_preview/models/_models_py3.py
@@ -5900,7 +5900,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -6061,7 +6061,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -6112,7 +6112,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -7264,7 +7264,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -7303,7 +7303,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -7328,7 +7328,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -7371,7 +7371,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9941,7 +9941,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -9950,7 +9950,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -10033,7 +10033,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -12994,9 +12994,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+ https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -13034,7 +13034,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -13043,7 +13043,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -13180,7 +13180,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -13189,7 +13189,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -13266,9 +13266,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+ https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -13306,7 +13306,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -13315,7 +13315,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -13473,7 +13473,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -13482,7 +13482,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -13578,9 +13578,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+ https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -13618,7 +13618,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -13627,7 +13627,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -13842,7 +13842,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -13851,7 +13851,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -13987,7 +13987,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -14034,7 +14034,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -14044,7 +14044,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -14199,7 +14199,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -14209,7 +14209,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -14282,7 +14282,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -14329,7 +14329,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -14339,7 +14339,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -14515,7 +14515,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -14525,7 +14525,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -14617,7 +14617,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -14664,7 +14664,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -14674,7 +14674,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -14908,7 +14908,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -14918,7 +14918,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -21152,7 +21152,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -21204,7 +21204,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01/models/_models.py
index 7f4f5f5c7878..99ab08757dd7 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01/models/_models.py
@@ -4843,7 +4843,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -5001,7 +5001,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -5045,7 +5045,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -6101,7 +6101,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -6123,7 +6123,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -6153,7 +6153,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6190,7 +6190,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -6215,7 +6215,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6253,7 +6253,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8565,7 +8565,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -8574,7 +8574,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -8648,7 +8648,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -10368,9 +10368,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -10408,7 +10408,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -10417,7 +10417,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -10525,7 +10525,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -10534,7 +10534,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -10611,9 +10611,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -10651,7 +10651,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -10660,7 +10660,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -10785,7 +10785,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -10794,7 +10794,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -10860,9 +10860,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -10900,7 +10900,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -10909,7 +10909,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -11082,7 +11082,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -11091,7 +11091,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11197,7 +11197,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -11244,7 +11244,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -11254,7 +11254,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -11376,7 +11376,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -11386,7 +11386,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11459,7 +11459,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -11506,7 +11506,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -11516,7 +11516,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -11655,7 +11655,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -11665,7 +11665,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11723,7 +11723,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -11770,7 +11770,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -11780,7 +11780,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -11968,7 +11968,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -11978,7 +11978,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16483,7 +16483,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -16511,7 +16511,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -16587,7 +16587,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -16632,7 +16632,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01/models/_models_py3.py
index 619d69b1ab62..54ca7c66aead 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01/models/_models_py3.py
@@ -5220,7 +5220,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -5388,7 +5388,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -5439,7 +5439,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -6580,7 +6580,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -6606,7 +6606,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -6636,7 +6636,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6677,7 +6677,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -6702,7 +6702,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -6745,7 +6745,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9228,7 +9228,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -9237,7 +9237,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -9324,7 +9324,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -11195,9 +11195,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11235,7 +11235,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11244,7 +11244,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -11381,7 +11381,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -11390,7 +11390,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11467,9 +11467,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11507,7 +11507,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11516,7 +11516,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -11674,7 +11674,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -11683,7 +11683,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -11749,9 +11749,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -11789,7 +11789,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -11798,7 +11798,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -12013,7 +12013,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -12022,7 +12022,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12128,7 +12128,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12175,7 +12175,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12185,7 +12185,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -12340,7 +12340,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -12350,7 +12350,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12423,7 +12423,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12470,7 +12470,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12480,7 +12480,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -12656,7 +12656,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -12666,7 +12666,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -12724,7 +12724,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -12771,7 +12771,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -12781,7 +12781,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -13015,7 +13015,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -13025,7 +13025,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17892,7 +17892,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -17926,7 +17926,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -18007,7 +18007,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -18059,7 +18059,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models.py
index d0b0e1b5f374..1165d3eb8142 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models.py
@@ -6349,7 +6349,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -6511,7 +6511,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -6563,7 +6563,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
:keyword stage: Stage in the component lifecycle.
@@ -7759,7 +7759,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -7781,7 +7781,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -7811,7 +7811,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -7848,7 +7848,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -7873,7 +7873,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -7911,7 +7911,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -11080,7 +11080,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -11089,7 +11089,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -11172,7 +11172,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -14307,9 +14307,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -14347,7 +14347,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -14356,7 +14356,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -14464,7 +14464,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -14473,7 +14473,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -14550,9 +14550,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -14590,7 +14590,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -14599,7 +14599,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -14724,7 +14724,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -14733,7 +14733,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -14799,9 +14799,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -14839,7 +14839,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -14848,7 +14848,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15021,7 +15021,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15030,7 +15030,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15136,7 +15136,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -15183,7 +15183,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -15193,7 +15193,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -15315,7 +15315,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -15325,7 +15325,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15398,7 +15398,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -15445,7 +15445,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -15455,7 +15455,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -15594,7 +15594,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -15604,7 +15604,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15662,7 +15662,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -15709,7 +15709,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -15719,7 +15719,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -15917,7 +15917,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -15927,7 +15927,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -23358,7 +23358,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -23386,7 +23386,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -23462,7 +23462,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -23507,7 +23507,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models_py3.py
index 626f8ed291bf..b8e2b7bcd701 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_04_01_preview/models/_models_py3.py
@@ -6823,7 +6823,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -6995,7 +6995,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -7056,7 +7056,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
:keyword stage: Stage in the component lifecycle.
@@ -8345,7 +8345,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8371,7 +8371,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8401,7 +8401,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8442,7 +8442,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -8467,7 +8467,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8510,7 +8510,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -11919,7 +11919,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -11928,7 +11928,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -12026,7 +12026,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -15438,9 +15438,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -15478,7 +15478,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -15487,7 +15487,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15624,7 +15624,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15633,7 +15633,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15710,9 +15710,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -15750,7 +15750,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -15759,7 +15759,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15917,7 +15917,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15926,7 +15926,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15992,9 +15992,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16032,7 +16032,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16041,7 +16041,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -16256,7 +16256,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -16265,7 +16265,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16371,7 +16371,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -16418,7 +16418,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -16428,7 +16428,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -16583,7 +16583,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -16593,7 +16593,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16666,7 +16666,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -16713,7 +16713,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -16723,7 +16723,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -16899,7 +16899,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -16909,7 +16909,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16967,7 +16967,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17014,7 +17014,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17024,7 +17024,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -17270,7 +17270,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -17280,7 +17280,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -25319,7 +25319,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -25353,7 +25353,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -25434,7 +25434,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -25486,7 +25486,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_06_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_06_01_preview/models/_models.py
index fe9068164eb6..d2ae30a5af84 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_06_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_06_01_preview/models/_models.py
@@ -6452,7 +6452,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -6614,7 +6614,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -6666,7 +6666,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
:keyword stage: Stage in the component lifecycle.
@@ -7862,7 +7862,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -7884,7 +7884,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -7914,7 +7914,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -7951,7 +7951,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -7976,7 +7976,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8014,7 +8014,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -11287,7 +11287,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -11296,7 +11296,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -11379,7 +11379,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -14863,9 +14863,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -14903,7 +14903,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -14912,7 +14912,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15020,7 +15020,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15029,7 +15029,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15106,9 +15106,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -15146,7 +15146,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -15155,7 +15155,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15280,7 +15280,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15289,7 +15289,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15355,9 +15355,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -15395,7 +15395,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -15404,7 +15404,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15577,7 +15577,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15586,7 +15586,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15692,7 +15692,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -15739,7 +15739,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -15749,7 +15749,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -15871,7 +15871,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -15881,7 +15881,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15954,7 +15954,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -16001,7 +16001,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -16011,7 +16011,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -16150,7 +16150,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -16160,7 +16160,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16218,7 +16218,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -16265,7 +16265,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -16275,7 +16275,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -16473,7 +16473,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -16483,7 +16483,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -23883,7 +23883,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -23911,7 +23911,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -23987,7 +23987,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -24032,7 +24032,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_06_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_06_01_preview/models/_models_py3.py
index e963a760a83f..824fef4839bb 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_06_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_06_01_preview/models/_models_py3.py
@@ -6926,7 +6926,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -7098,7 +7098,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -7159,7 +7159,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
:keyword stage: Stage in the component lifecycle.
@@ -8448,7 +8448,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8474,7 +8474,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8504,7 +8504,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8545,7 +8545,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -8570,7 +8570,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8613,7 +8613,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -12137,7 +12137,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -12146,7 +12146,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -12244,7 +12244,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -16033,9 +16033,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16073,7 +16073,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16082,7 +16082,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -16219,7 +16219,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -16228,7 +16228,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16305,9 +16305,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16345,7 +16345,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16354,7 +16354,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -16512,7 +16512,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -16521,7 +16521,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16587,9 +16587,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16627,7 +16627,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16636,7 +16636,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -16851,7 +16851,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -16860,7 +16860,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16966,7 +16966,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17013,7 +17013,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17023,7 +17023,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -17178,7 +17178,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -17188,7 +17188,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17261,7 +17261,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17308,7 +17308,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17318,7 +17318,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -17494,7 +17494,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -17504,7 +17504,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17562,7 +17562,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17609,7 +17609,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17619,7 +17619,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -17865,7 +17865,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -17875,7 +17875,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -25885,7 +25885,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -25919,7 +25919,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.RecurrenceSchedule
@@ -26000,7 +26000,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -26052,7 +26052,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_08_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_08_01_preview/models/_models.py
index 1c1b3c539fdd..d22720e97eee 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_08_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_08_01_preview/models/_models.py
@@ -6614,7 +6614,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -6776,7 +6776,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -6828,7 +6828,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
:keyword stage: Stage in the component lifecycle.
@@ -8102,7 +8102,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8124,7 +8124,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8154,7 +8154,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8191,7 +8191,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -8216,7 +8216,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8254,7 +8254,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -11534,7 +11534,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -11543,7 +11543,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -11626,7 +11626,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -15155,9 +15155,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -15195,7 +15195,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -15204,7 +15204,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15312,7 +15312,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15321,7 +15321,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15398,9 +15398,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -15438,7 +15438,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -15447,7 +15447,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15572,7 +15572,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15581,7 +15581,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15647,9 +15647,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -15687,7 +15687,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -15696,7 +15696,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15869,7 +15869,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15878,7 +15878,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15984,7 +15984,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -16031,7 +16031,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -16041,7 +16041,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -16163,7 +16163,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -16173,7 +16173,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16246,7 +16246,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -16293,7 +16293,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -16303,7 +16303,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -16442,7 +16442,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -16452,7 +16452,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16510,7 +16510,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -16557,7 +16557,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -16567,7 +16567,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -16765,7 +16765,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -16775,7 +16775,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -25177,7 +25177,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -25206,7 +25206,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -25282,7 +25282,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -25327,7 +25327,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_08_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_08_01_preview/models/_models_py3.py
index 87cbd3851fef..6911dae5a24c 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_08_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_08_01_preview/models/_models_py3.py
@@ -7103,7 +7103,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -7275,7 +7275,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -7336,7 +7336,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
:keyword stage: Stage in the component lifecycle.
@@ -8712,7 +8712,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8738,7 +8738,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8768,7 +8768,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8809,7 +8809,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -8834,7 +8834,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8877,7 +8877,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -12411,7 +12411,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -12420,7 +12420,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -12518,7 +12518,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -16355,9 +16355,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16395,7 +16395,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16404,7 +16404,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -16541,7 +16541,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -16550,7 +16550,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16627,9 +16627,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16667,7 +16667,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16676,7 +16676,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -16834,7 +16834,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -16843,7 +16843,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16909,9 +16909,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16949,7 +16949,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16958,7 +16958,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -17173,7 +17173,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -17182,7 +17182,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17288,7 +17288,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17335,7 +17335,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17345,7 +17345,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -17500,7 +17500,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -17510,7 +17510,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17583,7 +17583,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17630,7 +17630,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17640,7 +17640,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -17816,7 +17816,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -17826,7 +17826,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17884,7 +17884,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17931,7 +17931,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17941,7 +17941,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -18187,7 +18187,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -18197,7 +18197,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -27293,7 +27293,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -27328,7 +27328,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -27409,7 +27409,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -27461,7 +27461,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_10_01/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_10_01/models/_models_py3.py
index e69cc93262a8..0129e8fa69d6 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_10_01/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2023_10_01/models/_models_py3.py
@@ -5720,7 +5720,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
.
Variables are only populated by the server, and will be ignored when sending a request.
@@ -5884,7 +5884,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: JSON
:ivar provisioning_state: Provisioning state for the component version. Known values are:
@@ -5935,7 +5935,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: JSON
"""
@@ -7165,7 +7165,7 @@ class Cron(_serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -7191,7 +7191,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -7221,7 +7221,7 @@ class TriggerBase(_serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: [Required]. Required. Known values are: "Recurrence" and "Cron".
:vartype trigger_type: str or ~azure.mgmt.machinelearningservices.models.TriggerType
@@ -7254,7 +7254,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super().__init__(**kwargs)
@@ -7279,7 +7279,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: [Required]. Required. Known values are: "Recurrence" and "Cron".
:vartype trigger_type: str or ~azure.mgmt.machinelearningservices.models.TriggerType
@@ -7321,7 +7321,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format. Required.
@@ -10111,7 +10111,7 @@ class EnvironmentVersionProperties(AssetBase): # pylint: disable=too-many-insta
.. raw:: html
. Known values are: "Curated" and "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -10120,7 +10120,7 @@ class EnvironmentVersionProperties(AssetBase): # pylint: disable=too-many-insta
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -10207,7 +10207,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -13556,9 +13556,9 @@ class ImageModelDistributionSettings(_serialization.Model): # pylint: disable=t
valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+ https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -13596,7 +13596,7 @@ class ImageModelDistributionSettings(_serialization.Model): # pylint: disable=t
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -13605,7 +13605,7 @@ class ImageModelDistributionSettings(_serialization.Model): # pylint: disable=t
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -13742,7 +13742,7 @@ def __init__( # pylint: disable=too-many-locals
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -13751,7 +13751,7 @@ def __init__( # pylint: disable=too-many-locals
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -13830,9 +13830,9 @@ class ImageModelDistributionSettingsClassification(
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+ https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -13870,7 +13870,7 @@ class ImageModelDistributionSettingsClassification(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -13879,7 +13879,7 @@ class ImageModelDistributionSettingsClassification(
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -14037,7 +14037,7 @@ def __init__( # pylint: disable=too-many-locals
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -14046,7 +14046,7 @@ def __init__( # pylint: disable=too-many-locals
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -14144,9 +14144,9 @@ class ImageModelDistributionSettingsObjectDetection(
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+ https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -14184,7 +14184,7 @@ class ImageModelDistributionSettingsObjectDetection(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -14193,7 +14193,7 @@ class ImageModelDistributionSettingsObjectDetection(
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -14408,7 +14408,7 @@ def __init__( # pylint: disable=too-many-locals
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -14417,7 +14417,7 @@ def __init__( # pylint: disable=too-many-locals
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -14553,7 +14553,7 @@ def __init__( # pylint: disable=too-many-locals
class ImageModelSettings(_serialization.Model): # pylint: disable=too-many-instance-attributes
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -14600,7 +14600,7 @@ class ImageModelSettings(_serialization.Model): # pylint: disable=too-many-inst
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -14610,7 +14610,7 @@ class ImageModelSettings(_serialization.Model): # pylint: disable=too-many-inst
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -14765,7 +14765,7 @@ def __init__( # pylint: disable=too-many-locals
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -14775,7 +14775,7 @@ def __init__( # pylint: disable=too-many-locals
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -14848,7 +14848,7 @@ def __init__( # pylint: disable=too-many-locals
class ImageModelSettingsClassification(ImageModelSettings): # pylint: disable=too-many-instance-attributes
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -14895,7 +14895,7 @@ class ImageModelSettingsClassification(ImageModelSettings): # pylint: disable=t
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -14905,7 +14905,7 @@ class ImageModelSettingsClassification(ImageModelSettings): # pylint: disable=t
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -15081,7 +15081,7 @@ def __init__( # pylint: disable=too-many-locals
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -15091,7 +15091,7 @@ def __init__( # pylint: disable=too-many-locals
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15183,7 +15183,7 @@ def __init__( # pylint: disable=too-many-locals
class ImageModelSettingsObjectDetection(ImageModelSettings): # pylint: disable=too-many-instance-attributes
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -15230,7 +15230,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings): # pylint: disable=
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -15240,7 +15240,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings): # pylint: disable=
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -15474,7 +15474,7 @@ def __init__( # pylint: disable=too-many-locals
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -15484,7 +15484,7 @@ def __init__( # pylint: disable=too-many-locals
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -21214,7 +21214,7 @@ class Recurrence(_serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -21249,7 +21249,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -21330,7 +21330,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: [Required]. Required. Known values are: "Recurrence" and "Cron".
:vartype trigger_type: str or ~azure.mgmt.machinelearningservices.models.TriggerType
@@ -21381,7 +21381,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: [Required] The frequency to trigger schedule. Required. Known values are:
"Minute", "Hour", "Day", "Week", and "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_01_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_01_01_preview/models/_models.py
index 72261ed2910c..ae7539830f7c 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_01_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_01_01_preview/models/_models.py
@@ -7562,7 +7562,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -7724,7 +7724,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -7776,7 +7776,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
:keyword stage: Stage in the component lifecycle.
@@ -9306,7 +9306,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9328,7 +9328,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9358,7 +9358,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -9395,7 +9395,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -9420,7 +9420,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -9458,7 +9458,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -13180,7 +13180,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -13189,7 +13189,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -13272,7 +13272,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -17014,9 +17014,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -17054,7 +17054,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -17063,7 +17063,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -17171,7 +17171,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -17180,7 +17180,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17257,9 +17257,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -17297,7 +17297,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -17306,7 +17306,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -17431,7 +17431,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -17440,7 +17440,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17506,9 +17506,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -17546,7 +17546,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -17555,7 +17555,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -17728,7 +17728,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -17737,7 +17737,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17843,7 +17843,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17890,7 +17890,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17900,7 +17900,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -18022,7 +18022,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -18032,7 +18032,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18105,7 +18105,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -18152,7 +18152,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -18162,7 +18162,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -18301,7 +18301,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -18311,7 +18311,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18369,7 +18369,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -18416,7 +18416,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -18426,7 +18426,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -18624,7 +18624,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -18634,7 +18634,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -27895,7 +27895,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -27924,7 +27924,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -28000,7 +28000,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -28045,7 +28045,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_01_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_01_01_preview/models/_models_py3.py
index d967e0c7e151..0cce7c2c64a8 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_01_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_01_01_preview/models/_models_py3.py
@@ -8128,7 +8128,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -8300,7 +8300,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -8361,7 +8361,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
:keyword stage: Stage in the component lifecycle.
@@ -10012,7 +10012,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -10038,7 +10038,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -10068,7 +10068,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -10109,7 +10109,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -10134,7 +10134,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -10177,7 +10177,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -14189,7 +14189,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -14198,7 +14198,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -14296,7 +14296,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -18370,9 +18370,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -18410,7 +18410,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -18419,7 +18419,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -18556,7 +18556,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -18565,7 +18565,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18642,9 +18642,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -18682,7 +18682,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -18691,7 +18691,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -18849,7 +18849,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -18858,7 +18858,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18924,9 +18924,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -18964,7 +18964,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -18973,7 +18973,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -19188,7 +19188,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -19197,7 +19197,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -19303,7 +19303,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -19350,7 +19350,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -19360,7 +19360,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -19515,7 +19515,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -19525,7 +19525,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -19598,7 +19598,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -19645,7 +19645,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -19655,7 +19655,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -19831,7 +19831,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -19841,7 +19841,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -19899,7 +19899,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -19946,7 +19946,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -19956,7 +19956,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -20202,7 +20202,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -20212,7 +20212,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -30228,7 +30228,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -30263,7 +30263,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -30344,7 +30344,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -30396,7 +30396,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_04_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_04_01_preview/models/_models.py
index e791f7b72139..daccee47223c 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_04_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_04_01_preview/models/_models.py
@@ -7571,7 +7571,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -7733,7 +7733,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -7785,7 +7785,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
:keyword stage: Stage in the component lifecycle.
@@ -9334,7 +9334,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9356,7 +9356,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9386,7 +9386,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -9423,7 +9423,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -9448,7 +9448,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -9486,7 +9486,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -13210,7 +13210,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -13219,7 +13219,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -13302,7 +13302,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -17067,9 +17067,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -17107,7 +17107,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -17116,7 +17116,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -17224,7 +17224,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -17233,7 +17233,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17310,9 +17310,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -17350,7 +17350,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -17359,7 +17359,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -17484,7 +17484,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -17493,7 +17493,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17559,9 +17559,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -17599,7 +17599,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -17608,7 +17608,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -17781,7 +17781,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -17790,7 +17790,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17896,7 +17896,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17943,7 +17943,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17953,7 +17953,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -18075,7 +18075,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -18085,7 +18085,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18158,7 +18158,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -18205,7 +18205,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -18215,7 +18215,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -18354,7 +18354,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -18364,7 +18364,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18422,7 +18422,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -18469,7 +18469,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -18479,7 +18479,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -18677,7 +18677,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -18687,7 +18687,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -28431,7 +28431,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -28460,7 +28460,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -28536,7 +28536,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -28581,7 +28581,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_04_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_04_01_preview/models/_models_py3.py
index 8e5625ef3647..dcb2def94e72 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_04_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_04_01_preview/models/_models_py3.py
@@ -8137,7 +8137,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -8309,7 +8309,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -8370,7 +8370,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
:keyword stage: Stage in the component lifecycle.
@@ -10042,7 +10042,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -10068,7 +10068,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -10098,7 +10098,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -10139,7 +10139,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -10164,7 +10164,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -10207,7 +10207,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -14221,7 +14221,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -14230,7 +14230,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -14328,7 +14328,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -18427,9 +18427,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -18467,7 +18467,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -18476,7 +18476,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -18613,7 +18613,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -18622,7 +18622,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18699,9 +18699,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -18739,7 +18739,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -18748,7 +18748,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -18906,7 +18906,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -18915,7 +18915,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18981,9 +18981,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -19021,7 +19021,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -19030,7 +19030,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -19245,7 +19245,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -19254,7 +19254,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -19360,7 +19360,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -19407,7 +19407,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -19417,7 +19417,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -19572,7 +19572,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -19582,7 +19582,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -19655,7 +19655,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -19702,7 +19702,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -19712,7 +19712,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -19888,7 +19888,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -19898,7 +19898,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -19956,7 +19956,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -20003,7 +20003,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -20013,7 +20013,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -20259,7 +20259,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -20269,7 +20269,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -30808,7 +30808,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -30843,7 +30843,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -30924,7 +30924,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -30976,7 +30976,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_07_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_07_01_preview/models/_models.py
index 4367e5524e01..6a382c7e1252 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_07_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_07_01_preview/models/_models.py
@@ -6450,7 +6450,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -6608,7 +6608,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -6652,7 +6652,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -8265,7 +8265,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8287,7 +8287,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8317,7 +8317,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8354,7 +8354,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -8379,7 +8379,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8417,7 +8417,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -11990,7 +11990,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -11999,7 +11999,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -12073,7 +12073,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -15229,9 +15229,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -15269,7 +15269,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -15278,7 +15278,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15386,7 +15386,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15395,7 +15395,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15472,9 +15472,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -15512,7 +15512,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -15521,7 +15521,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15646,7 +15646,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15655,7 +15655,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -15721,9 +15721,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -15761,7 +15761,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -15770,7 +15770,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -15943,7 +15943,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -15952,7 +15952,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16058,7 +16058,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -16105,7 +16105,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -16115,7 +16115,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -16237,7 +16237,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -16247,7 +16247,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16320,7 +16320,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -16367,7 +16367,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -16377,7 +16377,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -16516,7 +16516,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -16526,7 +16526,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16584,7 +16584,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -16631,7 +16631,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -16641,7 +16641,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -16829,7 +16829,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -16839,7 +16839,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -23984,7 +23984,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -24013,7 +24013,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -24089,7 +24089,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -24134,7 +24134,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_07_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_07_01_preview/models/_models_py3.py
index d385b6fae657..fa9ed84e1e80 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_07_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_07_01_preview/models/_models_py3.py
@@ -6939,7 +6939,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -7107,7 +7107,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -7158,7 +7158,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -8899,7 +8899,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8925,7 +8925,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8955,7 +8955,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8996,7 +8996,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -9021,7 +9021,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -9064,7 +9064,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -12927,7 +12927,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -12936,7 +12936,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -13023,7 +13023,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -16453,9 +16453,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16493,7 +16493,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16502,7 +16502,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -16639,7 +16639,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -16648,7 +16648,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16725,9 +16725,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16765,7 +16765,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16774,7 +16774,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -16932,7 +16932,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -16941,7 +16941,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17007,9 +17007,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -17047,7 +17047,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -17056,7 +17056,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -17271,7 +17271,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -17280,7 +17280,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17386,7 +17386,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17433,7 +17433,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17443,7 +17443,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -17598,7 +17598,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -17608,7 +17608,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17681,7 +17681,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17728,7 +17728,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17738,7 +17738,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -17914,7 +17914,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -17924,7 +17924,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17982,7 +17982,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -18029,7 +18029,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -18039,7 +18039,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -18273,7 +18273,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -18283,7 +18283,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -26007,7 +26007,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -26042,7 +26042,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -26123,7 +26123,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -26175,7 +26175,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_10_01_preview/models/_models.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_10_01_preview/models/_models.py
index 2f3261e47885..e998cda3ae50 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_10_01_preview/models/_models.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_10_01_preview/models/_models.py
@@ -6801,7 +6801,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -6959,7 +6959,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -7003,7 +7003,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -8622,7 +8622,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8644,7 +8644,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -8674,7 +8674,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8711,7 +8711,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -8736,7 +8736,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -8774,7 +8774,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -12606,7 +12606,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -12615,7 +12615,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -12689,7 +12689,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -16084,9 +16084,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16124,7 +16124,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16133,7 +16133,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -16241,7 +16241,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -16250,7 +16250,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16327,9 +16327,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16367,7 +16367,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16376,7 +16376,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -16501,7 +16501,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -16510,7 +16510,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16576,9 +16576,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -16616,7 +16616,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -16625,7 +16625,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -16798,7 +16798,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -16807,7 +16807,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -16913,7 +16913,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -16960,7 +16960,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -16970,7 +16970,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -17092,7 +17092,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -17102,7 +17102,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17175,7 +17175,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17222,7 +17222,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17232,7 +17232,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -17371,7 +17371,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -17381,7 +17381,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17439,7 +17439,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -17486,7 +17486,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -17496,7 +17496,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -17684,7 +17684,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -17694,7 +17694,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -25506,7 +25506,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -25535,7 +25535,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -25611,7 +25611,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -25656,7 +25656,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_10_01_preview/models/_models_py3.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_10_01_preview/models/_models_py3.py
index fcb36586ee8b..05353fd2ca50 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_10_01_preview/models/_models_py3.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_restclient/v2024_10_01_preview/models/_models_py3.py
@@ -7322,7 +7322,7 @@ class ComponentContainerProperties(AssetContainer):
.. raw:: html
- .
+ .
Variables are only populated by the server, and will be ignored when sending a request.
@@ -7490,7 +7490,7 @@ class ComponentVersionProperties(AssetBase):
.. raw:: html
.
:vartype component_spec: any
:ivar provisioning_state: Provisioning state for the component version. Possible values
@@ -7541,7 +7541,7 @@ def __init__(
.. raw:: html
.
:paramtype component_spec: any
"""
@@ -9289,7 +9289,7 @@ class Cron(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9315,7 +9315,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -9345,7 +9345,7 @@ class TriggerBase(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -9386,7 +9386,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
"""
super(TriggerBase, self).__init__(**kwargs)
@@ -9411,7 +9411,7 @@ class CronTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -9454,7 +9454,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword expression: Required. [Required] Specifies cron expression of schedule.
The expression should follow NCronTab format.
@@ -13604,7 +13604,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
. Possible values include: "Curated", "UserCreated".
:vartype environment_type: str or ~azure.mgmt.machinelearningservices.models.EnvironmentType
:ivar image: Name of the image that will be used for the environment.
@@ -13613,7 +13613,7 @@ class EnvironmentVersionProperties(AssetBase):
.. raw:: html
.
:vartype image: str
:ivar inference_config: Defines configuration specific to inference.
@@ -13700,7 +13700,7 @@ def __init__(
.. raw:: html
.
:paramtype image: str
:keyword inference_config: Defines configuration specific to inference.
@@ -17397,9 +17397,9 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
All distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)
where distribution name can be: uniform, quniform, loguniform, etc
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -17437,7 +17437,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -17446,7 +17446,7 @@ class ImageModelDistributionSettings(msrest.serialization.Model):
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -17583,7 +17583,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -17592,7 +17592,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17669,9 +17669,9 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -17709,7 +17709,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -17718,7 +17718,7 @@ class ImageModelDistributionSettingsClassification(ImageModelDistributionSetting
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -17876,7 +17876,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -17885,7 +17885,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -17951,9 +17951,9 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
LayersToFreeze = "choice(0, 2)";
````
For more details on how to compose distribution expressions please check the documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
+https://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar ams_gradient: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
:vartype ams_gradient: str
@@ -17991,7 +17991,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: str
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: str
@@ -18000,7 +18000,7 @@ class ImageModelDistributionSettingsObjectDetection(ImageModelDistributionSettin
:vartype learning_rate_scheduler: str
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: str
@@ -18215,7 +18215,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: str
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: str
@@ -18224,7 +18224,7 @@ def __init__(
:paramtype learning_rate_scheduler: str
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18330,7 +18330,7 @@ def __init__(
class ImageModelSettings(msrest.serialization.Model):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -18377,7 +18377,7 @@ class ImageModelSettings(msrest.serialization.Model):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -18387,7 +18387,7 @@ class ImageModelSettings(msrest.serialization.Model):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -18542,7 +18542,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -18552,7 +18552,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18625,7 +18625,7 @@ def __init__(
class ImageModelSettingsClassification(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -18672,7 +18672,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -18682,7 +18682,7 @@ class ImageModelSettingsClassification(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -18858,7 +18858,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -18868,7 +18868,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -18926,7 +18926,7 @@ def __init__(
class ImageModelSettingsObjectDetection(ImageModelSettings):
"""Settings used for training the model.
For more information on the available settings please visit the official documentation:
-https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:ivar advanced_settings: Settings for advanced scenarios.
:vartype advanced_settings: str
@@ -18973,7 +18973,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype layers_to_freeze: int
:ivar learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:vartype learning_rate: float
@@ -18983,7 +18983,7 @@ class ImageModelSettingsObjectDetection(ImageModelSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:ivar model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:vartype model_name: str
:ivar momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:vartype momentum: float
@@ -19217,7 +19217,7 @@ def __init__(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -19227,7 +19227,7 @@ def __init__(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:paramtype model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
@@ -27679,7 +27679,7 @@ class Recurrence(msrest.serialization.Model):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar schedule: [Required] The recurrence schedule.
:vartype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -27714,7 +27714,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword schedule: [Required] The recurrence schedule.
:paramtype schedule: ~azure.mgmt.machinelearningservices.models.ComputeRecurrenceSchedule
@@ -27795,7 +27795,7 @@ class RecurrenceTrigger(TriggerBase):
:vartype start_time: str
:ivar time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:vartype time_zone: str
:ivar trigger_type: Required. [Required].Constant filled by server. Possible values include:
"Recurrence", "Cron".
@@ -27847,7 +27847,7 @@ def __init__(
:paramtype start_time: str
:keyword time_zone: Specifies time zone in which the schedule runs.
TimeZone should follow Windows time zone format. Refer:
- https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
+ https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11.
:paramtype time_zone: str
:keyword frequency: Required. [Required] The frequency to trigger schedule. Possible values
include: "Minute", "Hour", "Day", "Week", "Month".
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/_utils/_artifact_utils.py b/sdk/ml/azure-ai-ml/azure/ai/ml/_utils/_artifact_utils.py
index 8b19c7c36e39..9dafaf79e339 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/_utils/_artifact_utils.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/_utils/_artifact_utils.py
@@ -132,7 +132,7 @@ def get_organization_project_by_git():
# Organization URL has two format, https://dev.azure.com/{organization} and
# https://{organization}.visualstudio.com
- # https://docs.microsoft.com/en-us/azure/devops/extend/develop/work-with-urls?view=azure-devops&tabs=http
+ # https://learn.microsoft.com/azure/devops/extend/develop/work-with-urls?view=azure-devops&tabs=http
if "dev.azure.com" in origin_url:
regex = r"^https:\/\/\w*@?dev\.azure\.com\/(\w*)\/(\w*)"
results = re.findall(regex, origin_url)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_image.py b/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_image.py
index 82ac498268fb..521c9aa2064d 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_image.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_image.py
@@ -80,7 +80,7 @@ def image_classification(
:keyword primary_metric: The metric that Automated Machine Learning will optimize for model selection.
Automated Machine Learning collects more metrics than it can optimize.
For more information on how metrics are calculated, see
- https://docs.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
+ https://learn.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
Acceptable values: accuracy, AUC_weighted, norm_macro_recall, average_precision_score_weighted,
and precision_score_weighted
@@ -140,7 +140,7 @@ def image_classification_multilabel(
:keyword primary_metric: The metric that Automated Machine Learning will optimize for model selection.
Automated Machine Learning collects more metrics than it can optimize.
For more information on how metrics are calculated, see
- https://docs.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
+ https://learn.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
Acceptable values: accuracy, AUC_weighted, norm_macro_recall, average_precision_score_weighted,
precision_score_weighted, and Iou
@@ -200,7 +200,7 @@ def image_object_detection(
:keyword primary_metric: The metric that Automated Machine Learning will optimize for model selection.
Automated Machine Learning collects more metrics than it can optimize.
For more information on how metrics are calculated, see
- https://docs.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
+ https://learn.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
Acceptable values: MeanAveragePrecision
Defaults to MeanAveragePrecision.
@@ -259,7 +259,7 @@ def image_instance_segmentation(
:keyword primary_metric: The metric that Automated Machine Learning will optimize for model selection.
Automated Machine Learning collects more metrics than it can optimize.
For more information on how metrics are calculated, see
- https://docs.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
+ https://learn.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
Acceptable values: MeanAveragePrecision
Defaults to MeanAveragePrecision.
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_nlp.py b/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_nlp.py
index c7bddc3f519e..ac7ebcf6631c 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_nlp.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_nlp.py
@@ -82,7 +82,7 @@ def text_classification_multilabel(
A text classification multilabel job is used to train a model that can predict the classes/categories
of a text data. Input training data should include a target column that classifies the text into class(es).
For more information on format of multilabel data, refer to:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-nlp-models#multi-label
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-nlp-models#multi-label
:keyword training_data: The training data to be used within the experiment.
It should contain both training features and a target column.
@@ -137,7 +137,7 @@ def text_ner(
A text named entity recognition job is used to train a model that can predict the named entities in the text.
Input training data should be a text file in CoNLL format. For more information on format of text NER data,
refer to:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-nlp-models#named-entity-recognition-ner
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-nlp-models#named-entity-recognition-ner
:keyword training_data: The training data to be used within the experiment.
It should contain both training features and a target column.
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_tabular.py b/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_tabular.py
index 7d0fecc741b9..9c45e5f1c938 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_tabular.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/automl/_automl_tabular.py
@@ -46,7 +46,7 @@ def classification(
:keyword primary_metric: The metric that Automated Machine Learning will optimize for model selection.
Automated Machine Learning collects more metrics than it can optimize.
For more information on how metrics are calculated, see
- https://docs.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
+ https://learn.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
Acceptable values: accuracy, AUC_weighted, norm_macro_recall, average_precision_score_weighted,
and precision_score_weighted
@@ -56,7 +56,7 @@ def classification(
training iterations.
The default is None. For more information, see
`Interpretability: model explanations in automated machine learning
- `__.
+ `__.
:paramtype enable_model_explainability: bool
:keyword weight_column_name: The name of the sample weight column. Automated ML supports a weighted column
as an input, causing rows in the data to be weighted up or down.
@@ -78,7 +78,7 @@ def classification(
For custom cross validation fold, use ``cv_split_column_names``.
For more information, see
- `Configure data splits and cross-validation in automated machine learning `__.
Defaults to None
@@ -90,7 +90,7 @@ def classification(
For custom cross validation fold, use ``cv_split_column_names``.
For more information, see
- `Configure data splits and cross-validation in automated machine learning `__.
Defaults to None
@@ -188,7 +188,7 @@ def regression(
:keyword primary_metric: The metric that Automated Machine Learning will optimize for model selection.
Automated Machine Learning collects more metrics than it can optimize.
For more information on how metrics are calculated, see
- https://docs.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
+ https://learn.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
Acceptable values: spearman_correlation, r2_score, normalized_mean_absolute_error,
normalized_root_mean_squared_error.
@@ -198,7 +198,7 @@ def regression(
training iterations.
The default is None. For more information, see
`Interpretability: model explanations in automated machine learning
- `__.
+ `__.
:paramtype enable_model_explainability: bool
:keyword weight_column_name: The name of the sample weight column. Automated ML supports a weighted column
as an input, causing rows in the data to be weighted up or down.
@@ -220,7 +220,7 @@ def regression(
For custom cross validation fold, use ``cv_split_column_names``.
For more information, see
- `Configure data splits and cross-validation in automated machine learning `__.
Defaults to None
@@ -232,7 +232,7 @@ def regression(
For custom cross validation fold, use ``cv_split_column_names``.
For more information, see
- `Configure data splits and cross-validation in automated machine learning `__.
Defaults to None
@@ -330,7 +330,7 @@ def forecasting(
:keyword primary_metric: The metric that Automated Machine Learning will optimize for model selection.
Automated Machine Learning collects more metrics than it can optimize.
For more information on how metrics are calculated, see
- https://docs.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
+ https://learn.microsoft.com/azure/machine-learning/how-to-configure-auto-train#primary-metric.
Acceptable values: r2_score, normalized_mean_absolute_error, normalized_root_mean_squared_error
Defaults to normalized_root_mean_squared_error
@@ -339,7 +339,7 @@ def forecasting(
training iterations.
The default is None. For more information, see
`Interpretability: model explanations in automated machine learning
- `__.
+ `__.
:paramtype enable_model_explainability: bool
:keyword weight_column_name: The name of the sample weight column. Automated ML supports a weighted column
as an input, causing rows in the data to be weighted up or down.
@@ -361,7 +361,7 @@ def forecasting(
For custom cross validation fold, use ``cv_split_column_names``.
For more information, see
- `Configure data splits and cross-validation in automated machine learning `__.
Defaults to None
@@ -373,7 +373,7 @@ def forecasting(
For custom cross validation fold, use ``cv_split_column_names``.
For more information, see
- `Configure data splits and cross-validation in automated machine learning `__.
Defaults to None
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/constants/_common.py b/sdk/ml/azure-ai-ml/azure/ai/ml/constants/_common.py
index df490b0fdeb9..647b261f29b0 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/constants/_common.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/constants/_common.py
@@ -168,7 +168,7 @@
"\nAdditional Resources: The easiest way to author a yaml specification file is using IntelliSense and "
"auto-completion Azure ML VS code extension provides: "
"{link_color}https://code.visualstudio.com/docs/datascience/azure-machine-learning.{reset} "
- "To set up VS Code, visit {link_color}https://docs.microsoft.com/azure/machine-learning/how-to-setup-vs-"
+ "To set up VS Code, visit {link_color}https://learn.microsoft.com/azure/machine-learning/how-to-setup-vs-"
"code{reset}\n"
)
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_feature_store/feature_store.py b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_feature_store/feature_store.py
index 11dd9127b854..0c41f1a3e6ad 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_feature_store/feature_store.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_feature_store/feature_store.py
@@ -54,7 +54,7 @@ class FeatureStore(Workspace):
:param hbi_workspace: Boolean for whether the customer data is of high business impact (HBI),
containing sensitive business information. Defaults to False.
For more information, see
- https://docs.microsoft.com/azure/machine-learning/concept-data-encryption#encryption-at-rest.
+ https://learn.microsoft.com/azure/machine-learning/concept-data-encryption#encryption-at-rest.
:type hbi_workspace: Optional[bool]
:param storage_account: The resource ID of an existing storage account to use instead of creating a new one.
Defaults to None.
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/automl_image_classification_base.py b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/automl_image_classification_base.py
index 3d73ba7b7c62..ef0c8a2db679 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/automl_image_classification_base.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/automl_image_classification_base.py
@@ -219,7 +219,7 @@ def set_training_parameters(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/reference-automl-images-hyperparameters#model-agnostic-hyperparameters. # pylint: disable=line-too-long
+ see: https://learn.microsoft.com/azure/machine-learning/reference-automl-images-hyperparameters#model-agnostic-hyperparameters. # pylint: disable=line-too-long
:type layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -229,7 +229,7 @@ def set_training_parameters(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:type model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/automl_image_object_detection_base.py b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/automl_image_object_detection_base.py
index 5ae6fd0e1280..db0c7bc6c660 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/automl_image_object_detection_base.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/automl_image_object_detection_base.py
@@ -220,7 +220,7 @@ def set_training_parameters(
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/reference-automl-images-hyperparameters#model-agnostic-hyperparameters. # pylint: disable=line-too-long
+ see: https://learn.microsoft.com/azure/machine-learning/reference-automl-images-hyperparameters#model-agnostic-hyperparameters. # pylint: disable=line-too-long
:type layers_to_freeze: int
:keyword learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:paramtype learning_rate: float
@@ -230,7 +230,7 @@ def set_training_parameters(
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:keyword model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:type model_name: str
:keyword momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_classification_search_space.py b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_classification_search_space.py
index d2796216a168..0691f243294b 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_classification_search_space.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_classification_search_space.py
@@ -52,7 +52,7 @@ class ImageClassificationSearchSpace(RestTranslatableMixin):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/reference-automl-images-hyperparameters#model-agnostic-hyperparameters. # pylint: disable=line-too-long
+ see: https://learn.microsoft.com/azure/machine-learning/reference-automl-images-hyperparameters#model-agnostic-hyperparameters. # pylint: disable=line-too-long
:type layers_to_freeze: int or ~azure.ai.ml.entities._job.sweep.search_space.SweepDistribution
:param learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:type learning_rate: float or ~azure.ai.ml.entities._job.sweep.search_space.SweepDistribution
@@ -61,7 +61,7 @@ class ImageClassificationSearchSpace(RestTranslatableMixin):
:type learning_rate_scheduler: str or ~azure.ai.ml.entities._job.sweep.search_space.SweepDistribution
:param model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:type model_name: str or ~azure.ai.ml.entities._job.sweep.search_space.SweepDistribution
:param momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_model_settings.py b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_model_settings.py
index 1b075c22a792..890f987a67e9 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_model_settings.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_model_settings.py
@@ -67,7 +67,7 @@ class ImageModelDistributionSettings(RestTranslatableMixin):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:type layers_to_freeze: int
:param learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:type learning_rate: float
@@ -77,7 +77,7 @@ class ImageModelDistributionSettings(RestTranslatableMixin):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:param model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:type model_name: str
:param momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:type momentum: float
@@ -259,7 +259,7 @@ class ImageModelSettingsClassification(ImageModelDistributionSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:type layers_to_freeze: int
:param learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:type learning_rate: float
@@ -269,7 +269,7 @@ class ImageModelSettingsClassification(ImageModelDistributionSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:param model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:type model_name: str
:param momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:type momentum: float
@@ -540,7 +540,7 @@ class ImageModelSettingsObjectDetection(ImageModelDistributionSettings):
For instance, passing 2 as value for 'seresnext' means
freezing layer0 and layer1. For a full list of models supported and details on layer freeze,
please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ see: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:type layers_to_freeze: int
:param learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:type learning_rate: float
@@ -550,7 +550,7 @@ class ImageModelSettingsObjectDetection(ImageModelDistributionSettings):
~azure.mgmt.machinelearningservices.models.LearningRateScheduler
:param model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:type model_name: str
:param momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
:type momentum: float
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_object_detection_search_space.py b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_object_detection_search_space.py
index 1a5e4e17f529..a9004d1ed25c 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_object_detection_search_space.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/image/image_object_detection_search_space.py
@@ -58,7 +58,7 @@ class ImageObjectDetectionSearchSpace(RestTranslatableMixin):
:param layers_to_freeze: Number of layers to freeze for the model. Must be a positive
integer. For instance, passing 2 as value for 'seresnext' means freezing layer0 and layer1.
For a full list of models supported and details on layer freeze, please
- see: https://docs.microsoft.com/en-us/azure/machine-learning/reference-automl-images-hyperparameters#model-agnostic-hyperparameters. # pylint: disable=line-too-long
+ see: https://learn.microsoft.com/azure/machine-learning/reference-automl-images-hyperparameters#model-agnostic-hyperparameters. # pylint: disable=line-too-long
:type layers_to_freeze: int or ~azure.ai.ml.entities.SweepDistribution
:param learning_rate: Initial learning rate. Must be a float in the range [0, 1].
:type learning_rate: float or ~azure.ai.ml.entities.SweepDistribution
@@ -67,7 +67,7 @@ class ImageObjectDetectionSearchSpace(RestTranslatableMixin):
:type learning_rate_scheduler: str or ~azure.ai.ml.entities.SweepDistribution
:param model_name: Name of the model to use for training.
For more information on the available models please visit the official documentation:
- https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.
+ https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.
:type model_name: str or ~azure.ai.ml.entities.SweepDistribution
:param momentum: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0,
1].
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/automl_tabular.py b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/automl_tabular.py
index cfa1346b9799..5f4ed22b3249 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/automl_tabular.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/automl_tabular.py
@@ -270,7 +270,7 @@ def set_limits(
:keyword exit_score: Target score for experiment. The experiment terminates after this score is reached.
If not specified (no criteria), the experiment runs until no further progress is made
on the primary metric. For for more information on exit criteria, see this `article
- `_
+ `_
, defaults to None
:paramtype exit_score: typing.Optional[float]
:keyword max_concurrent_trials: This is the maximum number of iterations that would be executed in parallel.
@@ -358,7 +358,7 @@ def set_training(
:keyword enable_onnx_compatible_models: Whether to enable or disable enforcing the ONNX-compatible models.
The default is False. For more information about Open Neural Network Exchange (ONNX) and Azure Machine
- Learning,see this `article `__.
+ Learning,see this `article `__.
:paramtype enable_onnx_compatible_models: typing.Optional[bool]
:keyword enable_dnn_training: Whether to include DNN based models during model selection.
However, the default is True for DNN NLP tasks, and it's False for all other AutoML tasks.
@@ -366,7 +366,7 @@ def set_training(
:keyword enable_model_explainability: Whether to enable explaining the best AutoML model at the end of all
AutoML training iterations. For more information, see
`Interpretability: model explanations in automated machine learning
- `__.
+ `__.
, defaults to None
:paramtype enable_model_explainability: typing.Optional[bool]
:keyword enable_stack_ensemble: Whether to enable/disable StackEnsemble iteration.
@@ -374,12 +374,12 @@ def set_training(
Similarly, for Timeseries tasks, StackEnsemble iteration will be disabled by default, to avoid risks of
overfitting due to small training set used in fitting the meta learner.
For more information about ensembles, see `Ensemble configuration
- `__
+ `__
, defaults to None
:paramtype enable_stack_ensemble: typing.Optional[bool]
:keyword enable_vote_ensemble: Whether to enable/disable VotingEnsemble iteration.
For more information about ensembles, see `Ensemble configuration
- `__
+ `__
, defaults to None
:paramtype enable_vote_ensemble: typing.Optional[bool]
:keyword stack_ensemble_settings: Settings for StackEnsemble iteration, defaults to None
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/forecasting_job.py b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/forecasting_job.py
index 76f0c0b594ff..9bd10b19875d 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/forecasting_job.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/forecasting_job.py
@@ -143,7 +143,7 @@ def set_forecast_settings(
Units are based on the time interval of your training data, e.g., monthly, weekly that the forecaster
should predict out. When task type is forecasting, this parameter is required. For more information on
- setting forecasting parameters, see `Auto-train a time-series forecast model `_.
:type forecast_horizon: Optional[Union[int, str]]
:keyword time_series_id_column_names:
@@ -162,7 +162,7 @@ def set_forecast_settings(
month may depend on the price of specific commodities 3 months prior. In this example, you may want
to lag the target (demand) negatively by 3 months so that the model is training on the correct
relationship. For more information, see `Auto-train a time-series forecast model
- `_.
+ `_.
**Note on auto detection of target lags and rolling window size.
Please see the corresponding comments in the rolling window section.**
@@ -425,7 +425,7 @@ def set_training(
:keyword enable_onnx_compatible_models:
Whether to enable or disable enforcing the ONNX-compatible models.
The default is False. For more information about Open Neural Network Exchange (ONNX) and Azure Machine
- Learning, see this `article `__.
+ Learning, see this `article `__.
:type enable_onnx_compatible: Optional[bool]
:keyword enable_dnn_training:
Whether to include DNN based models during model selection.
@@ -434,7 +434,7 @@ def set_training(
:keyword enable_model_explainability:
Whether to enable explaining the best AutoML model at the end of all AutoML training iterations.
For more information, see `Interpretability: model explanations in automated machine learning
- `__.
+ `__.
, defaults to None
:type enable_model_explainability: Optional[bool]
:keyword enable_stack_ensemble:
@@ -443,13 +443,13 @@ def set_training(
Similarly, for Timeseries tasks, StackEnsemble iteration will be disabled by default, to avoid risks of
overfitting due to small training set used in fitting the meta learner.
For more information about ensembles, see `Ensemble configuration
- `__
+ `__
, defaults to None
:type enable_stack_ensemble: Optional[bool]
:keyword enable_vote_ensemble:
Whether to enable/disable VotingEnsemble iteration.
For more information about ensembles, see `Ensemble configuration
- `__
+ `__
, defaults to None
:type enable_vote_ensemble: Optional[bool]
:keyword stack_ensemble_settings:
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/forecasting_settings.py b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/forecasting_settings.py
index 88a6a0028f64..09439483a8a2 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/forecasting_settings.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_job/automl/tabular/forecasting_settings.py
@@ -44,7 +44,7 @@ class ForecastingSettings(RestTranslatableMixin):
Units are based on the time interval of your training data, e.g., monthly, weekly that the forecaster
should predict out. When task type is forecasting, this parameter is required. For more information on
- setting forecasting parameters, see `Auto-train a time-series forecast model `_.
:type forecast_horizon: Optional[Union[int, str]]
:param target_lags:
@@ -57,7 +57,7 @@ class ForecastingSettings(RestTranslatableMixin):
month may depend on the price of specific commodities 3 months prior. In this example, you may want
to lag the target (demand) negatively by 3 months so that the model is training on the correct
relationship. For more information, see `Auto-train a time-series forecast model
- `_.
+ `_.
**Note on auto detection of target lags and rolling window size.
Please see the corresponding comments in the rolling window section.**
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_util.py b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_util.py
index c85662bd20e5..c487be6edeea 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_util.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_util.py
@@ -213,7 +213,7 @@ def decorate_validation_error(schema: Any, pretty_error: str, additional_message
additional_message += (
"\nThe easiest way to author a specification file is using IntelliSense and auto-completion Azure ML VS "
"code extension provides: https://code.visualstudio.com/docs/datascience/azure-machine-learning. "
- "To set up: https://docs.microsoft.com/azure/machine-learning/how-to-setup-vs-code"
+ "To set up: https://learn.microsoft.com/azure/machine-learning/how-to-setup-vs-code"
)
return f"Validation for {schema.__name__} failed:\n\n {pretty_error} \n\n {additional_message}"
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_workspace/workspace.py b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_workspace/workspace.py
index 9a1eae7fb636..495e00b0fcc0 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_workspace/workspace.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/entities/_workspace/workspace.py
@@ -56,7 +56,7 @@ class Workspace(Resource):
:param hbi_workspace: Whether the customer data is of high business impact (HBI),
containing sensitive business information.
For more information, see
- https://docs.microsoft.com/azure/machine-learning/concept-data-encryption#encryption-at-rest.
+ https://learn.microsoft.com/azure/machine-learning/concept-data-encryption#encryption-at-rest.
:type hbi_workspace: bool
:param storage_account: The resource ID of an existing storage account to use instead of creating a new one.
:type storage_account: str
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/identity/_aio/_credentials/aml_on_behalf_of.py b/sdk/ml/azure-ai-ml/azure/ai/ml/identity/_aio/_credentials/aml_on_behalf_of.py
index f9af37f9d446..386993d67828 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/identity/_aio/_credentials/aml_on_behalf_of.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/identity/_aio/_credentials/aml_on_behalf_of.py
@@ -19,7 +19,7 @@ class AzureMLOnBehalfOfCredential(AsyncContextManager):
"""Authenticates a user via the on-behalf-of flow.
This credential can only be used on `Azure Machine Learning Compute.
- `_ during job execution when user request to
+ `_ during job execution when user request to
run job during its identity.
"""
# pylint: enable=line-too-long
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/identity/_credentials/aml_on_behalf_of.py b/sdk/ml/azure-ai-ml/azure/ai/ml/identity/_credentials/aml_on_behalf_of.py
index 4afed59572c9..ba9385129b43 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/identity/_credentials/aml_on_behalf_of.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/identity/_credentials/aml_on_behalf_of.py
@@ -19,8 +19,8 @@ class AzureMLOnBehalfOfCredential(object):
"""Authenticates a user via the on-behalf-of flow.
This credential can only be used on `Azure Machine Learning Compute
- `_ or `Azure Machine Learning Serverless Spark Compute
- `_
+ `_ or `Azure Machine Learning Serverless Spark Compute
+ `_
during job execution when user request to run job using its identity.
"""
# pylint: enable=line-too-long
diff --git a/sdk/ml/azure-ai-ml/azure/ai/ml/operations/_online_deployment_operations.py b/sdk/ml/azure-ai-ml/azure/ai/ml/operations/_online_deployment_operations.py
index 89c4f980f2f8..13fe2357728e 100644
--- a/sdk/ml/azure-ai-ml/azure/ai/ml/operations/_online_deployment_operations.py
+++ b/sdk/ml/azure-ai-ml/azure/ai/ml/operations/_online_deployment_operations.py
@@ -150,7 +150,7 @@ def begin_create_or_update(
module_logger.warning(
"Instance type %s may be too small for compute resources. "
"Minimum recommended compute SKU is Standard_DS3_v2 for general purpose endpoints. Learn more about SKUs here: " # pylint: disable=line-too-long
- "https://learn.microsoft.com/en-us/azure/machine-learning/referencemanaged-online-endpoints-vm-sku-list",
+ "https://learn.microsoft.com/azure/machine-learning/referencemanaged-online-endpoints-vm-sku-list",
deployment.instance_type,
)
if (
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2020-09-01-dataplanepreview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2020-09-01-dataplanepreview/machineLearningServices.json
index ce408bfa872a..a9ca648a63fd 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2020-09-01-dataplanepreview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2020-09-01-dataplanepreview/machineLearningServices.json
@@ -680,7 +680,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -1615,7 +1615,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning services and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning services and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedServiceList"
}
@@ -1912,7 +1912,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Workspace connections and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Workspace connections and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedWorkspaceConnectionsList"
}
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2021-10-01-dataplanepreview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2021-10-01-dataplanepreview/machineLearningServices.json
index ce408bfa872a..a9ca648a63fd 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2021-10-01-dataplanepreview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2021-10-01-dataplanepreview/machineLearningServices.json
@@ -680,7 +680,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -1615,7 +1615,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning services and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning services and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedServiceList"
}
@@ -1912,7 +1912,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Workspace connections and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Workspace connections and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedWorkspaceConnectionsList"
}
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2021-10-01-dataplanepreview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2021-10-01-dataplanepreview/mfe.json
index 509b76dc853a..8401619b18d4 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2021-10-01-dataplanepreview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2021-10-01-dataplanepreview/mfe.json
@@ -4057,7 +4057,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -4177,7 +4177,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -4730,7 +4730,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -4738,7 +4738,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-01-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-01-01-preview/machineLearningServices.json
index ecfcd6096c8f..026e952d29ec 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-01-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-01-01-preview/machineLearningServices.json
@@ -719,7 +719,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-02-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-02-01-preview/machineLearningServices.json
index d2a90eaf2c30..04c09f98ed2c 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-02-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-02-01-preview/machineLearningServices.json
@@ -719,7 +719,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -4780,11 +4780,11 @@
"properties": {
"objectId": {
"type": "string",
- "description": "User�s AAD Object Id."
+ "description": "User�s AAD Object Id."
},
"tenantId": {
"type": "string",
- "description": "User�s AAD Tenant Id."
+ "description": "User�s AAD Tenant Id."
}
},
"required": [
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-02-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-02-01-preview/mfe.json
index cefa0a4dab1a..32adb3f2efeb 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-02-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-02-01-preview/mfe.json
@@ -6772,7 +6772,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -6830,7 +6830,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -8009,7 +8009,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -8017,7 +8017,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -8714,7 +8714,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -8784,7 +8784,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -8802,7 +8802,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -8895,7 +8895,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -8931,7 +8931,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -9021,7 +9021,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -9115,7 +9115,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -9131,7 +9131,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -9221,7 +9221,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -9257,7 +9257,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-10-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-10-01-preview/machineLearningServices.json
index 86f0afe434f1..fbcd78a7ee7e 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-10-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-10-01-preview/machineLearningServices.json
@@ -736,7 +736,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -5433,7 +5433,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
@@ -5453,7 +5453,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"type": "string",
"default": "UTC"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-10-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-10-01-preview/mfe.json
index e6bd556dfcac..89ea2fb5e56d 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-10-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-10-01-preview/mfe.json
@@ -10295,7 +10295,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -10363,7 +10363,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -11625,7 +11625,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -11633,7 +11633,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -12462,7 +12462,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -12532,7 +12532,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -12550,7 +12550,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -12637,7 +12637,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -12673,7 +12673,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -12763,7 +12763,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -12852,7 +12852,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -12868,7 +12868,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -12952,7 +12952,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -12988,7 +12988,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -18484,7 +18484,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-12-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-12-01-preview/machineLearningServices.json
index 70cba01fd3a4..057dbcad4198 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-12-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-12-01-preview/machineLearningServices.json
@@ -736,7 +736,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-12-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-12-01-preview/mfe.json
index 32ad23635952..fb2ce5912bcb 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-12-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2022-12-01-preview/mfe.json
@@ -10326,7 +10326,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -10394,7 +10394,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -11673,7 +11673,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -11681,7 +11681,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -12510,7 +12510,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -12580,7 +12580,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -12598,7 +12598,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -12685,7 +12685,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -12721,7 +12721,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -12811,7 +12811,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -12900,7 +12900,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -12916,7 +12916,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -13000,7 +13000,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -13036,7 +13036,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -18618,7 +18618,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-02-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-02-01-preview/machineLearningServices.json
index 58bfa1399110..fd632d87a884 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-02-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-02-01-preview/machineLearningServices.json
@@ -736,7 +736,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-02-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-02-01-preview/mfe.json
index bed9e3d885f7..90eb61348487 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-02-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-02-01-preview/mfe.json
@@ -12855,7 +12855,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -12923,7 +12923,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -14245,7 +14245,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -14253,7 +14253,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -15636,7 +15636,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -15706,7 +15706,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -15724,7 +15724,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -15811,7 +15811,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -15847,7 +15847,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -15937,7 +15937,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -16026,7 +16026,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -16042,7 +16042,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -16126,7 +16126,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -16162,7 +16162,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -22393,7 +22393,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/machineLearningServices.json
index 907a5cbb04d9..4b25c622001e 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/machineLearningServices.json
@@ -745,7 +745,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -5825,7 +5825,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
@@ -5845,7 +5845,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"type": "string",
"default": "UTC"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/mfe.json
index f187354b53bc..0e03ac5f511d 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-04-01-preview/mfe.json
@@ -13602,7 +13602,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -13670,7 +13670,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -15473,7 +15473,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -15481,7 +15481,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -17017,7 +17017,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -17087,7 +17087,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -17105,7 +17105,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -17192,7 +17192,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -17228,7 +17228,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -17318,7 +17318,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -17407,7 +17407,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -17423,7 +17423,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -17507,7 +17507,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -17543,7 +17543,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -25214,7 +25214,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-06-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-06-01-preview/machineLearningServices.json
index 359ef637c72f..ac1f3aa19ebc 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-06-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-06-01-preview/machineLearningServices.json
@@ -260,7 +260,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -3331,7 +3331,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
@@ -3351,7 +3351,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"type": "string",
"default": "UTC"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-06-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-06-01-preview/mfe.json
index 1b34f5856dea..b61072349b12 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-06-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-06-01-preview/mfe.json
@@ -13714,7 +13714,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -13782,7 +13782,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -15633,7 +15633,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -15641,7 +15641,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -17420,7 +17420,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -17490,7 +17490,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -17508,7 +17508,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -17595,7 +17595,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -17631,7 +17631,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -17721,7 +17721,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -17810,7 +17810,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -17826,7 +17826,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -17910,7 +17910,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -17946,7 +17946,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -25934,7 +25934,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-08-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-08-01-preview/machineLearningServices.json
index 3d216a8476cb..b145130b96e4 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-08-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-08-01-preview/machineLearningServices.json
@@ -260,7 +260,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -3555,7 +3555,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
@@ -3704,7 +3704,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"type": "string",
"default": "UTC"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-08-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-08-01-preview/mfe.json
index 55740e8b1570..a43d2248423b 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-08-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2023-08-01-preview/mfe.json
@@ -16102,7 +16102,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -16170,7 +16170,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -18046,7 +18046,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -18054,7 +18054,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -19864,7 +19864,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -19934,7 +19934,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -19952,7 +19952,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -20039,7 +20039,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -20075,7 +20075,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -20165,7 +20165,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -20254,7 +20254,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -20270,7 +20270,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -20354,7 +20354,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -20390,7 +20390,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -29097,7 +29097,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-01-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-01-01-preview/machineLearningServices.json
index afa3853f7f6c..5398f66623fa 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-01-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-01-01-preview/machineLearningServices.json
@@ -260,7 +260,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -3608,7 +3608,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
@@ -3757,7 +3757,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"type": "string",
"default": "UTC"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-01-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-01-01-preview/mfe.json
index 237468057e3d..baad35390f2e 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-01-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-01-01-preview/mfe.json
@@ -17010,7 +17010,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -17078,7 +17078,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -19066,7 +19066,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -19074,7 +19074,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -21068,7 +21068,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -21138,7 +21138,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -21156,7 +21156,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -21243,7 +21243,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -21279,7 +21279,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -21369,7 +21369,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -21458,7 +21458,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -21474,7 +21474,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -21558,7 +21558,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -21594,7 +21594,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -30691,7 +30691,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-04-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-04-01-preview/machineLearningServices.json
index 456323283df3..cc002c8b0fe9 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-04-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-04-01-preview/machineLearningServices.json
@@ -260,7 +260,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -3619,7 +3619,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
@@ -3768,7 +3768,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"type": "string",
"default": "UTC"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-04-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-04-01-preview/mfe.json
index 73584342ffb6..efb888111741 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-04-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-04-01-preview/mfe.json
@@ -17010,7 +17010,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -17078,7 +17078,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -19066,7 +19066,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -19074,7 +19074,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -21068,7 +21068,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -21138,7 +21138,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -21156,7 +21156,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -21243,7 +21243,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -21279,7 +21279,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -21369,7 +21369,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -21458,7 +21458,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -21474,7 +21474,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -21558,7 +21558,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -21594,7 +21594,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -30691,7 +30691,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-07-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-07-01-preview/machineLearningServices.json
index f7bfe4541028..df6780e17a97 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-07-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-07-01-preview/machineLearningServices.json
@@ -260,7 +260,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -3619,7 +3619,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
@@ -3768,7 +3768,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"type": "string",
"default": "UTC"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-07-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-07-01-preview/mfe.json
index 2ddf62964ce8..f563b40b753c 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-07-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-07-01-preview/mfe.json
@@ -13905,7 +13905,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -13973,7 +13973,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -15728,7 +15728,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -15736,7 +15736,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -17144,7 +17144,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -17214,7 +17214,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -17232,7 +17232,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -17319,7 +17319,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -17355,7 +17355,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -17445,7 +17445,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -17534,7 +17534,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -17550,7 +17550,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -17634,7 +17634,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -17670,7 +17670,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -23807,7 +23807,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-10-01-preview/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-10-01-preview/machineLearningServices.json
index c19ee4515256..19f84adc2dcc 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-10-01-preview/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-10-01-preview/machineLearningServices.json
@@ -260,7 +260,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -3619,7 +3619,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
@@ -3768,7 +3768,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"type": "string",
"default": "UTC"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-10-01-preview/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-10-01-preview/mfe.json
index d8906051a3b7..a7d93889a98b 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-10-01-preview/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/2024-10-01-preview/mfe.json
@@ -15918,7 +15918,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -15986,7 +15986,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -17900,7 +17900,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -17908,7 +17908,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -19536,7 +19536,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -19606,7 +19606,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -19624,7 +19624,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -19711,7 +19711,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -19747,7 +19747,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -19837,7 +19837,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -19926,7 +19926,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -19942,7 +19942,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -20026,7 +20026,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -20062,7 +20062,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -26636,7 +26636,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/runhistory/run-history.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/runhistory/run-history.json
index cd27d542a0a9..d88b532c41e7 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/runhistory/run-history.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/preview/runhistory/run-history.json
@@ -5796,7 +5796,7 @@
},
"filter": {
"type": "string",
- "description": "Allows for filtering the collection of resources.\r\nThe expression specified is evaluated for each resource in the collection, and only items where the expression evaluates to true are included in the response.\r\nSee https://docs.microsoft.com/en-us/azure/search/query-odata-filter-orderby-syntax for details on the expression syntax.",
+ "description": "Allows for filtering the collection of resources.\r\nThe expression specified is evaluated for each resource in the collection, and only items where the expression evaluates to true are included in the response.\r\nSee https://learn.microsoft.com/azure/search/query-odata-filter-orderby-syntax for details on the expression syntax.",
"nullable": true
},
"continuationToken": {
@@ -6563,7 +6563,7 @@
"properties": {
"filter": {
"type": "string",
- "description": "Allows for filtering the collection of resources.\r\nThe expression specified is evaluated for each resource in the collection, and only items where the expression evaluates to true are included in the response.\r\nSee https://docs.microsoft.com/en-us/azure/search/query-odata-filter-orderby-syntax for details on the expression syntax.",
+ "description": "Allows for filtering the collection of resources.\r\nThe expression specified is evaluated for each resource in the collection, and only items where the expression evaluates to true are included in the response.\r\nSee https://learn.microsoft.com/azure/search/query-odata-filter-orderby-syntax for details on the expression syntax.",
"nullable": true
},
"continuationToken": {
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-05-01/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-05-01/machineLearningServices.json
index f5ae53d16418..29691978b5ba 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-05-01/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-05-01/machineLearningServices.json
@@ -736,7 +736,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -5337,11 +5337,11 @@
"properties": {
"objectId": {
"type": "string",
- "description": "User�s AAD Object Id."
+ "description": "User�s AAD Object Id."
},
"tenantId": {
"type": "string",
- "description": "User�s AAD Tenant Id."
+ "description": "User�s AAD Tenant Id."
}
},
"required": [
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-05-01/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-05-01/mfe.json
index 14d9eaeeb21a..9611e76c1052 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-05-01/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2022-05-01/mfe.json
@@ -6413,7 +6413,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -6471,7 +6471,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -7466,7 +7466,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -7474,7 +7474,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/machineLearningServices.json
index 41f26c87e1c4..cae976f254b0 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/machineLearningServices.json
@@ -736,7 +736,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -5275,7 +5275,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
@@ -5295,7 +5295,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"type": "string",
"default": "UTC"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/mfe.json
index 32a6800b9e5d..2374c317c6d2 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-04-01/mfe.json
@@ -10640,7 +10640,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -10708,7 +10708,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -11918,7 +11918,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -11926,7 +11926,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -12612,7 +12612,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -12682,7 +12682,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -12700,7 +12700,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -12787,7 +12787,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -12823,7 +12823,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -12913,7 +12913,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -13002,7 +13002,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -13018,7 +13018,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -13102,7 +13102,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -13138,7 +13138,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -17221,7 +17221,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-10-01/machineLearningServices.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-10-01/machineLearningServices.json
index 46c379531f63..8f1a35767f1e 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-10-01/machineLearningServices.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-10-01/machineLearningServices.json
@@ -778,7 +778,7 @@
],
"responses": {
"200": {
- "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits/.",
+ "description": "The response includes a paginated array of Machine Learning computes and a URI to the next set of results, if any. For the more information the limits of the number of items in a resource group, see https://azure.microsoft.com/documentation/articles/azure-subscription-service-limits/.",
"schema": {
"$ref": "#/definitions/PaginatedComputeResourcesList"
}
@@ -5637,7 +5637,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
@@ -5786,7 +5786,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"type": "string",
"default": "UTC"
},
diff --git a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-10-01/mfe.json b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-10-01/mfe.json
index 618d167b57b0..4eacc012d563 100644
--- a/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-10-01/mfe.json
+++ b/sdk/ml/azure-ai-ml/swagger/machinelearningservices/resource-manager/Microsoft.MachineLearningServices/stable/2023-10-01/mfe.json
@@ -13043,7 +13043,7 @@
"additionalProperties": false
},
"ComponentContainer": {
- "description": "Component container definition.\r\n",
+ "description": "Component container definition.\r\n",
"type": "object",
"allOf": [
{
@@ -13111,7 +13111,7 @@
],
"properties": {
"componentSpec": {
- "description": "Defines Component definition details.\r\n",
+ "description": "Defines Component definition details.\r\n",
"type": "object",
"example": {
"name": "Hello_Python_World",
@@ -14781,7 +14781,7 @@
]
},
"environmentType": {
- "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
+ "description": "Environment type is either user managed or curated by the Azure ML service\r\n",
"$ref": "#/definitions/EnvironmentType",
"readOnly": true,
"x-ms-mutability": [
@@ -14789,7 +14789,7 @@
]
},
"image": {
- "description": "Name of the image that will be used for the environment.\r\n",
+ "description": "Name of the image that will be used for the environment.\r\n",
"type": "string",
"example": "docker.io/tensorflow/serving:latest",
"x-ms-mutability": [
@@ -16197,7 +16197,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettings": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nAll distributions can be specified as distribution_name(min, max) or choice(val1, val2, ..., valn)\r\nwhere distribution name can be: uniform, quniform, loguniform, etc\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"amsGradient": {
@@ -16267,7 +16267,7 @@
"x-nullable": true
},
"layersToFreeze": {
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice(1, 2)",
"x-nullable": true
@@ -16285,7 +16285,7 @@
"x-nullable": true
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"example": "choice('seresnext', 'resnest50')",
"x-nullable": true
@@ -16372,7 +16372,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsClassification": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -16408,7 +16408,7 @@
"additionalProperties": false
},
"ImageModelDistributionSettingsObjectDetection": {
- "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Distribution expressions to sweep over values of model settings.\r\n\r\nSome examples are:\r\n```\r\nModelName = \"choice('seresnext', 'resnest50')\";\r\nLearningRate = \"uniform(0.001, 0.01)\";\r\nLayersToFreeze = \"choice(0, 2)\";\r\n```\r\nFor more details on how to compose distribution expressions please check the documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-tune-hyperparameters\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -16498,7 +16498,7 @@
"additionalProperties": false
},
"ImageModelSettings": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"properties": {
"advancedSettings": {
@@ -16587,7 +16587,7 @@
},
"layersToFreeze": {
"format": "int32",
- "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Number of layers to freeze for the model. Must be a positive integer.\r\nFor instance, passing 2 as value for 'seresnext' means\r\nfreezing layer0 and layer1. For a full list of models supported and details on layer freeze, please\r\nsee: https://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "integer",
"x-nullable": true
},
@@ -16603,7 +16603,7 @@
"$ref": "#/definitions/LearningRateScheduler"
},
"modelName": {
- "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Name of the model to use for training.\r\nFor more information on the available models please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "string",
"x-nullable": true
},
@@ -16687,7 +16687,7 @@
"additionalProperties": false
},
"ImageModelSettingsClassification": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -16723,7 +16723,7 @@
"additionalProperties": false
},
"ImageModelSettingsObjectDetection": {
- "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.",
+ "description": "Settings used for training the model.\r\nFor more information on the available settings please visit the official documentation:\r\nhttps://learn.microsoft.com/azure/machine-learning/how-to-auto-train-image-models.",
"type": "object",
"allOf": [
{
@@ -21957,7 +21957,7 @@
"x-nullable": true
},
"timeZone": {
- "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://docs.microsoft.com/en-us/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
+ "description": "Specifies time zone in which the schedule runs.\r\nTimeZone should follow Windows time zone format. Refer: https://learn.microsoft.com/windows-hardware/manufacture/desktop/default-time-zones?view=windows-11",
"default": "UTC",
"type": "string"
},
diff --git a/sdk/ml/azure-ai-ml/tests/test_configs/flows/web_classification_with_additional_includes/flow.dag.yaml b/sdk/ml/azure-ai-ml/tests/test_configs/flows/web_classification_with_additional_includes/flow.dag.yaml
index b61c122c5457..7863bb452226 100644
--- a/sdk/ml/azure-ai-ml/tests/test_configs/flows/web_classification_with_additional_includes/flow.dag.yaml
+++ b/sdk/ml/azure-ai-ml/tests/test_configs/flows/web_classification_with_additional_includes/flow.dag.yaml
@@ -2,7 +2,7 @@ $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
inputs:
url:
type: string
- default: https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h
+ default: https://www.microsoft.com/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h
outputs:
category:
type: string
diff --git a/sdk/ml/azure-ai-ml/tests/test_configs/pipeline_jobs/serverless_compute/all_types/automl/components/src/register.py b/sdk/ml/azure-ai-ml/tests/test_configs/pipeline_jobs/serverless_compute/all_types/automl/components/src/register.py
index ea46ddacd2fa..ce1a68c65905 100644
--- a/sdk/ml/azure-ai-ml/tests/test_configs/pipeline_jobs/serverless_compute/all_types/automl/components/src/register.py
+++ b/sdk/ml/azure-ai-ml/tests/test_configs/pipeline_jobs/serverless_compute/all_types/automl/components/src/register.py
@@ -14,7 +14,7 @@
import mlflow.sklearn
# Based on example:
-# https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-cli
+# https://learn.microsoft.com/azure/machine-learning/how-to-train-cli
# which references
# https://github.com/Azure/azureml-examples/tree/main/cli/jobs/train/lightgbm/iris
diff --git a/sdk/ml/azure-ai-ml/tests/test_configs/pipeline_jobs/serverless_compute/job_tier/automl_in_pipeline/components/src/register.py b/sdk/ml/azure-ai-ml/tests/test_configs/pipeline_jobs/serverless_compute/job_tier/automl_in_pipeline/components/src/register.py
index ea46ddacd2fa..ce1a68c65905 100644
--- a/sdk/ml/azure-ai-ml/tests/test_configs/pipeline_jobs/serverless_compute/job_tier/automl_in_pipeline/components/src/register.py
+++ b/sdk/ml/azure-ai-ml/tests/test_configs/pipeline_jobs/serverless_compute/job_tier/automl_in_pipeline/components/src/register.py
@@ -14,7 +14,7 @@
import mlflow.sklearn
# Based on example:
-# https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-cli
+# https://learn.microsoft.com/azure/machine-learning/how-to-train-cli
# which references
# https://github.com/Azure/azureml-examples/tree/main/cli/jobs/train/lightgbm/iris