def METHOD_NAME(self):
    broadcast_shape = infer_broadcast_shape(
        self.feed_data['x'], self.feed_data['index'], self.axis)
    if not broadcast_shape:
        broadcast_shape = self.feed_data['index'].shape
    self.feed_data['index'] = np.broadcast_to(self.feed_data['index'],
                                              broadcast_shape).copy()
    broadcast_shape_list = list(broadcast_shape)
    broadcast_shape_list[self.axis] = list(
        self.feed_data['x'].shape)[self.axis]
    broadcast_shape = tuple(broadcast_shape_list)
    self.feed_data['x'] = np.broadcast_to(self.feed_data['x'],
                                          broadcast_shape).copy()
    x = paddle.static.data(
        name='x',
        shape=self.feed_data['x'].shape,
        dtype=self.feed_data['x'].dtype)
    index = paddle.static.data(
        name='index',
        shape=self.feed_data['index'].shape,
        dtype=self.feed_data['index'].dtype)
    return {'Input': [x], 'Index': [index]}