Update using_tf.rst

Added example of creating an Estimator using an ECR URI

Author: IvyBazan

doc/frameworks/tensorflow/using_tf.rst

@@ -197,6 +197,26 @@ The following args are not permitted when using Script Mode:
 Where the S3 url is a path to your training data within Amazon S3.
 The constructor keyword arguments define how SageMaker runs your training script.
 
+Create an Estimator using Docker containers
+-------------------------------------------
+
+You can also create an Estimator using Docker containers by specifying the ECR URI for the Python and framework version directly. For a full list of available container URIs, see `Available Deep Learning Containers Images <https://github.com/aws/deep-learning-containers/blob/master/available_images.md>`__ For more information on using Docker containers, see `Use Your Own Algorithms or Models with Amazon SageMaker <https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html>`__.
+
+When creating an Estimator using a container, you must use the ``image_name=''`` arg to replace both of the following args:
+
+- ``py_version=''``
+- ``framework_version=''``
+
+The following example uses the ``image_name='763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:1.15.2-cpu-py37-ubuntu18.04'`` arg to specify the container image, Python version, and framework version:
+
+.. code:: python
+
+   tf_estimator = TensorFlow(entry_point='tf-train.py',
+                             role='SageMakerRole',
+                             train_instance_count=1,
+                             train_instance_type='ml.p2.xlarge',
+                             image_name='763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:1.15.2-cpu-py37-ubuntu18.04',
+                            script_mode=True)
 For more information about the sagemaker.tensorflow.TensorFlow estimator, see `SageMaker TensorFlow Classes`_.
 
 Call the fit Method