import tensorflow as tf

      shape=[],
      dtype=tf.int64,
      initializer=tf.initializers.zeros(),
      trainable=False,
      collections=[tf.GraphKeys.GLOBAL_VARIABLES])
  return global_step


def get_src_train_op(loss):  # pylint: disable=unused-argument
  """Returns the source training op."""
  global_step = tf.train.get_global_step()
  src_learning_rate = FLAGS.learning_rate
  src_learning_rate = tf.train.piecewise_constant(
      global_step, [800,],
      [FLAGS.learning_rate, FLAGS.learning_rate * 0.1])
  optimizer = tf.train.MomentumOptimizer(
      learning_rate=src_learning_rate,
      momentum=0.9,
      use_nesterov=True
  )
