code: def test(self, use_cpu_only, backend, rank, infer_shape):
      shape = np.random.randint(low=2, high=4, size=rank)
      # target shape does not include the batch dimension
      target_shape = random.sample(list(shape[1:]), len(shape[1:]))
      if len(target_shape) > 0 and infer_shape:
          target_shape[-1] = -1
      model = tf.keras.Sequential(
          [
              tf.keras.layers.Reshape(
                  batch_input_shape=shape, target_shape=target_shape
              )
          ]
      )
      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 TestReshape obj's underlying member method code with example usage: obj.test(use_cpu_only, backend, rank, infer_shape) without return types