update samples from Release-128 as a part of SDK release

update samples from Release-127 as a part of  SDK release

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

@@ -7,26 +7,23 @@ dependencies:
   # The python interpreter version.
   # Currently Azure ML only supports 3.6.0 and later.
 - pip==20.2.4
-- python>=3.6,<3.8
-- boto3==1.20.19
-- botocore<=1.23.19
+- python>=3.6,<3.9
 - matplotlib==3.3.4
-- numpy==1.18.5
-- cython==0.29.14
-- urllib3==1.26.7
-- scipy>=1.4.1,<=1.5.2
-- scikit-learn==0.22.1
-- py-xgboost<=1.3.3
-- holidays==0.10.3
-- conda-forge::fbprophet==0.7.1
+- py-xgboost==1.3.3
 - pytorch::pytorch=1.4.0
+- conda-forge::fbprophet==0.7.1
 - cudatoolkit=10.1.243
+- tqdm==4.62.3
+- notebook
+- pywin32==225
+- PySocks==1.7.1
+- conda-forge::pyqt==5.12.3
 
 - pip:
   # Required packages for AzureML execution, history, and data preparation.
   - azureml-widgets~=1.39.0
   - pytorch-transformers==1.0.0
-  - spacy==2.1.8
+  - 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/1.39.0/validated_win32_requirements.txt [--no-deps]

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

@@ -7,11 +7,11 @@ dependencies:
   # The python interpreter version.
   # Currently Azure ML only supports 3.6.0 and later.
 - pip==20.2.4
-- python>=3.6,<3.8
+- python>=3.6,<3.9
 - boto3==1.20.19
 - botocore<=1.23.19
 - matplotlib==3.3.4
-- numpy==1.18.5
+- numpy==1.19.5
 - cython==0.29.14
 - urllib3==1.26.7
 - scipy>=1.4.1,<=1.5.2
@@ -26,7 +26,7 @@ dependencies:
   # Required packages for AzureML execution, history, and data preparation.
   - azureml-widgets~=1.39.0
   - pytorch-transformers==1.0.0
-  - spacy==2.1.8
+  - 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/1.39.0/validated_linux_requirements.txt [--no-deps]

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

@@ -8,11 +8,11 @@ dependencies:
   # Currently Azure ML only supports 3.6.0 and later.
 - pip==20.2.4
 - nomkl
-- python>=3.6,<3.8
+- python>=3.6,<3.9
 - boto3==1.20.19
 - botocore<=1.23.19
 - matplotlib==3.3.4
-- numpy==1.18.5
+- numpy==1.19.5
 - cython==0.29.14
 - urllib3==1.26.7
 - scipy>=1.4.1,<=1.5.2
@@ -27,7 +27,7 @@ dependencies:
   # Required packages for AzureML execution, history, and data preparation.
   - azureml-widgets~=1.39.0
   - pytorch-transformers==1.0.0
-  - spacy==2.1.8
+  - 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/1.39.0/validated_darwin_requirements.txt [--no-deps]

how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb

@@ -167,6 +167,7 @@
         "                                                           # To use BERT (this is recommended for best performance), select a GPU such as \"STANDARD_NC6\" \n",
         "                                                           # or similar GPU option\n",
         "                                                           # available in your workspace\n",
+        "                                                           idle_seconds_before_scaledown = 60,\n",
         "                                                           max_nodes = num_nodes)\n",
         "    compute_target = ComputeTarget.create(ws, amlcompute_cluster_name, compute_config)\n",
         "\n",

how-to-use-azureml/ml-frameworks/fastai/fastai-with-custom-docker/fastai-with-custom-docker.ipynb

@@ -163,7 +163,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "fastai_env.docker.base_image = \"fastdotai/fastai:latest\"\n",
+        "fastai_env.docker.base_image = \"fastdotai/fastai:2021-02-11\"\n",
         "fastai_env.python.user_managed_dependencies = True"
       ]
     },

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

@@ -6,5 +6,5 @@ dependencies:
   - pillow==5.4.1
   - matplotlib
   - numpy==1.19.3
-  - https://download.pytorch.org/whl/cpu/torch-1.6.0%2Bcpu-cp36-cp36m-win_amd64.whl
-  - https://download.pytorch.org/whl/cpu/torchvision-0.7.0%2Bcpu-cp36-cp36m-win_amd64.whl
+  - https://download.pytorch.org/whl/cpu/torch-1.6.0%2Bcpu-cp38-cp38-win_amd64.whl
+  - https://download.pytorch.org/whl/cpu/torchvision-0.7.0%2Bcpu-cp38-cp38-win_amd64.whl

how-to-use-azureml/reinforcement-learning/cartpole-on-single-compute/files/docker/Dockerfile

@@ -26,6 +26,6 @@ RUN conda install -y conda=4.7.12 python=3.7 && conda clean -ay && \
     ray[rllib,dashboard,tune]==0.8.3 \
     psutil \
     setproctitle \
-    gym[classic_control] && \
+    gym[classic_control]==0.22.0 && \
     conda install -y -c conda-forge x264='1!152.20180717' ffmpeg=4.0.2 && \
     conda install -c anaconda opencv