docstr: Test when num of rows/cols can evenly divide pooling ratio.
  
  This is a case regular average pooling can handle. Should be handled by
  fractional pooling as well.
code: def testDivisiblePoolingRatio(self):
      """Test when num of rows/cols can evenly divide pooling ratio.
  
      This is a case regular average pooling can handle. Should be handled by
      fractional pooling as well.
      """
      pseudo_random = True
      overlapping = True
      num_batches = 3
      num_channels = 3
      num_rows = 30
      num_cols = 50
      tensor_shape = (num_batches, num_rows, num_cols, num_channels)
      # random tensor with value in [-500.0, 500.0)
      rand_mat = self._PRNG.random_sample(tensor_shape) * 1000 - 500
      self._ValidateFractionalAvgPoolResult(
          rand_mat, [1, 2, 2, 1], pseudo_random, overlapping
      )
  
imports: import math
  import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  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
  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 10 for calling the FractionalAvgTest obj's underlying member method code with example usage: obj.testDivisiblePoolingRatio() without return types