yt8m_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