code: def _VerifyValues(
      self, pool_func, input_sizes, window, strides, padding, expected
  ):
      for data_format, use_gpu in GetTestConfigs():
          self._VerifyOneTest(
              pool_func,
              input_sizes,
              window,
              strides,
              padding,
              data_format,
              dtypes.float32,
              expected,
              use_gpu,
          )
          # Don't test bfloat16 on GPU if there is no GPU available.
          if (not use_gpu) or test_util.is_gpu_available(
              cuda_only=True
          ):
              self._VerifyOneTest(
                  pool_func,
                  input_sizes,
                  window,
                  strides,
                  padding,
                  data_format,
                  dtypes.bfloat16,
                  expected,
                  use_gpu,
              )
  
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 2 for calling the PoolingTest obj's underlying member method code with example usage: obj._VerifyValues(pool_func, input_sizes, window, strides, padding, expected) without return types