code: def layer_norm(x,
                 filters=None,
                 epsilon=1e-6,
                 name=None,
                 reuse=None,
                 layer_collection=None):
    
    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)
docs: Layer normalize the tensor x, averaging over the last dimension.