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src/tf_container/train_entry_point.py

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@@ -17,7 +17,6 @@
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import time
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from threading import Thread
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import boto3
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import tensorflow as tf
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import container_support as cs
@@ -164,7 +163,7 @@ def train():
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# only the master should export the model at the end of the execution
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if checkpoint_dir != env.model_dir and train_wrapper.task_type == 'master' and train_wrapper.saves_training():
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serve.export_saved_model(checkpoint_dir, env.model_dir, s3=boto3.client('s3', region_name=env.sagemaker_region))
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serve.export_saved_model(checkpoint_dir, env.model_dir)
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if train_wrapper.task_type != 'master':
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_wait_until_master_is_down(_get_master(tf_config))

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