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

update samples from Release-126 as a part of  SDK release

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/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/torch-1.6.0%2Bcpu-cp38-cp38-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/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