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doc: update links to TF notebook examples to link to script mode examples. #1268

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Merged
merged 3 commits into from
Jan 28, 2020
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doc: update links to TF notebook examples to link to script mode examples. #1268

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doc: update links to TF notebook examples to link to script mode exam…
nadiaya Jan 27, 2020
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Merge branch 'master' into tf-doc
knakad Jan 28, 2020
c668ad0
Merge branch 'master' into tf-doc
knakad Jan 28, 2020
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4 changes: 2 additions & 2 deletions doc/using_tf.rst
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Expand Up @@ -91,7 +91,7 @@ is good practice.
Note that SageMaker doesn't support argparse actions.
For example, if you want to use a boolean hyperparameter, specify ``type`` as ``bool`` in your script and provide an explicit ``True`` or ``False`` value for this hyperparameter when you create the TensorFlow estimator.

For a complete example of a TensorFlow training script, see `mnist.py <https://github.com/awslabs/amazon-sagemaker-examples/blob/master/sagemaker-python-sdk/tensorflow_distributed_mnist/mnist.py>`__.
For a complete example of a TensorFlow training script, see `mnist.py <https://github.com/awslabs/amazon-sagemaker-examples/blob/master/sagemaker-python-sdk/tensorflow_script_mode_training_and_serving/mnist.py>`__.


Adapting your local TensorFlow script
Expand Down Expand Up @@ -360,7 +360,7 @@ Training with MKL-DNN disabled
SageMaker TensorFlow CPU images use TensorFlow built with Intel® MKL-DNN optimization.

In certain cases you might be able to get a better performance by disabling this optimization
(`for example when using small models <https://github.com/awslabs/amazon-sagemaker-examples/blob/d88d1c19861fb7733941969f5a68821d9da2982e/sagemaker-python-sdk/tensorflow_iris_dnn_classifier_using_estimators/iris_dnn_classifier.py#L7-L9>`_)
(for example when using small models).

You can disable MKL-DNN optimization for TensorFlow ``1.8.0`` and above by setting two following environment variables:

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2 changes: 1 addition & 1 deletion tests/scripts/run-notebook-test.sh
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Expand Up @@ -19,4 +19,4 @@ echo "set SAGEMAKER_ROLE_ARN=$SAGEMAKER_ROLE_ARN"
--region us-west-2 \
--lifecycle-config-name install-python-sdk \
--notebook-instance-role-arn $SAGEMAKER_ROLE_ARN \
./amazon-sagemaker-examples/sagemaker-python-sdk/tensorflow_distributed_mnist/tensorflow_batch_transform_mnist.ipynb
./amazon-sagemaker-examples/sagemaker-python-sdk/tensorflow_script_mode_training_and_serving/tensorflow_script_mode_training_and_serving.ipynb