import tensorflow as tf

    return
  with tf.variable_scope("losses_avg"):
    with tf.variable_scope("problem_0"):
      for var_name in ["total", "extra", "training"]:
        tf.get_variable(
            "%s_loss" % var_name, initializer=100.0, trainable=False)
  with tf.variable_scope("train_stats"):
    tf.get_variable("problem_0_steps", initializer=0, trainable=False)


# These metrics are implemented with py_funcs and therefore do no work with TPU
TPU_METRIC_BLACKLIST = set([
