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research/slim/train_image_classifier.py

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@@ -552,6 +552,8 @@ def clone_fn(batch_queue):
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# Merge all summaries together.
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summary_op = tf.summary.merge(list(summaries), name='summary_op')
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# Add config to avoid 'could not satisfy explicit device' problem
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sess_config = tf.ConfigProto(allow_soft_placement=True)
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###########################
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# Kicks off the training. #
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log_every_n_steps=FLAGS.log_every_n_steps,
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save_summaries_secs=FLAGS.save_summaries_secs,
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save_interval_secs=FLAGS.save_interval_secs,
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sync_optimizer=optimizer if FLAGS.sync_replicas else None)
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sync_optimizer=optimizer if FLAGS.sync_replicas else None,
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session_config=sess_config)
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if __name__ == '__main__':

samples/core/get_started/eager.ipynb

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@@ -538,7 +538,7 @@
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"\n",
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"<table>\n",
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" <tr><td>\n",
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" <img src=\"http://cs231n.github.io/assets/nn3/opt1.gif\" width=\"70%\"\n",
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" <img src=\"https://cs231n.github.io/assets/nn3/opt1.gif\" width=\"70%\"\n",
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" alt=\"Optimization algorthims visualized over time in 3D space.\">\n",
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" </td></tr>\n",
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" <tr><td align=\"center\">\n",

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