update samples from Release-243 as a part of 1.58.0 SDK stable release

Author: amlrelsa-ms

configuration.ipynb

@@ -103,7 +103,7 @@
       "source": [
         "import azureml.core\n",
         "\n",
-        "print(\"This notebook was created using version 1.57.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.58.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },

how-to-use-azureml/automated-machine-learning/automl_env.yml

@@ -14,14 +14,13 @@ dependencies:
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.57.0
-  - azureml-defaults~=1.57.0
-  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.57.0/validated_win32_requirements.txt [--no-deps]
+  - azureml-widgets~=1.58.0
+  - azureml-defaults~=1.58.0
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.58.0/validated_win32_requirements.txt [--no-deps]
   - matplotlib==3.7.1
   - xgboost==1.5.2
   - prophet==1.1.4
   - pandas==1.3.5
-  - cmdstanpy==1.1.0
   - setuptools-git==1.2
   - spacy==3.7.4
   - https://aka.ms/automl-resources/packages/en_core_web_sm-3.7.1.tar.gz

how-to-use-azureml/automated-machine-learning/automl_env_linux.yml

@@ -20,11 +20,11 @@ dependencies:
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.57.0
-  - azureml-defaults~=1.57.0
+  - azureml-widgets~=1.58.0
+  - azureml-defaults~=1.58.0
   - pytorch-transformers==1.0.0
   - spacy==3.7.4
   - xgboost==1.5.2
   - prophet==1.1.4
   - https://aka.ms/automl-resources/packages/en_core_web_sm-3.7.1.tar.gz
-  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.57.0/validated_linux_requirements.txt [--no-deps]
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.58.0/validated_linux_requirements.txt [--no-deps]

how-to-use-azureml/automated-machine-learning/automl_env_mac.yml

@@ -15,12 +15,12 @@ dependencies:
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.57.0
-  - azureml-defaults~=1.57.0
+  - azureml-widgets~=1.58.0
+  - azureml-defaults~=1.58.0
   - pytorch-transformers==1.0.0
   - prophet==1.1.4
   - xgboost==1.5.2
   - spacy==3.7.4
   - matplotlib==3.7.1
   - https://aka.ms/automl-resources/packages/en_core_web_sm-3.7.1.tar.gz
-  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.57.0/validated_darwin_requirements.txt [--no-deps]
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.58.0/validated_darwin_requirements.txt [--no-deps]

how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb

@@ -93,7 +93,8 @@
         "from azureml.core.workspace import Workspace\n",
         "from azureml.core.dataset import Dataset\n",
         "from azureml.train.automl import AutoMLConfig\n",
-        "from azureml.interpret import ExplanationClient"
+        "from azureml.interpret import ExplanationClient\n",
+        "from azureml.data.datapath import DataPath"
       ]
     },
     {
@@ -266,10 +267,12 @@
         "pd.DataFrame(data).to_csv(\"data/train_data.csv\", index=False)\n",
         "\n",
         "ds = ws.get_default_datastore()\n",
-        "ds.upload(\n",
-        "    src_dir=\"./data\", target_path=\"bankmarketing\", overwrite=True, show_progress=True\n",
+        "target = DataPath(\n",
+        "    datastore=ds, path_on_datastore=\"bankmarketing/train_data.csv\", name=\"bankmarketing\"\n",
+        ")\n",
+        "Dataset.File.upload_directory(\n",
+        "    src_dir=\"./data\", target=target, overwrite=True, show_progress=True\n",
         ")\n",
-        "\n",
         "\n",
         "# Upload the training data as a tabular dataset for access during training on remote compute\n",
         "train_data = Dataset.Tabular.from_delimited_files(\n",
@@ -1090,7 +1093,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.8.12"
+      "version": "3.10.14"
     },
     "nteract": {
       "version": "[email protected]"
@@ -1104,5 +1107,5 @@
     "task": "Classification"
   },
   "nbformat": 4,
-  "nbformat_minor": 1
+  "nbformat_minor": 4
 }

how-to-use-azureml/automated-machine-learning/experimental/autofeaturization-codegen/codegen-for-autofeaturization.ipynb

@@ -97,7 +97,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.57.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.58.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },

how-to-use-azureml/automated-machine-learning/experimental/autofeaturization-custom-model-training/custom-model-training-from-autofeaturization-run.ipynb

@@ -97,7 +97,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.57.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.58.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },

how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb

@@ -91,7 +91,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.57.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.58.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },

how-to-use-azureml/ml-frameworks/pytorch/distributed-pytorch-with-distributeddataparallel/distributed-pytorch-with-distributeddataparallel.ipynb

@@ -293,7 +293,7 @@
       "source": [
         "from azureml.core import Environment\n",
         "\n",
-        "pytorch_env = Environment.get(ws, name='azureml-acpt-pytorch-1.13-cuda11.7')"
+        "pytorch_env = Environment.get(ws, name='azureml-acpt-pytorch-2.2-cuda12.1')"
       ]
     },
     {