documentation: Mention for custom Docker Image (aws#4270)

Author: jjerphan

doc/frameworks/pytorch/using_pytorch.rst

@@ -132,14 +132,49 @@ Using third-party libraries
 ---------------------------
 
 When running your training script on SageMaker, it will have access to some pre-installed third-party libraries including ``torch``, ``torchvision``, and ``numpy``.
-For more information on the runtime environment, including specific package versions, see `SageMaker PyTorch Docker containers <https://github.com/aws/deep-learning-containers/tree/master/pytorch>`_.
 
 If there are other packages you want to use with your script, you can include a ``requirements.txt`` file in the same directory as your training script to install other dependencies at runtime. Both ``requirements.txt`` and your training script should be put in the same folder. You must specify this folder in ``source_dir`` argument when creating PyTorch estimator.
 
 The function of installing packages using ``requirements.txt`` is supported for all PyTorch versions during training. When serving a PyTorch model, support for this function varies with PyTorch versions. For PyTorch 1.3.1 or newer, ``requirements.txt`` must be under folder ``code``. The SageMaker PyTorch Estimator will automatically save ``code`` in ``model.tar.gz`` after training (assuming you set up your script and ``requirements.txt`` correctly as stipulated in the previous paragraph). In the case of bringing your own trained model for deployment, you must save ``requirements.txt`` under folder ``code`` in ``model.tar.gz`` yourself or specify it through ``dependencies``. For PyTorch 1.2.0, ``requirements.txt`` is not supported for inference. For PyTorch 0.4.0 to 1.1.0, ``requirements.txt`` must be in ``source_dir``.
 
 A ``requirements.txt`` file is a text file that contains a list of items that are installed by using ``pip install``. You can also specify the version of an item to install. For information about the format of a ``requirements.txt`` file, see `Requirements Files <https://pip.pypa.io/en/stable/user_guide/#requirements-files>`__ in the pip documentation.
 
+If you were to use your own custom Docker Image, the `SageMaker Python SDK` and the `SageMaker Training Toolkit <https://github.com/aws/sagemaker-training-toolkit/>`__ need to be installed.
+
+To do so, you can add the following lines to your ``requirements.txt`` file:
+
+.. code:: text
+
+    sagemaker
+    sagemaker-training
+
+Deep Learning Framework-Specific SageMaker Toolkits and Containers
+------------------------------------------------------------------
+
+Framework-specific Toolkits exist. You might want to use them in your applications for framework-specific features.
+
+For Training Toolkits, see:
+
+- `SageMaker PyTorch Training Toolkit <https://github.com/aws/sagemaker-pytorch-training-toolkit>`__
+- `SageMaker MXNet Training Toolkit <https://github.com/aws/sagemaker-mxnet-training-toolkit>`__
+- `SageMaker TensorFlow Training Toolkit <https://github.com/aws/sagemaker-tensorflow-training-toolkit>`__
+
+For Inference Toolkits, see:
+
+- `SageMaker PyTorch Inference Toolkit <https://github.com/aws/sagemaker-pytorch-inference-toolkit>`__
+- `SageMaker MXNet Inference Toolkit <https://github.com/aws/sagemaker-mxnet-training-toolkit>`__
+- `SageMaker TensorFlow Inference Toolkit <https://github.com/aws/sagemaker-tensorflow-inference-toolkit>`__
+- `SageMaker HuggingFace Inference Toolkit <https://github.com/aws/sagemaker-huggingface-inference-toolkit>`__
+
+Moreover, for more information on the container runtime environment, including specific framework versions and configurations,
+see `AWS Deep Learning Containers <https://github.com/aws/deep-learning-containers/>`_. More specifically, see:
+
+- `Images for PyTorch <https://github.com/aws/deep-learning-containers/tree/master/pytorch>`__
+- `Images for MXNet <https://github.com/aws/deep-learning-containers/tree/master/mxnet>`__
+- `Images for TensorFlow <https://github.com/aws/deep-learning-containers/tree/master/tensorflow>`__
+- `Images for HuggingFace <https://github.com/aws/deep-learning-containers/tree/master/huggingface>`__
+
+
 Create an Estimator
 ===================