Automated g4 rollback of changelist 160182040

PiperOrigin-RevId: 160190881

1 files changed, 5 insertions, 38 deletions

diff --git a/tensorflow/examples/image_retraining/retrain.py b/tensorflow/examples/image_retraining/retrain.py
index 44a3097d80..8e3b1a3a36 100644
--- a/tensorflow/examples/image_retraining/retrain.py
+++ b/tensorflow/examples/image_retraining/retrain.py
@@ -800,27 +800,11 @@ def add_evaluation_step(result_tensor, ground_truth_tensor):
   return evaluation_step, prediction
 
 
-def save_graph_to_file(sess, graph, graph_file_name):
-  output_graph_def = graph_util.convert_variables_to_constants(
-    sess, graph.as_graph_def(), [FLAGS.final_tensor_name])
-  with gfile.FastGFile(graph_file_name, 'wb') as f:
-    f.write(output_graph_def.SerializeToString())
-  return
-
-
-def prepare_file_system():
+def main(_):
   # Setup the directory we'll write summaries to for TensorBoard
   if tf.gfile.Exists(FLAGS.summaries_dir):
     tf.gfile.DeleteRecursively(FLAGS.summaries_dir)
   tf.gfile.MakeDirs(FLAGS.summaries_dir)
-  if FLAGS.intermediate_store_frequency > 0:
-    ensure_dir_exists(FLAGS.intermediate_output_graphs_dir)
-  return
-
-
-def main(_):
-  # Prepare necessary directories  that can be used during training
-  prepare_file_system()
 
   # Set up the pre-trained graph.
   maybe_download_and_extract()
@@ -933,14 +917,6 @@ def main(_):
               (datetime.now(), i, validation_accuracy * 100,
                len(validation_bottlenecks)))
 
-      # Store intermediate results
-      intermediate_frequency = FLAGS.intermediate_store_frequency
-
-      if intermediate_frequency > 0 and (i % intermediate_frequency == 0) and i > 0:
-        intermediate_file_name = FLAGS.intermediate_output_graphs_dir + 'intermediate_' + str(i) + '.pb'
-        print('Save intermediate result to : ' + intermediate_file_name)
-        save_graph_to_file(sess, graph, intermediate_file_name)
-                
     # We've completed all our training, so run a final test evaluation on
     # some new images we haven't used before.
     test_bottlenecks, test_ground_truth, test_filenames = (
@@ -964,7 +940,10 @@ def main(_):
 
     # Write out the trained graph and labels with the weights stored as
     # constants.
-    save_graph_to_file(sess, graph, FLAGS.output_graph)
+    output_graph_def = graph_util.convert_variables_to_constants(
+        sess, graph.as_graph_def(), [FLAGS.final_tensor_name])
+    with gfile.FastGFile(FLAGS.output_graph, 'wb') as f:
+      f.write(output_graph_def.SerializeToString())
     with gfile.FastGFile(FLAGS.output_labels, 'w') as f:
       f.write('\n'.join(image_lists.keys()) + '\n')
 
@@ -984,18 +963,6 @@ if __name__ == '__main__':
       help='Where to save the trained graph.'
   )
   parser.add_argument(
-      '--intermediate_output_graphs_dir',
-      type=str,
-      default='/tmp/intermediate_graph/',
-      help='Where to save the intermediate graphs.'
-  )
-  parser.add_argument(
-      '--intermediate_store_frequency',
-      type=int,
-      default=0,
-      help='How many steps to store intermediate graph. If "0" then will not store.'
-  )
-  parser.add_argument(
       '--output_labels',
       type=str,
       default='/tmp/output_labels.txt',