def layer_norm(x,
               filters=None,
               epsilon=1e-6,
               name=None,
               reuse=None,
               layer_collection=None):
  """Layer normalize the tensor x, averaging over the last dimension."""
  if filters is None:
    filters = shape_list(x)[-1]
  with tf.variable_scope(
      name, default_name="layer_norm", values=[x], reuse=reuse):
    scale, bias = layer_norm_vars(filters)
    return layer_norm_compute(x, epsilon, scale, bias,
                              layer_collection=layer_collection)
Layer normalize the tensor x, averaging over the last dimension.