code: def test(self, use_cpu_only, backend, op, data_format, padding):
      shape = None
      kwargs = {}
      if op == tf.keras.layers.ZeroPadding1D:
          padding = padding[-1]
          shape = np.random.randint(low=2, high=4, size=3)
      elif op == tf.keras.layers.ZeroPadding2D:
          padding = padding[1:]
          kwargs = {"data_format": data_format}
          shape = np.random.randint(low=2, high=4, size=4)
      elif op == tf.keras.layers.ZeroPadding3D:
          kwargs = {"data_format": data_format}
          shape = np.random.randint(low=2, high=4, size=5)
      model = tf.keras.Sequential(
          [op(batch_input_shape=shape, padding=padding, **kwargs)]
      )
      run_compare_tf_keras(
          model,
          [random_gen(shape, rand_min=-10, rand_max=10)],
          use_cpu_only=use_cpu_only,
          backend=backend,
      )
  
imports: import random
  from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.frontend.tensorflow2.test.testing_utils import run_compare_tf_keras
  from coremltools.converters.mil.testing_reqs import *
label_desc: Use image node_id 1 for calling the TestPadding obj's underlying member method code with example usage: obj.test(use_cpu_only, backend, op, data_format, padding) without return types