update samples from Release-166 as a part of SDK release

update samples from Release-156 as a part of 1.47.0 SDK stable release

configuration.ipynb

@@ -103,7 +103,7 @@
       "source": [
         "import azureml.core\n",
         "\n",
-        "print(\"This notebook was created using version 1.46.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.47.0 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

@@ -10,12 +10,11 @@ dependencies:
 - python>=3.6,<3.9
 - matplotlib==3.2.1
 - py-xgboost==1.3.3
-- pytorch::pytorch=1.4.0
+- pytorch::pytorch=1.11.0
 - conda-forge::fbprophet==0.7.1
 - cudatoolkit=10.1.243
 - scipy==1.5.3
 - notebook
-- pywin32==227
 - PySocks==1.7.1
 - conda-forge::pyqt==5.12.3
 - jinja2<=2.11.2
@@ -25,12 +24,12 @@ dependencies:
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.46.0
+  - azureml-widgets~=1.47.0
-  - azureml-defaults~=1.46.0
+  - azureml-defaults~=1.47.0
   - pytorch-transformers==1.0.0
   - spacy==2.2.4
   - pystan==2.19.1.1
   - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz
-  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.46.0/validated_win32_requirements.txt [--no-deps]
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.47.0/validated_win32_requirements.txt [--no-deps]
   - arch==4.14
   - wasabi==0.9.1

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

@@ -6,10 +6,8 @@ channels:
 dependencies:
   # The python interpreter version.
   # Currently Azure ML only supports 3.6.0 and later.
-- pip==20.2.4
+- pip==20.1.1
 - python>=3.6,<3.9
-- boto3==1.20.19
-- botocore<=1.23.19
 - matplotlib==3.2.1
 - numpy>=1.21.6,<=1.22.3
 - cython==0.29.14
@@ -19,19 +17,19 @@ dependencies:
 - py-xgboost<=1.3.3
 - holidays==0.10.3
 - conda-forge::fbprophet==0.7.1
-- pytorch::pytorch=1.4.0
+- pytorch::pytorch=1.11.0
 - cudatoolkit=10.1.243
+- notebook
 - jinja2<=2.11.2
 - markupsafe<2.1.0
-- jsonschema==4.15.0
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.46.0
+  - azureml-widgets~=1.47.0
-  - azureml-defaults~=1.46.0
+  - azureml-defaults~=1.47.0
   - pytorch-transformers==1.0.0
   - spacy==2.2.4
   - pystan==2.19.1.1
   - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz
-  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.46.0/validated_linux_requirements.txt [--no-deps]
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.47.0/validated_linux_requirements.txt [--no-deps]
   - arch==4.14

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

@@ -6,11 +6,8 @@ channels:
 dependencies:
   # The python interpreter version.
   # Currently Azure ML only supports 3.6.0 and later.
-- pip==20.2.4
+- pip==20.1.1
-- nomkl
 - python>=3.6,<3.9
-- boto3==1.20.19
-- botocore<=1.23.19
 - matplotlib==3.2.1
 - numpy>=1.21.6,<=1.22.3
 - cython==0.29.14
@@ -20,19 +17,19 @@ dependencies:
 - py-xgboost<=1.3.3
 - holidays==0.10.3
 - conda-forge::fbprophet==0.7.1
-- pytorch::pytorch=1.4.0
+- pytorch::pytorch=1.11.0
 - cudatoolkit=9.0
+- notebook
 - jinja2<=2.11.2
 - markupsafe<2.1.0
-- jsonschema==4.15.0
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.46.0
+  - azureml-widgets~=1.47.0
-  - azureml-defaults~=1.46.0
+  - azureml-defaults~=1.47.0
   - pytorch-transformers==1.0.0
   - spacy==2.2.4
   - pystan==2.19.1.1
   - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz
-  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.46.0/validated_darwin_requirements.txt [--no-deps]
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.47.0/validated_darwin_requirements.txt [--no-deps]
   - arch==4.14

how-to-use-azureml/automated-machine-learning/automl_setup.cmd

@@ -33,6 +33,8 @@ if not errorlevel 1 (
   call conda env create -f %automl_env_file% -n %conda_env_name%
 )
 
+python "%conda_prefix%\scripts\pywin32_postinstall.py" -install
+
 call conda activate %conda_env_name% 2>nul:
 if errorlevel 1 goto ErrorExit
 

how-to-use-azureml/automated-machine-learning/check_conda_version.py

@@ -1,4 +1,4 @@
-from distutils.version import LooseVersion
+from setuptools._vendor.packaging import version
 import platform
 
 try:
@@ -17,7 +17,7 @@ if architecture != "64bit":
 
 minimumVersion = "4.7.8"
 
-versionInvalid = (LooseVersion(conda.__version__) < LooseVersion(minimumVersion))
+versionInvalid = (version.parse(conda.__version__) < version.parse(minimumVersion))
 
 if versionInvalid:
     print('Setup requires conda version ' + minimumVersion + ' or higher.')

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 1.46.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.47.0 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 1.46.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.47.0 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/automl_thin_client_env.yml

@@ -9,7 +9,6 @@ dependencies:
 - PyJWT < 2.0.0
 - numpy==1.22.3
 - pywin32==227
-- cryptography<37.0.0
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.

how-to-use-azureml/automated-machine-learning/experimental/automl_thin_client_env_mac.yml

@@ -11,7 +11,6 @@ dependencies:
 - urllib3==1.26.7
 - PyJWT < 2.0.0
 - numpy>=1.21.6,<=1.22.3
-- cryptography<37.0.0
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.

how-to-use-azureml/automated-machine-learning/experimental/classification-credit-card-fraud-local-managed/auto-ml-classification-credit-card-fraud-local-managed.ipynb

@@ -92,7 +92,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.46.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.47.0 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 1.46.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.47.0 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/forecasting-backtest-many-models/auto-ml-forecasting-backtest-many-models.ipynb

@@ -406,7 +406,7 @@
         "    compute_target=compute_target,\n",
         "    node_count=2,\n",
         "    process_count_per_node=2,\n",
-        "    run_invocation_timeout=920,\n",
+        "    run_invocation_timeout=1200,\n",
         "    train_pipeline_parameters=mm_paramters,\n",
         ")"
       ]

how-to-use-azureml/automated-machine-learning/forecasting-hierarchical-timeseries/auto-ml-forecasting-hierarchical-timeseries.ipynb

@@ -365,6 +365,7 @@
         "    node_count=2,\n",
         "    process_count_per_node=8,\n",
         "    train_pipeline_parameters=hts_parameters,\n",
+        "    run_invocation_timeout=3900,\n",
         ")"
       ]
     },
@@ -634,7 +635,12 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.6.8"
+      "version": "3.7.13"
+    },
+    "vscode": {
+      "interpreter": {
+        "hash": "6db9c8d9f0cce2d9127e384e15560d42c3b661994c9f717d0553d1d8985ab1ea"
+      }
     }
   },
   "nbformat": 4,

how-to-use-azureml/automated-machine-learning/forecasting-many-models/auto-ml-forecasting-many-models.ipynb

@@ -517,7 +517,7 @@
         "    compute_target=compute_target,\n",
         "    node_count=2,\n",
         "    process_count_per_node=8,\n",
-        "    run_invocation_timeout=920,\n",
+        "    run_invocation_timeout=1200,\n",
         "    train_pipeline_parameters=mm_paramters,\n",
         ")"
       ]

how-to-use-azureml/explain-model/azure-integration/gpu-explanation/train-explain-model-gpu-tree-explainer.ipynb

@@ -106,7 +106,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "print(\"This notebook was created using version 1.46.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.47.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -241,6 +241,8 @@
         "for dist in list(available_packages):\n",
         "    if dist.key == 'pandas':\n",
         "        pandas_ver = dist.version\n",
+        "    if dist.key == 'numpy':\n",
+        "        numpy_ver = dist.version\n",
         "pandas_dep = 'pandas'\n",
         "numpy_dep = 'numpy'\n",
         "if pandas_ver:\n",
@@ -286,7 +288,7 @@
         "pip uninstall -y xgboost && \\\n",
         "conda install py-xgboost==1.3.3 && \\\n",
         "pip uninstall -y numpy && \\\n",
-        "conda install {numpy_dep} \\\n",
+        "pip install {numpy_dep} \\\n",
         "\"\"\"\n",
         "\n",
         "env.python.user_managed_dependencies = True\n",

how-to-use-azureml/ml-frameworks/pytorch/train-hyperparameter-tune-deploy-with-pytorch/pytorch_train.py

@@ -166,7 +166,7 @@ def download_data():
     from zipfile import ZipFile
     # download data
     data_file = './fowl_data.zip'
-    download_url = 'https://azureopendatastorage.blob.core.windows.net/testpublic/temp/fowl_data.zip'
+    download_url = 'https://azuremlexamples.blob.core.windows.net/datasets/fowl_data.zip'
     urllib.request.urlretrieve(download_url, filename=data_file)
 
     # extract files

how-to-use-azureml/ml-frameworks/pytorch/train-hyperparameter-tune-deploy-with-pytorch/train-hyperparameter-tune-deploy-with-pytorch.ipynb

@@ -176,7 +176,7 @@
       "metadata": {},
       "source": [
         "### Download training data\n",
-        "The dataset we will use (located on a public blob [here](https://azureopendatastorage.blob.core.windows.net/testpublic/temp/fowl_data.zip) as a zip file) consists of about 120 training images each for turkeys and chickens, with 100 validation images for each class. The images are a subset of the [Open Images v5 Dataset](https://storage.googleapis.com/openimages/web/index.html). We will download and extract the dataset as part of our training script `pytorch_train.py`"
+        "The dataset we will use (located on a public blob [here](https://azuremlexamples.blob.core.windows.net/datasets/fowl_data.zip) as a zip file) consists of about 120 training images each for turkeys and chickens, with 100 validation images for each class. The images are a subset of the [Open Images v5 Dataset](https://storage.googleapis.com/openimages/web/index.html). We will download and extract the dataset as part of our training script `pytorch_train.py`"
       ]
     },
     {
@@ -260,15 +260,14 @@
         "\n",
         "channels:\n",
         "- conda-forge\n",
+        "- pytorch\n",
         "dependencies:\n",
-        "- python=3.6.2\n",
+        "- python=3.8.12\n",
         "- pip=21.3.1\n",
+        "- pytorch::pytorch==1.8.1\n",
+        "- pytorch::torchvision==0.9.1\n",
         "- pip:\n",
-        "  - azureml-defaults==1.43.0\n",
+        "  - azureml-defaults"
-        "  - torch==1.6.0\n",
-        "  - torchvision==0.7.0\n",
-        "  - future==0.17.1\n",
-        "  - pillow"
       ]
     },
     {

how-to-use-azureml/ml-frameworks/tensorflow/distributed-tensorflow-with-horovod/distributed-tensorflow-with-horovod.ipynb

@@ -160,7 +160,7 @@
       "source": [
         "from azureml.core import Dataset\n",
         "\n",
-        "web_paths = ['https://azureopendatastorage.blob.core.windows.net/testpublic/text8.zip']\n",
+        "web_paths = ['https://azuremlexamples.blob.core.windows.net/datasets/text8.zip']\n",
         "dataset = Dataset.File.from_files(path=web_paths)"
       ]
     },

how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb

@@ -101,7 +101,7 @@
         "\n",
         "# Check core SDK version number\n",
         "\n",
-        "print(\"This notebook was created using SDK version 1.46.0, you are currently running version\", azureml.core.VERSION)"
+        "print(\"This notebook was created using SDK version 1.47.0, you are currently running version\", azureml.core.VERSION)"
       ]
     },
     {

how-to-use-azureml/training/train-on-local/train-on-local.ipynb

@@ -139,7 +139,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "with open('./train.py', 'r') as f:\n",
+        "with open('./scripts/train.py', 'r') as f:\n",
         "    print(f.read())"
       ]
     },
@@ -149,7 +149,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "with open('./mylib.py', 'r') as f:\n",
+        "with open('./scripts/mylib.py', 'r') as f:\n",
         "    print(f.read())"
       ]
     },
@@ -203,7 +203,7 @@
       "source": [
         "from azureml.core import ScriptRunConfig\n",
         "\n",
-        "src = ScriptRunConfig(source_directory='./', script='train.py', environment=user_managed_env)"
+        "src = ScriptRunConfig(source_directory='./scripts', script='train.py', environment=user_managed_env)"
       ]
     },
     {

setup-environment/configuration.ipynb

@@ -102,7 +102,7 @@
       "source": [
         "import azureml.core\n",
         "\n",
-        "print(\"This notebook was created using version 1.46.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.47.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },