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doc: fix documentation to provide working example. (#1387)
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doc/using_tf.rst

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@@ -267,19 +267,19 @@ Training with ``MPI`` is configured by specifying following fields in ``distribu
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command executed by SageMaker to launch distributed horovod training.
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In the below example we create an estimator to launch Horovod distributed training with 2 processes on one host:
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In the below example we create an estimator to launch Horovod distributed training with 4 processes on one host:
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.. code:: python
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from sagemaker.tensorflow import TensorFlow
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tf_estimator = TensorFlow(entry_point='tf-train.py', role='SageMakerRole',
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train_instance_count=1, train_instance_type='ml.p2.xlarge',
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framework_version='1.12', py_version='py3',
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train_instance_count=1, train_instance_type='ml.p3.8xlarge',
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framework_version='2.1.0', py_version='py3',
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distributions={
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'mpi': {
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'enabled': True,
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'processes_per_host': 2,
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'processes_per_host': 4,
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'custom_mpi_options': '--NCCL_DEBUG INFO'
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}
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})

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