update samples from Release-161 as a part of SDK release

update samples from Release-160 as a part of  SDK release

SECURITY.md

@@ -0,0 +1,41 @@
+<!-- BEGIN MICROSOFT SECURITY.MD V0.0.7 BLOCK -->
+
+## Security
+
+Microsoft takes the security of our software products and services seriously, which includes all source code repositories managed through our GitHub organizations, which include [Microsoft](https://github.com/Microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet](https://github.com/aspnet), [Xamarin](https://github.com/xamarin), and [our GitHub organizations](https://opensource.microsoft.com/).
+
+If you believe you have found a security vulnerability in any Microsoft-owned repository that meets [Microsoft's definition of a security vulnerability](https://aka.ms/opensource/security/definition), please report it to us as described below.
+
+## Reporting Security Issues
+
+**Please do not report security vulnerabilities through public GitHub issues.**
+
+Instead, please report them to the Microsoft Security Response Center (MSRC) at [https://msrc.microsoft.com/create-report](https://aka.ms/opensource/security/create-report).
+
+If you prefer to submit without logging in, send email to [secure@microsoft.com](mailto:secure@microsoft.com).  If possible, encrypt your message with our PGP key; please download it from the [Microsoft Security Response Center PGP Key page](https://aka.ms/opensource/security/pgpkey).
+
+You should receive a response within 24 hours. If for some reason you do not, please follow up via email to ensure we received your original message. Additional information can be found at [microsoft.com/msrc](https://aka.ms/opensource/security/msrc). 
+
+Please include the requested information listed below (as much as you can provide) to help us better understand the nature and scope of the possible issue:
+
+  * Type of issue (e.g. buffer overflow, SQL injection, cross-site scripting, etc.)
+  * Full paths of source file(s) related to the manifestation of the issue
+  * The location of the affected source code (tag/branch/commit or direct URL)
+  * Any special configuration required to reproduce the issue
+  * Step-by-step instructions to reproduce the issue
+  * Proof-of-concept or exploit code (if possible)
+  * Impact of the issue, including how an attacker might exploit the issue
+
+This information will help us triage your report more quickly.
+
+If you are reporting for a bug bounty, more complete reports can contribute to a higher bounty award. Please visit our [Microsoft Bug Bounty Program](https://aka.ms/opensource/security/bounty) page for more details about our active programs.
+
+## Preferred Languages
+
+We prefer all communications to be in English.
+
+## Policy
+
+Microsoft follows the principle of [Coordinated Vulnerability Disclosure](https://aka.ms/opensource/security/cvd).
+
+<!-- END MICROSOFT SECURITY.MD BLOCK -->

configuration.ipynb

@@ -103,7 +103,7 @@
       "source": [
         "import azureml.core\n",
         "\n",
-        "print(\"This notebook was created using version 1.44.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.45.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },

contrib/fairness/fairlearn-azureml-mitigation.yml

@@ -6,7 +6,7 @@ dependencies:
   - fairlearn>=0.6.2
   - joblib
   - liac-arff
-  - raiwidgets~=0.19.0
+  - raiwidgets~=0.21.0
   - itsdangerous==2.0.1
   - markupsafe<2.1.0
   - protobuf==3.20.0

contrib/fairness/upload-fairness-dashboard.yml

@@ -6,7 +6,7 @@ dependencies:
   - fairlearn>=0.6.2
   - joblib
   - liac-arff
-  - raiwidgets~=0.19.0
+  - raiwidgets~=0.21.0
   - itsdangerous==2.0.1
   - markupsafe<2.1.0
   - protobuf==3.20.0

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

@@ -18,15 +18,18 @@ dependencies:
 - pywin32==227
 - PySocks==1.7.1
 - conda-forge::pyqt==5.12.3
-- jsonschema==4.9.1
+- jinja2<=2.11.2
+- markupsafe<2.1.0
+- tqdm==4.64.0
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.44.0
+  - azureml-widgets~=1.45.0
+  - azureml-defaults~=1.45.0
   - 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/1.44.0/validated_win32_requirements.txt [--no-deps]
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.45.0/validated_win32_requirements.txt [--no-deps]
   - arch==4.14
   - wasabi==0.9.1

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

@@ -21,13 +21,16 @@ dependencies:
 - conda-forge::fbprophet==0.7.1
 - pytorch::pytorch=1.4.0
 - cudatoolkit=10.1.243
+- jinja2<=2.11.2
+- markupsafe<2.1.0
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.44.0
+  - azureml-widgets~=1.45.0
+  - azureml-defaults~=1.45.0
   - 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/1.44.0/validated_linux_requirements.txt [--no-deps]
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.45.0/validated_linux_requirements.txt [--no-deps]
   - arch==4.14

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

@@ -22,13 +22,16 @@ dependencies:
 - conda-forge::fbprophet==0.7.1
 - pytorch::pytorch=1.4.0
 - cudatoolkit=9.0
+- jinja2<=2.11.2
+- markupsafe<2.1.0
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
-  - azureml-widgets~=1.44.0
+  - azureml-widgets~=1.45.0
+  - azureml-defaults~=1.45.0
   - 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/1.44.0/validated_darwin_requirements.txt [--no-deps]
+  - -r https://automlsdkdataresources.blob.core.windows.net/validated-requirements/1.45.0/validated_darwin_requirements.txt [--no-deps]
   - arch==4.14

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 1.44.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.45.0 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 1.44.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.45.0 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

@@ -3,7 +3,7 @@ dependencies:
   # The python interpreter version.
   # Currently Azure ML only supports 3.6.0 and later.
 - pip<=20.2.4
-- python>=3.6.0,<3.9
+- python>=3.6.0,<3.10
 - cython==0.29.14
 - urllib3==1.26.7
 - PyJWT < 2.0.0
@@ -18,4 +18,6 @@ dependencies:
   - azureml-defaults
   - azureml-sdk
   - azureml-widgets
+  - azureml-mlflow
   - pandas
+  - mlflow

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

@@ -7,7 +7,7 @@ dependencies:
   # Currently Azure ML only supports 3.6.0 and later.
 - pip<=20.2.4
 - nomkl
-- python>=3.6.0,<3.9
+- python>=3.6.0,<3.10
 - urllib3==1.26.7
 - PyJWT < 2.0.0
 - numpy>=1.21.6,<=1.22.3
@@ -20,4 +20,6 @@ dependencies:
   - azureml-defaults
   - azureml-sdk
   - azureml-widgets
+  - azureml-mlflow
   - pandas
+  - mlflow

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 1.44.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.45.0 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 1.44.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.45.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },

how-to-use-azureml/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 1.44.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.45.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },
@@ -237,12 +237,16 @@
         "import pkg_resources\n",
         "available_packages = pkg_resources.working_set\n",
         "pandas_ver = None\n",
+        "numpy_ver = None\n",
         "for dist in list(available_packages):\n",
         "    if dist.key == 'pandas':\n",
         "        pandas_ver = dist.version\n",
         "pandas_dep = 'pandas'\n",
+        "numpy_dep = 'numpy'\n",
         "if pandas_ver:\n",
         "    pandas_dep = 'pandas=={}'.format(pandas_ver)\n",
+        "if numpy_ver:\n",
+        "    numpy_dep = 'numpy=={}'.format(numpy_ver)\n",
         "\n",
         "# Note: we build shap at commit 690245 for Tesla K80 GPUs\n",
         "env.docker.base_dockerfile = f\"\"\"\n",
@@ -282,7 +286,7 @@
         "pip uninstall -y xgboost && \\\n",
         "conda install py-xgboost==1.3.3 && \\\n",
         "pip uninstall -y numpy && \\\n",
-        "conda install numpy==1.20.3 \\\n",
+        "conda install {numpy_dep} \\\n",
         "\"\"\"\n",
         "\n",
         "env.python.user_managed_dependencies = True\n",

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

@@ -7,12 +7,12 @@ dependencies:
   - flask
   - flask-cors
   - gevent>=1.3.6
-  - jinja2
   - ipython
   - matplotlib
   - ipywidgets
-  - raiwidgets~=0.19.0
+  - raiwidgets~=0.21.0
   - itsdangerous==2.0.1
   - markupsafe<2.1.0
   - scipy>=1.5.3
   - protobuf==3.20.0
+  - jinja2==3.0.3

how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.yml

@@ -6,13 +6,13 @@ dependencies:
   - flask
   - flask-cors
   - gevent>=1.3.6
-  - jinja2
   - ipython
   - matplotlib
   - azureml-dataset-runtime
   - ipywidgets
-  - raiwidgets~=0.19.0
+  - raiwidgets~=0.21.0
   - itsdangerous==2.0.1
   - markupsafe<2.1.0
   - scipy>=1.5.3
   - protobuf==3.20.0
+  - jinja2==3.0.3

how-to-use-azureml/explain-model/azure-integration/run-history/save-retrieve-explanations-run-history.yml

@@ -6,13 +6,13 @@ dependencies:
   - flask
   - flask-cors
   - gevent>=1.3.6
-  - jinja2
   - ipython
   - matplotlib
   - ipywidgets
-  - raiwidgets~=0.19.0
+  - raiwidgets~=0.21.0
   - packaging>=20.9
   - itsdangerous==2.0.1
   - markupsafe<2.1.0
   - scipy>=1.5.3
   - protobuf==3.20.0
+  - jinja2==3.0.3

how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.yml

@@ -6,13 +6,13 @@ dependencies:
   - flask
   - flask-cors
   - gevent>=1.3.6
-  - jinja2
   - ipython
   - matplotlib
   - ipywidgets
-  - raiwidgets~=0.19.0
+  - raiwidgets~=0.21.0
   - packaging>=20.9
   - itsdangerous==2.0.1
   - markupsafe<2.1.0
   - scipy>=1.5.3
   - protobuf==3.20.0
+  - jinja2==3.0.3

how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.yml

@@ -6,14 +6,14 @@ dependencies:
   - flask
   - flask-cors
   - gevent>=1.3.6
-  - jinja2
   - ipython
   - matplotlib
   - azureml-dataset-runtime
   - azureml-core
   - ipywidgets
-  - raiwidgets~=0.19.0
+  - raiwidgets~=0.21.0
   - itsdangerous==2.0.1
   - markupsafe<2.1.0
   - scipy>=1.5.3
   - protobuf==3.20.0
+  - jinja2==3.0.3

how-to-use-azureml/ml-frameworks/chainer/train-hyperparameter-tune-deploy-with-chainer/chainer_mnist.py

@@ -4,7 +4,7 @@ import os
 
 import numpy as np
 
-from utils import download_mnist
+from datautils import download_mnist
 
 import chainer
 from chainer import backend

how-to-use-azureml/ml-frameworks/chainer/train-hyperparameter-tune-deploy-with-chainer/chainer_score.py

@@ -2,7 +2,7 @@ import numpy as np
 import os
 import json
 
-from utils import download_mnist
+from datautils import download_mnist
 
 from chainer import serializers, using_config, Variable, datasets
 import chainer.functions as F

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

@@ -210,7 +210,7 @@
         "\n",
         "shutil.copy('chainer_mnist.py', project_folder)\n",
         "shutil.copy('chainer_score.py', project_folder)\n",
-        "shutil.copy('utils.py', project_folder)"
+        "shutil.copy('datautils.py', project_folder)"
       ]
     },
     {

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

@@ -283,7 +283,7 @@
         "\n",
         "# Specify a GPU base image\n",
         "pytorch_env.docker.enabled = True\n",
-        "pytorch_env.docker.base_image = 'mcr.microsoft.com/azureml/openmpi3.1.2-cuda10.1-cudnn7-ubuntu18.04'"
+        "pytorch_env.docker.base_image = 'mcr.microsoft.com/azureml/openmpi4.1.0-cuda11.1-cudnn8-ubuntu18.04'"
       ]
     },
     {

how-to-use-azureml/responsible-ai/visualize-upload-loan-decision/rai-loan-decision.yml

@@ -8,7 +8,7 @@ dependencies:
   - matplotlib
   - azureml-dataset-runtime
   - ipywidgets
-  - raiwidgets~=0.19.0
+  - raiwidgets~=0.21.0
   - liac-arff
   - packaging>=20.9
   - itsdangerous==2.0.1

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 1.44.0, you are currently running version\", azureml.core.VERSION)"
+        "print(\"This notebook was created using SDK version 1.45.0, you are currently running version\", azureml.core.VERSION)"
       ]
     },
     {

how-to-use-azureml/work-with-data/datasets-tutorial/pipeline-with-datasets/keras-mnist-fashion/train.py

@@ -1,10 +1,11 @@
-import keras
+from tensorflow.keras.models import Sequential
-from keras.models import Sequential
+from tensorflow.keras.layers import Dense, Dropout, Flatten
-from keras.layers import Dense, Dropout, Flatten
+from tensorflow.keras.layers import Conv2D, MaxPooling2D
-from keras.layers import Conv2D, MaxPooling2D
+from tensorflow.keras.layers import BatchNormalization
-from keras.layers.normalization import BatchNormalization
+from tensorflow.keras.losses import categorical_crossentropy
-from keras.utils import to_categorical
+from tensorflow.keras.optimizers import Adam
-from keras.callbacks import Callback
+from tensorflow.keras.utils import to_categorical
+from tensorflow.keras.callbacks import Callback
 
 import numpy as np
 import pandas as pd
@@ -64,8 +65,8 @@ model.add(Dense(128, activation='relu'))
 model.add(Dropout(0.3))
 model.add(Dense(num_classes, activation='softmax'))
 
-model.compile(loss=keras.losses.categorical_crossentropy,
+model.compile(loss=categorical_crossentropy,
-              optimizer=keras.optimizers.Adam(),
+              optimizer=Adam(),
               metrics=['accuracy'])
 
 # start an Azure ML run

how-to-use-azureml/work-with-data/datasets-tutorial/pipeline-with-datasets/pipeline-for-image-classification.ipynb

@@ -270,16 +270,19 @@
         "%%writefile conda_dependencies.yml\n",
         "\n",
         "dependencies:\n",
-        "- python=3.6.2\n",
+        "- python=3.8\n",
+        "- pip==20.2.4\n",
         "- pip:\n",
         "  - azureml-core\n",
         "  - azureml-dataset-runtime\n",
-        "  - keras==2.4.3\n",
+        "  - keras==2.6\n",
-        "  - tensorflow==2.4.3\n",
+        "  - tensorflow-gpu==2.6\n",
         "  - numpy\n",
         "  - scikit-learn\n",
         "  - pandas\n",
-        "  - matplotlib"
+        "  - matplotlib\n",
+        "  - protobuf==3.20.1\n",
+        "  - typing-extensions==4.3.0"
       ]
     },
     {

setup-environment/configuration.ipynb

@@ -102,7 +102,7 @@
       "source": [
         "import azureml.core\n",
         "\n",
-        "print(\"This notebook was created using version 1.44.0 of the Azure ML SDK\")\n",
+        "print(\"This notebook was created using version 1.45.0 of the Azure ML SDK\")\n",
         "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")"
       ]
     },

tutorials/compute-instance-quickstarts/quickstart-azureml-python-sdk/quickstart-azureml-python-sdk.ipynb

@@ -151,8 +151,7 @@
         "# use a curated environment that has already been built for you\n",
         "\n",
         "env = Environment.get(workspace=ws, \n",
-        "                      name=\"AzureML-Scikit-learn0.24-Cuda11-OpenMpi4.1.0-py36\", \n",
+        "                      name=\"AzureML-sklearn-0.24-ubuntu18.04-py37-cpu\")"
-        "                      version=1)"
       ]
     },
     {