code: def testKernelSmallerThanStride(self, data_format, op_name):
      expected_output = np.reshape(
          [
              0.037037037037037035,
              0.1111111111111111,
              0.25925925925925924,
              0.3333333333333333,
              0.7037037037037037,
              0.7777777777777778,
              0.9259259259259259,
              1.0,
          ],
          [1, 2, 2, 2, 1],
      )
  
      self._VerifyValues(
          input_sizes=[1, 3, 3, 3, 1],
          filter_sizes=[1, 1, 1, 1, 1],
          strides=[2, 2, 2],
          padding="SAME",
          expected=expected_output,
          data_format_src="NDHWC",
          data_format_dst=data_format,
          op_name=op_name,
      )
      self._VerifyValues(
          input_sizes=[1, 3, 3, 3, 1],
          filter_sizes=[1, 1, 1, 1, 1],
          strides=[2, 2, 2],
          padding="VALID",
          expected=expected_output,
          data_format_src="NDHWC",
          data_format_dst=data_format,
          op_name=op_name,
      )
  
      expected_output = np.reshape(
          [
              0.5408163265306123,
              0.5801749271137027,
              0.28061224489795916,
              0.8163265306122448,
              0.8556851311953353,
              0.4030612244897959,
              0.41873177842565595,
              0.43403790087463556,
              0.19642857142857142,
              2.4693877551020407,
              2.5087463556851315,
              1.1377551020408163,
              2.7448979591836733,
              2.7842565597667637,
              1.260204081632653,
              1.168731778425656,
              1.1840379008746356,
              0.5178571428571429,
              1.0951166180758019,
              1.1060495626822158,
              0.4464285714285714,
              1.1716472303206997,
              1.1825801749271136,
              0.4770408163265306,
              0.3691690962099125,
              0.37244897959183676,
              0.125,
          ],
          [1, 3, 3, 3, 1],
      )
      self._VerifyValues(
          input_sizes=[1, 7, 7, 7, 1],
          filter_sizes=[2, 2, 2, 1, 1],
          strides=[3, 3, 3],
          padding="SAME",
          expected=expected_output,
          data_format_src="NDHWC",
          data_format_dst=data_format,
          op_name=op_name,
      )
  
      expected_output = np.reshape(
          [
              0.5408163265306123,
              0.5801749271137027,
              0.8163265306122448,
              0.8556851311953353,
              2.4693877551020407,
              2.5087463556851315,
              2.7448979591836733,
              2.7842565597667637,
          ],
          [1, 2, 2, 2, 1],
      )
      self._VerifyValues(
          input_sizes=[1, 7, 7, 7, 1],
          filter_sizes=[2, 2, 2, 1, 1],
          strides=[3, 3, 3],
          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 10 for calling the Conv3DTest obj's underlying member method code with example usage: obj.testKernelSmallerThanStride(data_format, op_name) without return types