from tensorflow.python.ops import variables as vars_

      if not isinstance(opt, optimizer_.Optimizer):
        raise ValueError("Unrecognized optimizer: function should return "
                         "subclass of Optimizer. Got %s." % str(opt))
    else:
      raise ValueError("Unrecognized optimizer: should be string, "
                       "subclass of Optimizer, instance of "
                       "subclass of Optimizer or function with one argument. "
                       "Got %s." % str(optimizer))

    # All trainable variables, if specific variables are not specified.
    if variables is None:
      variables = vars_.trainable_variables()

    # Compute gradients.
    gradients = opt.compute_gradients(
        loss,
        variables,
        colocate_gradients_with_ops=colocate_gradients_with_ops)

    # Optionally add gradient noise.
    if gradient_noise_scale is not None:
      gradients = _add_scaled_noise_to_gradients(gradients,
