docstr: Verifies the output shape of the max pooling function when tensor is empty.
  
  Args: none
code: def testMaxPool3DEmptyTensorOutputShape(self):
      """Verifies the output shape of the max pooling function when tensor is empty.
  
      Args: none
      """
      input_sizes = [0, 112, 112, 112, 64]
  
      input_data = 1.0
      input_tensor = constant_op.constant(
          input_data, shape=input_sizes, name="input"
      )
      max_pool_3d = nn_ops.max_pool3d(
          input_tensor,
          ksize=[2, 2, 2],
          strides=[2, 2, 2],
          padding="VALID",
          data_format="NDHWC",
          name="max_pool_3d",
      )
      values = self.evaluate(max_pool_3d)
      self.assertEqual(values.shape, (0, 56, 56, 56, 64))
  
imports: import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import nn_ops
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
label_desc: Use image node_id 13 for calling the PoolingTest obj's underlying member method code with example usage: obj.testMaxPool3DEmptyTensorOutputShape() without return types