docstr: Verifies the output values of the pooling function.
  
  Args:
    pool_func: Pooling function to be called, e.g., tf.nn.max_pool2d
    pool_grad_func: Corresponding pooling gradient function.
    input_sizes: Input tensor dimensions.
    ksize: The kernel size dimensions
    strides: The stride dimensions
    padding: Padding type.
    pool_grad_grad_func: Second-order gradient function, if available.
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code: def _VerifyValues(
      self,
      pool_func,
      pool_grad_func,
      input_sizes,
      ksize,
      strides,
      padding,
      pool_grad_grad_func=None,
  ):
      """Verifies the output values of the pooling function.
  
      Args:
        pool_func: Pooling function to be called, e.g., tf.nn.max_pool2d
        pool_grad_func: Corresponding pooling gradient function.
        input_sizes: Input tensor dimensions.
        ksize: The kernel size dimensions
        strides: The stride dimensions
        padding: Padding type.
        pool_grad_grad_func: Second-order gradient function, if available.
      """
      for data_format in GetTestConfigs():
          self._VerifyOneTest(
              pool_func,
              pool_grad_func,
              input_sizes,
              ksize,
              strides,
              padding,
              data_format,
              pool_grad_grad_func=pool_grad_grad_func,
          )
  
imports: import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  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 nn_ops
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 2 for calling the PoolGradTest obj's underlying member method code with example usage: obj._VerifyValues(pool_func, pool_grad_func, input_sizes, ksize, strides, padding, pool_grad_grad_func) without return types