docstr: Verifies the output values of the pooling function.
  
  Args:
    pool_func: Function to be called: co.MaxPool, co.AvgPool.
    input_sizes: Input tensor dimensions.
    window: Tuple of kernel dims: planes, rows, cols.
    strides: Tuple of strides for dims: planes, rows, cols.
    padding: Padding type.
    expected: An array containing the expected operation outputs.
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code: def _VerifyValues(
      self, pool_func, input_sizes, window, strides, padding, expected
  ):
      """Verifies the output values of the pooling function.
  
      Args:
        pool_func: Function to be called: co.MaxPool, co.AvgPool.
        input_sizes: Input tensor dimensions.
        window: Tuple of kernel dims: planes, rows, cols.
        strides: Tuple of strides for dims: planes, rows, cols.
        padding: Padding type.
        expected: An array containing the expected operation outputs.
      """
      total_size = 1
      for s in input_sizes:
          total_size *= s
      # Initializes the input tensor with array containing incrementing
      # numbers from 1.
      x = np.arange(1.0, total_size + 1, dtype=np.float32)
      x = x.reshape(input_sizes)
      with self.session() as sess, self.test_scope():
          inputs = array_ops.placeholder(dtypes.float32)
          t = pool_func(
              inputs,
              ksize=[1] + window + [1],
              strides=[1] + strides + [1],
              padding=padding,
          )
          vals = sess.run(t, {inputs: x})
      # Verifies values.
      actual = vals.flatten()
      self.assertAllClose(expected, actual)
  
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 1 for calling the Pooling3DTest obj's underlying member method code with example usage: obj._VerifyValues(pool_func, input_sizes, window, strides, padding, expected) without return types