code: def test_op_empty_batch():
      np.random.seed(13)
      data_width = 5
      data_height = 4
      data_channels = 3
      warp_width = 2
      warp_height = 6
      batch_size = 0
      dtype = np.float32
  
      warp = _make_warp(batch_size, warp_height, warp_width, dtype)
      data_shape = (batch_size, data_height, data_width, data_channels)
      data = np.zeros(data_shape).astype(dtype)
      data_tensor = tf.constant(data)
      warp_tensor = tf.constant(warp)
      with tf.GradientTape() as tape:
          tape.watch(data_tensor)
          tape.watch(warp_tensor)
          outputs = resampler_ops.resampler(
              data=data_tensor, warp=warp_tensor
          )
      data_grad, warp_grad = tape.gradient(
          outputs, (data_tensor, warp_tensor)
      )
      assert data_grad.shape == data.shape
      assert warp_grad.shape == warp.shape
  
file_path: addons/tensorflow_addons/image/tests/resampler_ops_test.py
imports: import numpy
  import pytest
  import tensorflow
  from tensorflow_addons.image import resampler_ops
  from tensorflow_addons.utils import test_utils
label_desc: Use image node_id 6 for calling a global function with example usage: test_op_empty_batch() without return types