code: def testConv3D2x2x2Filter(self, data_format, op_name):
      expected_output = np.reshape(
          [
              3.7719907407407405,
              3.850694444444445,
              3.929398148148149,
              4.265046296296295,
              4.357638888888888,
              4.450231481481481,
              6.730324074074074,
              6.892361111111109,
              7.054398148148148,
              7.223379629629629,
              7.399305555555557,
              7.575231481481481,
              9.688657407407408,
              9.934027777777779,
              10.17939814814815,
              10.181712962962962,
              10.440972222222221,
              10.700231481481481,
          ],
          [1, 3, 1, 2, 3],
      )
      # expected_shape = [1, 3, 1, 2, 5]
      self._VerifyValues(
          input_sizes=[1, 4, 2, 3, 3],  # b, z, y, x, fin
          filter_sizes=[2, 2, 2, 3, 3],  # z, y, x, fin, fout
          strides=[1, 1, 1],
          padding="VALID",
          expected=expected_output,
          data_format_src="NDHWC",
          data_format_dst=data_format,
          op_name=op_name,
      )
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.compiler.tests import test_utils
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import nn_ops
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 4 for calling the Conv3DTest obj's underlying member method code with example usage: obj.testConv3D2x2x2Filter(data_format, op_name) without return types