doc: clarify requirements.txt usage for Chainer, MXNet, and Scikit-learn

This change is just a copy of aws#1215, which revised the PyTorch docs.

Author: laurenyu

doc/using_chainer.rst

@@ -116,7 +116,10 @@ When running your training script on SageMaker, it will have access to some pre-
 For more information on the runtime environment, including specific package versions, see `SageMaker Chainer Docker containers <#sagemaker-chainer-docker-containers>`__.
 
 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.
-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.
+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 a Chainer estimator.
+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.
 
 Create an Estimator
@@ -637,4 +640,4 @@ SageMaker Chainer Docker containers
 
 You can visit the SageMaker Chainer containers repository here: https://github.com/aws/sagemaker-chainer-container
 
-For information about SageMaker Chainer Docker containers and their dependencies, see `SageMaker Chainer Docker containers <https://github.com/aws/sagemaker-python-sdk/tree/master/src/sagemaker/chainer#sagemaker-chainer-docker-containers>`_.
+For information about SageMaker Chainer Docker containers and their dependencies, see `SageMaker Chainer Docker containers <https://github.com/aws/sagemaker-python-sdk/tree/master/src/sagemaker/chainer#sagemaker-chainer-docker-containers>`_.

doc/using_mxnet.rst

@@ -310,7 +310,10 @@ When running your training script on SageMaker, it will have access to some pre-
 For more information on the runtime environment, including specific package versions, see `SageMaker MXNet Containers <#sagemaker-mxnet-containers>`__.
 
 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.
-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.
+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 an MXNet estimator.
+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.
 
 Create an Estimator

doc/using_pytorch.rst

@@ -125,7 +125,7 @@ Using third-party libraries
 When running your training script on SageMaker, it will have access to some pre-installed third-party libraries including ``torch``, ``torchvisopm``, and ``numpy``.
 For more information on the runtime environment, including specific package versions, see `SageMaker PyTorch Docker containers <#id4>`__.
 
-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. 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.
+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 a PyTorch estimator. 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.
 
 

doc/using_sklearn.rst

@@ -114,11 +114,12 @@ When running your training script on SageMaker, it has access to some pre-instal
 For more information on the runtime environment, including specific package versions, see `SageMaker Scikit-learn Docker Container <https://github.com/aws/sagemaker-scikit-learn-container>`__.
 
 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.
-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.
+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 a Scikit-learn estimator.
+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.
 
-
-
 Create an Estimator
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