def main(argv=None): # pylint: disable=unused-argument
cifar10.maybe_download_and_extract()
if FLAGS.retrain_count != 1: FLAGS.retrain_count = 2
if FLAGS.retrain:
print("Will only retrain the final %d layer(s)." %
(FLAGS.retrain_count))
if FLAGS.train_dir[-5:] == 'train' and FLAGS.train_dir[-7:] != 'train':
FLAGS.train_dir = FLAGS.train_dir[0:-5] + 'retrain'
if tf.gfile.Exists(FLAGS.train_dir):
tf.gfile.DeleteRecursively(FLAGS.train_dir)
tf.gfile.MakeDirs(FLAGS.train_dir)
train(True, FLAGS.retrain_count)
else:
print("Will train from scratch")
if tf.gfile.Exists(FLAGS.train_dir):
tf.gfile.DeleteRecursively(FLAGS.train_dir)
tf.gfile.MakeDirs(FLAGS.train_dir)
train()
def main(argv=None): # pylint: disable=unused-argument
cifar10.maybe_download_and_extract()
if FLAGS.retrain:
if FLAGS.retrain_list == '':
FLAGS.retrain_list = ['softmax_linear']
else:
FLAGS.retrain_list = set(FLAGS.retrain_list.split(' ')+['softmax_linear'])
print ("Will only retrain following layer(s): %s."%(' '.join(FLAGS.retrain_list)))
if FLAGS.train_dir[-5:]=='train' and FLAGS.train_dir[-7:]!='train':
FLAGS.train_dir=FLAGS.train_dir[0:-5]+'retrain'
if tf.gfile.Exists(FLAGS.train_dir):
tf.gfile.DeleteRecursively(FLAGS.train_dir)
tf.gfile.MakeDirs(FLAGS.train_dir)
train(True,FLAGS.retrain_list)
else:
print ("Will train from scratch")
if tf.gfile.Exists(FLAGS.train_dir):
tf.gfile.DeleteRecursively(FLAGS.train_dir)
tf.gfile.MakeDirs(FLAGS.train_dir)
train()
def main(argv=None): # pylint: disable=unused-argument
cifar10.maybe_download_and_extract()
if tf.gfile.Exists(FLAGS.train_dir):
tf.gfile.DeleteRecursively(FLAGS.train_dir)
tf.gfile.MakeDirs(FLAGS.train_dir)
train()
