Update docstrings and documentations

Author: mvsusp

src/sagemaker/chainer/README.rst

@@ -145,10 +145,10 @@ Optional arguments
 
 The following are optional arguments. When you create a ``Chainer`` object, you can specify these as keyword arguments.
 
--  ``source_dir`` Path (absolute or relative) to a directory with any
-   other training source code dependencies including the entry point
-   file. Structure within this directory will be preserved when training
-   on SageMaker.
+-  ``source_dir`` Single path (absolute or relative) or a list of paths
+    to directories with any other training source code dependencies
+    aside from the entry point file (default: None). The structures
+    within this directories are preserved when training on Amazon SageMaker.
 -  ``hyperparameters`` Hyperparameters that will be used for training.
    Will be made accessible as a dict[str, str] to the training code on
    SageMaker. For convenience, accepts other types besides str, but

src/sagemaker/chainer/estimator.py

@@ -64,9 +64,9 @@ def __init__(self, entry_point, use_mpi=None, num_processes=None, process_slots_
                 set to the number of GPUs on the instance (on GPU instances), or one (on CPU instances).
             additional_mpi_options (str): String of options to the 'mpirun' command used to run the entry point.
                 For example, '-X NCCL_DEBUG=WARN' will pass that option string to the mpirun command.
-            source_dir (str): Path (absolute or relative) to a directory with any other training
-                source code dependencies aside from tne entry point file (default: None). Structure within this
-                directory are preserved when training on Amazon SageMaker.
+            source_dir (str or [str]): Single path (absolute or relative) or a list of paths to directories with
+                any other training source code dependencies aside from the entry point file (default: None).
+                The structures within this directories are preserved when training on Amazon SageMaker.
             hyperparameters (dict): Hyperparameters that will be used for training (default: None).
                 The hyperparameters are made accessible as a dict[str, str] to the training code on SageMaker.
                 For convenience, this accepts other types for keys and values, but ``str()`` will be called

src/sagemaker/mxnet/README.rst

@@ -267,10 +267,10 @@ Optional arguments
 
 The following are optional arguments. When you create an ``MXNet`` object, you can specify these as keyword arguments.
 
--  ``source_dir`` Path (absolute or relative) to a directory with any
-   other training source code dependencies including the entry point
-   file. Structure within this directory will be preserved when training
-   on SageMaker.
+-  ``source_dir`` Single path (absolute or relative) or a list of paths
+    to directories with any other training source code dependencies
+    aside from the entry point file (default: None). The structures
+    within this directories are preserved when training on Amazon SageMaker.
 -  ``hyperparameters`` Hyperparameters that will be used for training.
    Will be made accessible as a dict[str, str] to the training code on
    SageMaker. For convenience, accepts other types besides str, but

src/sagemaker/mxnet/estimator.py

@@ -50,9 +50,9 @@ def __init__(self, entry_point, source_dir=None, hyperparameters=None, py_versio
         Args:
             entry_point (str): Path (absolute or relative) to the Python source file which should be executed
                 as the entry point to training. This should be compatible with either Python 2.7 or Python 3.5.
-            source_dir (str): Path (absolute or relative) to a directory with any other training
-                source code dependencies aside from tne entry point file (default: None). Structure within this
-                directory are preserved when training on Amazon SageMaker.
+            source_dir (str or [str]): Single path (absolute or relative) or a list of paths to directories with
+                any other training source code dependencies aside from the entry point file (default: None).
+                The structures within this directories are preserved when training on Amazon SageMaker.
             hyperparameters (dict): Hyperparameters that will be used for training (default: None).
                 The hyperparameters are made accessible as a dict[str, str] to the training code on SageMaker.
                 For convenience, this accepts other types for keys and values, but ``str()`` will be called

src/sagemaker/pytorch/README.rst

@@ -171,10 +171,10 @@ Optional arguments
 
 The following are optional arguments. When you create a ``PyTorch`` object, you can specify these as keyword arguments.
 
--  ``source_dir`` Path (absolute or relative) to a directory with any
-   other training source code dependencies including the entry point
-   file. Structure within this directory will be preserved when training
-   on SageMaker.
+-  ``source_dir`` Single path (absolute or relative) or a list of paths
+    to directories with any other training source code dependencies
+    aside from the entry point file (default: None). The structures
+    within this directories are preserved when training on Amazon SageMaker.
 -  ``hyperparameters`` Hyperparameters that will be used for training.
    Will be made accessible as a dict[str, str] to the training code on
    SageMaker. For convenience, accepts other types besides strings, but

src/sagemaker/pytorch/estimator.py

@@ -47,9 +47,9 @@ def __init__(self, entry_point, source_dir=None, hyperparameters=None, py_versio
         Args:
             entry_point (str): Path (absolute or relative) to the Python source file which should be executed
                 as the entry point to training. This should be compatible with either Python 2.7 or Python 3.5.
-            source_dir (str): Path (absolute or relative) to a directory with any other training
-                source code dependencies aside from tne entry point file (default: None). Structure within this
-                directory are preserved when training on Amazon SageMaker.
+            source_dir (str or [str]): Single path (absolute or relative) or a list of paths to directories with
+                any other training source code dependencies aside from the entry point file (default: None).
+                The structures within this directories are preserved when training on Amazon SageMaker.
             hyperparameters (dict): Hyperparameters that will be used for training (default: None).
                 The hyperparameters are made accessible as a dict[str, str] to the training code on SageMaker.
                 For convenience, this accepts other types for keys and values, but ``str()`` will be called

src/sagemaker/tensorflow/README.rst

@@ -405,10 +405,10 @@ Optional Arguments
 The following are optional arguments. When you create a ``TensorFlow`` object,
 you can specify these as keyword arguments.
 
--  ``source_dir (str)`` Path (absolute or relative) to a directory with any
-   other training source code dependencies including the entry point
-   file. Structure within this directory will be preserved when training
-   on SageMaker.
+-  ``source_dir (str)`` Single path (absolute or relative) or a list of paths
+    to directories with any other training source code dependencies
+    aside from the entry point file (default: None). The structures
+    within this directories are preserved when training on Amazon SageMaker.
 -  ``requirements_file (str)`` Path to a ``requirements.txt`` file. The path should
    be within and relative to ``source_dir``. This is a file containing a list of items to be
    installed using pip install. Details on the format can be found in the