Generated from 5271be59e1385aa17e3cc8b4e0ee8e1a1c9d7415

update examples

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/__init__.py

@@ -34,6 +34,8 @@
     from .virtual_machine_ssh_credentials_py3 import VirtualMachineSshCredentials
     from .virtual_machine_properties_py3 import VirtualMachineProperties
     from .virtual_machine_py3 import VirtualMachine
+    from .hd_insight_properties_py3 import HDInsightProperties
+    from .hd_insight_py3 import HDInsight
     from .data_factory_py3 import DataFactory
     from .service_principal_credentials_py3 import ServicePrincipalCredentials
     from .compute_secrets_py3 import ComputeSecrets
@@ -64,6 +66,8 @@
     from .virtual_machine_ssh_credentials import VirtualMachineSshCredentials
     from .virtual_machine_properties import VirtualMachineProperties
     from .virtual_machine import VirtualMachine
+    from .hd_insight_properties import HDInsightProperties
+    from .hd_insight import HDInsight
     from .data_factory import DataFactory
     from .service_principal_credentials import ServicePrincipalCredentials
     from .compute_secrets import ComputeSecrets
@@ -103,6 +107,8 @@
     'VirtualMachineSshCredentials',
     'VirtualMachineProperties',
     'VirtualMachine',
+    'HDInsightProperties',
+    'HDInsight',
     'DataFactory',
     'ServicePrincipalCredentials',
     'ComputeSecrets',

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/aks.py

@@ -20,6 +20,8 @@ class AKS(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -52,6 +54,7 @@ class AKS(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/aks_py3.py

@@ -20,6 +20,8 @@ class AKS(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -52,6 +54,7 @@ class AKS(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
@@ -62,7 +65,7 @@ class AKS(Compute):
         'properties': {'key': 'properties', 'type': 'AKSProperties'},
     }
 
-    def __init__(self, *, description: str=None, resource_id: str=None, properties=None, **kwargs) -> None:
-        super(AKS, self).__init__(description=description, resource_id=resource_id, **kwargs)
+    def __init__(self, *, compute_location: str=None, description: str=None, resource_id: str=None, properties=None, **kwargs) -> None:
+        super(AKS, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs)
         self.properties = properties
         self.compute_type = 'AKS'

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/azure_machine_learning_workspaces_enums.py

@@ -34,3 +34,4 @@ class ComputeType(str, Enum):
     batch_ai = "BatchAI"
     data_factory = "DataFactory"
     virtual_machine = "VirtualMachine"
+    hd_insight = "HDInsight"

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/batch_ai.py

@@ -20,6 +20,8 @@ class BatchAI(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -53,6 +55,7 @@ class BatchAI(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/batch_ai_py3.py

@@ -20,6 +20,8 @@ class BatchAI(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -53,6 +55,7 @@ class BatchAI(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
@@ -63,7 +66,7 @@ class BatchAI(Compute):
         'properties': {'key': 'properties', 'type': 'BatchAIProperties'},
     }
 
-    def __init__(self, *, description: str=None, resource_id: str=None, properties=None, **kwargs) -> None:
-        super(BatchAI, self).__init__(description=description, resource_id=resource_id, **kwargs)
+    def __init__(self, *, compute_location: str=None, description: str=None, resource_id: str=None, properties=None, **kwargs) -> None:
+        super(BatchAI, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs)
         self.properties = properties
         self.compute_type = 'BatchAI'

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/compute.py

@@ -16,13 +16,15 @@ class Compute(Model):
     """Machine Learning compute object.
 
     You probably want to use the sub-classes and not this class directly. Known
-    sub-classes are: AKS, BatchAI, VirtualMachine, DataFactory
+    sub-classes are: AKS, BatchAI, VirtualMachine, HDInsight, DataFactory
 
     Variables are only populated by the server, and will be ignored when
     sending a request.
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -53,6 +55,7 @@ class Compute(Model):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
@@ -63,11 +66,12 @@ class Compute(Model):
     }
 
     _subtype_map = {
-        'compute_type': {'AKS': 'AKS', 'BatchAI': 'BatchAI', 'VirtualMachine': 'VirtualMachine', 'DataFactory': 'DataFactory'}
+        'compute_type': {'AKS': 'AKS', 'BatchAI': 'BatchAI', 'VirtualMachine': 'VirtualMachine', 'HDInsight': 'HDInsight', 'DataFactory': 'DataFactory'}
     }
 
     def __init__(self, **kwargs):
         super(Compute, self).__init__(**kwargs)
+        self.compute_location = kwargs.get('compute_location', None)
         self.provisioning_state = None
         self.description = kwargs.get('description', None)
         self.created_on = None

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/compute_py3.py

@@ -16,13 +16,15 @@ class Compute(Model):
     """Machine Learning compute object.
 
     You probably want to use the sub-classes and not this class directly. Known
-    sub-classes are: AKS, BatchAI, VirtualMachine, DataFactory
+    sub-classes are: AKS, BatchAI, VirtualMachine, HDInsight, DataFactory
 
     Variables are only populated by the server, and will be ignored when
     sending a request.
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -53,6 +55,7 @@ class Compute(Model):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
@@ -63,11 +66,12 @@ class Compute(Model):
     }
 
     _subtype_map = {
-        'compute_type': {'AKS': 'AKS', 'BatchAI': 'BatchAI', 'VirtualMachine': 'VirtualMachine', 'DataFactory': 'DataFactory'}
+        'compute_type': {'AKS': 'AKS', 'BatchAI': 'BatchAI', 'VirtualMachine': 'VirtualMachine', 'HDInsight': 'HDInsight', 'DataFactory': 'DataFactory'}
     }
 
-    def __init__(self, *, description: str=None, resource_id: str=None, **kwargs) -> None:
+    def __init__(self, *, compute_location: str=None, description: str=None, resource_id: str=None, **kwargs) -> None:
         super(Compute, self).__init__(**kwargs)
+        self.compute_location = compute_location
         self.provisioning_state = None
         self.description = description
         self.created_on = None

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/data_factory.py

@@ -20,6 +20,8 @@ class DataFactory(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -50,6 +52,7 @@ class DataFactory(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/data_factory_py3.py

@@ -20,6 +20,8 @@ class DataFactory(Compute):
 
     All required parameters must be populated in order to send to Azure.
 
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
     :ivar provisioning_state: The provision state of the cluster. Valid values
      are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
      values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
@@ -50,6 +52,7 @@ class DataFactory(Compute):
     }
 
     _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
         'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
         'description': {'key': 'description', 'type': 'str'},
         'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
@@ -59,6 +62,6 @@ class DataFactory(Compute):
         'compute_type': {'key': 'computeType', 'type': 'str'},
     }
 
-    def __init__(self, *, description: str=None, resource_id: str=None, **kwargs) -> None:
-        super(DataFactory, self).__init__(description=description, resource_id=resource_id, **kwargs)
+    def __init__(self, *, compute_location: str=None, description: str=None, resource_id: str=None, **kwargs) -> None:
+        super(DataFactory, self).__init__(compute_location=compute_location, description=description, resource_id=resource_id, **kwargs)
         self.compute_type = 'DataFactory'

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/hd_insight.py

@@ -0,0 +1,72 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+#
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is
+# regenerated.
+# --------------------------------------------------------------------------
+
+from .compute import Compute
+
+
+class HDInsight(Compute):
+    """A HDInsight compute.
+
+    Variables are only populated by the server, and will be ignored when
+    sending a request.
+
+    All required parameters must be populated in order to send to Azure.
+
+    :param compute_location: Location for the underlying compute
+    :type compute_location: str
+    :ivar provisioning_state: The provision state of the cluster. Valid values
+     are Unknown, Updating, Provisioning, Succeeded, and Failed. Possible
+     values include: 'Unknown', 'Updating', 'Creating', 'Deleting',
+     'Succeeded', 'Failed', 'Canceled'
+    :vartype provisioning_state: str or
+     ~azure.mgmt.machinelearningservices.models.ProvisioningState
+    :param description: The description of the Machine Learning compute.
+    :type description: str
+    :ivar created_on: The date and time when the compute was created.
+    :vartype created_on: datetime
+    :ivar modified_on: The date and time when the compute was last modified.
+    :vartype modified_on: datetime
+    :param resource_id: ARM resource id of the compute
+    :type resource_id: str
+    :ivar provisioning_errors: Errors during provisioning
+    :vartype provisioning_errors:
+     list[~azure.mgmt.machinelearningservices.models.MachineLearningServiceError]
+    :param compute_type: Required. Constant filled by server.
+    :type compute_type: str
+    :param properties:
+    :type properties:
+     ~azure.mgmt.machinelearningservices.models.HDInsightProperties
+    """
+
+    _validation = {
+        'provisioning_state': {'readonly': True},
+        'created_on': {'readonly': True},
+        'modified_on': {'readonly': True},
+        'provisioning_errors': {'readonly': True},
+        'compute_type': {'required': True},
+    }
+
+    _attribute_map = {
+        'compute_location': {'key': 'computeLocation', 'type': 'str'},
+        'provisioning_state': {'key': 'provisioningState', 'type': 'str'},
+        'description': {'key': 'description', 'type': 'str'},
+        'created_on': {'key': 'createdOn', 'type': 'iso-8601'},
+        'modified_on': {'key': 'modifiedOn', 'type': 'iso-8601'},
+        'resource_id': {'key': 'resourceId', 'type': 'str'},
+        'provisioning_errors': {'key': 'provisioningErrors', 'type': '[MachineLearningServiceError]'},
+        'compute_type': {'key': 'computeType', 'type': 'str'},
+        'properties': {'key': 'properties', 'type': 'HDInsightProperties'},
+    }
+
+    def __init__(self, **kwargs):
+        super(HDInsight, self).__init__(**kwargs)
+        self.properties = kwargs.get('properties', None)
+        self.compute_type = 'HDInsight'

azure-mgmt-machinelearningservices/azure/mgmt/machinelearningservices/models/hd_insight_properties.py

@@ -0,0 +1,46 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+#
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is
+# regenerated.
+# --------------------------------------------------------------------------
+
+from msrest.serialization import Model
+
+
+class HDInsightProperties(Model):
+    """HDInsightProperties.
+
+    Variables are only populated by the server, and will be ignored when
+    sending a request.
+
+    :param ssh_port: Port open for ssh connections on the master node of the
+     cluster.
+    :type ssh_port: int
+    :ivar address: Public IP address of the master node of the cluster.
+    :vartype address: str
+    :param administrator_account: Admin credentials for master node of the
+     cluster
+    :type administrator_account:
+     ~azure.mgmt.machinelearningservices.models.VirtualMachineSshCredentials
+    """
+
+    _validation = {
+        'address': {'readonly': True},
+    }
+
+    _attribute_map = {
+        'ssh_port': {'key': 'sshPort', 'type': 'int'},
+        'address': {'key': 'address', 'type': 'str'},
+        'administrator_account': {'key': 'administratorAccount', 'type': 'VirtualMachineSshCredentials'},
+    }
+
+    def __init__(self, **kwargs):
+        super(HDInsightProperties, self).__init__(**kwargs)
+        self.ssh_port = kwargs.get('ssh_port', None)
+        self.address = None
+        self.administrator_account = kwargs.get('administrator_account', None)