utils.py 文件源码

def clip_gradient_norms(gradients_to_variables, max_norm):
  """Clips the gradients by the given value.

  Args:
    gradients_to_variables: A list of gradient to variable pairs (tuples).
    max_norm: the maximum norm value.

  Returns:
    A list of clipped gradient to variable pairs.
  """
  clipped_grads_and_vars = []
  for grad, var in gradients_to_variables:
    if grad is not None:
      if isinstance(grad, tf.IndexedSlices):
        tmp = tf.clip_by_norm(grad.values, max_norm)
        grad = tf.IndexedSlices(tmp, grad.indices, grad.dense_shape)
      else:
        grad = tf.clip_by_norm(grad, max_norm)
    clipped_grads_and_vars.append((grad, var))
  return clipped_grads_and_vars