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()