docstr: Test it works fine when input tensor is integer type.
      
docstr_tok: ["Test","it","works","fine","when","input","tensor","is","integer","type","."]
code: def testIntegerTensorInput(self):
      """Test it works fine when input tensor is integer type."""
      num_batches = 5
      num_channels = 3
      num_rows = 20
      num_cols = 30
      pseudo_random = True
      overlapping = True
      tensor_shape = (num_batches, num_rows, num_cols, num_channels)
      rand_mat = self._PRNG.randint(1000, size=tensor_shape)
      self._ValidateFractionalMaxPoolResult(
          rand_mat,
          [1, math.sqrt(3), math.sqrt(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 7 for calling the FractionalMaxPoolTest obj's underlying member method code with example usage: obj.testIntegerTensorInput() without return types