if summary_writer is not None:
train_step_kwargs['summary_writer'] = sv.summary_writer
- total_loss = 0
+ total_loss = None
should_retry = True
while should_retry:
try:
logging.info('Stopping Training.')
sv.request_stop()
break
- except errors.OutOfRangeError:
+ except errors.OutOfRangeError as e:
# OutOfRangeError is thrown when epoch limit per
# tf.train.limit_epochs is reached.
- logging.info('Caught OutOfRangeError. Stopping Training.')
+ logging.info('Caught OutOfRangeError. Stopping Training. %s', e)
if logdir and sv.is_chief:
logging.info('Finished training! Saving model to disk.')
sv.saver.save(sess, sv.save_path, global_step=sv.global_step)