code: def test_cropping_3d(
      self,
      dim1_cropping,
      dim2_cropping,
      dim3_cropping,
      data_format,
      dim1_expected,
      dim2_expected,
      dim3_expected,
  ):
      if data_format == "channels_first":
          inputs = np.random.rand(3, 5, 7, 9, 13)
          expected_output = ops.convert_to_tensor(
              inputs[
                  :,
                  :,
                  dim1_expected[0] : dim1_expected[1],
                  dim2_expected[0] : dim2_expected[1],
                  dim3_expected[0] : dim3_expected[1],
              ]
          )
      else:
          inputs = np.random.rand(3, 7, 9, 13, 5)
          expected_output = ops.convert_to_tensor(
              inputs[
                  :,
                  dim1_expected[0] : dim1_expected[1],
                  dim2_expected[0] : dim2_expected[1],
                  dim3_expected[0] : dim3_expected[1],
                  :,
              ]
          )
  
      cropping = (dim1_cropping, dim2_cropping, dim3_cropping)
      self.run_layer_test(
          layers.Cropping3D,
          init_kwargs={
              "cropping": cropping,
              "data_format": data_format,
          },
          input_data=inputs,
          expected_output=expected_output,
      )
  
file_path: keras/keras/layers/reshaping/cropping3d_test.py
imports: import numpy
  import pytest
  from absl.testing import parameterized
  from keras import backend
  from keras import layers
  from keras import ops
  from keras import testing
label_desc: Use image node_id 1 for calling the Cropping3DTest obj's underlying member method code with example usage: obj.test_cropping_3d(dim1_cropping, dim2_cropping, dim3_cropping, data_format, dim1_expected, dim2_expected, dim3_expected) without return types