Upgrade the TF2 version from 2.3.1 to 2.4.1

Author: karan6181

training/distributed_training/tensorflow/data_parallel/bert/Dockerfile

@@ -1,6 +1,6 @@
 ARG region
 
-FROM 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:2.3.1-gpu-py37-cu110-ubuntu18.04
+FROM 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:2.4.1-gpu-py37-cu110-ubuntu18.04
 
 RUN 	pip --no-cache-dir --no-cache install \
         scikit-learn==0.23.1 \

training/distributed_training/tensorflow/data_parallel/bert/tensorflow2_smdataparallel_bert_demo.ipynb

@@ -8,7 +8,7 @@
     "\n",
     "HSMDataParallel is a new capability in Amazon SageMaker to train deep learning models faster and cheaper. SMDataParallel is a distributed data parallel training framework for TensorFlow, PyTorch, and MXNet.\n",
     "\n",
-    "This notebook example shows how to use SMDataParallel with TensorFlow(version 2.3.1) on [Amazon SageMaker](https://aws.amazon.com/sagemaker/) to train a BERT model using [Amazon FSx for Lustre file-system](https://aws.amazon.com/fsx/lustre/) as data source.\n",
+    "This notebook example shows how to use SMDataParallel with TensorFlow(version 2.4.1) on [Amazon SageMaker](https://aws.amazon.com/sagemaker/) to train a BERT model using [Amazon FSx for Lustre file-system](https://aws.amazon.com/fsx/lustre/) as data source.\n",
     "\n",
     "The outline of steps is as follows:\n",
     "\n",

training/distributed_training/tensorflow/data_parallel/maskrcnn/Dockerfile

@@ -1,6 +1,6 @@
 ARG region
 
-FROM 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:2.3.1-gpu-py37-cu110-ubuntu18.04
+FROM 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:2.4.1-gpu-py37-cu110-ubuntu18.04
 
 RUN 	pip --no-cache-dir --no-cache install \
         Cython \

training/distributed_training/tensorflow/data_parallel/maskrcnn/tensorflow2_smdataparallel_maskrcnn_demo.ipynb

@@ -8,7 +8,7 @@
     "\n",
     "SMDataParallel is a new capability in Amazon SageMaker to train deep learning models faster and cheaper. SMDataParallel is a distributed data parallel training framework for TensorFlow, PyTorch, and MXNet.\n",
     "\n",
-    "This notebook example shows how to use SMDataParallel with TensorFlow(version 2.3.1) on [Amazon SageMaker](https://aws.amazon.com/sagemaker/) to train a MaskRCNN model on [COCO 2017 dataset](https://cocodataset.org/#home) using [Amazon FSx for Lustre file-system](https://aws.amazon.com/fsx/lustre/) as data source.\n",
+    "This notebook example shows how to use SMDataParallel with TensorFlow(version 2.4.1) on [Amazon SageMaker](https://aws.amazon.com/sagemaker/) to train a MaskRCNN model on [COCO 2017 dataset](https://cocodataset.org/#home) using [Amazon FSx for Lustre file-system](https://aws.amazon.com/fsx/lustre/) as data source.\n",
     "\n",
     "The outline of steps is as follows:\n",
     "\n",