def importHelper(self, struct):
        m = StrStrHashMap()
        keysAndValues = struct.get(self.__field)
        for i in range(0, len(keysAndValues), 2):
            m[keysAndValues[i]] = keysAndValues[i+1]
        return m
def _compute_reg_grads(gen_grads, disc_vars):
  """Compute gradients norm (this is an upper-bpund of the full-batch norm)."""
  gen_norm = tf.accumulate_n([tf.reduce_sum(u * u) for u in gen_grads])
  disc_reg_grads = tf.gradients(gen_norm, disc_vars)
  return disc_reg_grads