update documentation

Author: Chuyang Deng

doc/using_tf.rst

@@ -42,7 +42,7 @@ To train a TensorFlow model by using the SageMaker Python SDK:
 Prepare a Script Mode Training Script
 ======================================
 
-Your TensorFlow training script must be a Python 2.7- or 3.6-compatible source file.
+Your TensorFlow training script must be a Python 2.7-, 3.6- or 3.7-compatible source file.
 
 The training script is very similar to a training script you might run outside of SageMaker, but you can access useful properties about the training environment through various environment variables, including the following:
 
@@ -143,6 +143,11 @@ To use Script Mode, set at least one of these args
 - ``py_version='py3'``
 - ``script_mode=True``
 
+To use Python 3.7, please specify both of the args:
+
+- ``py_version='py37'``
+- ``framework_version='1.15.2'``
+
 When using Script Mode, your training script needs to accept the following args:
 
 - ``model_dir``

src/sagemaker/tensorflow/README.rst

@@ -69,7 +69,7 @@ The latest containers include the following Python packages:
 | tensorflow                     | 1.15.2        | 2.1.0         |
 +--------------------------------+---------------+---------------+
 
-Script Mode TensorFlow Docker images support both Python 2.7 and Python 3.6. The Docker images extend Ubuntu 16.04.
+Script Mode TensorFlow Docker images support Python 2.7 and Python 3.6, Python 3.7 for TensorFlow version 1.15.2. The Docker images extend Ubuntu 16.04.
 
 You can select version of TensorFlow by passing a ``framework_version`` keyword arg to the TensorFlow Estimator constructor. Currently supported versions are listed in the table above. You can also set ``framework_version`` to only specify major and minor version, e.g ``'1.6'``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.6.0.
 Alternatively, you can build your own image by following the instructions in the SageMaker TensorFlow containers