code: def testMaxPool3dSamePaddingDifferentStrides(self):
      expected_output = [
          2.0,
          5.0,
          8.0,
          18.0,
          21.0,
          24.0,
          34.0,
          37.0,
          40.0,
      ]
      self._VerifyValues(
          nn_ops.max_pool3d,
          input_sizes=[1, 5, 8, 1, 1],
          window=[1, 2, 3],
          strides=[2, 3, 1],
          padding="SAME",
          expected=expected_output,
      )
  
      # Test pooling on a larger input, with different stride and kernel
      # size for the 'z' dimension.
  
      # Simulate max pooling in numpy to get the expected output.
      input_data = np.arange(1, 5 * 27 * 27 * 64 + 1).reshape(
          (5, 27, 27, 64)
      )
      input_data = np.pad(
          input_data, [[0, 0], [0, 1], [0, 1], [0, 0]], mode="constant"
      )
      expected_output = input_data[:, 1::2, 1::2, :]
      expected_output[:, -1, :, :] = input_data[:, -2, 1::2, :]
      expected_output[:, :, -1, :] = input_data[:, 1::2, -2, :]
      expected_output[:, -1, -1, :] = input_data[:, -2, -2, :]
  
      self._VerifyValues(
          nn_ops.max_pool3d,
          input_sizes=[1, 5, 27, 27, 64],
          window=[1, 2, 2],
          strides=[1, 2, 2],
          padding="SAME",
          expected=expected_output.flatten(),
      )
  
imports: import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 7 for calling the Pooling3DTest obj's underlying member method code with example usage: obj.testMaxPool3dSamePaddingDifferentStrides() without return types