code: def testPoolingRatioHasMoreDimThanInput(self):
      with self.cached_session() as _:
          with self.assertRaisesRegex(
              errors.InvalidArgumentError,
              r"Pooling ratio is higher than input dimension size for dimension 1.*",
          ):
              result = nn_ops.gen_nn_ops.fractional_avg_pool(
                  value=constant_op.constant(
                      value=[[[[1, 4, 2, 3]]]], dtype=dtypes.int64
                  ),
                  pooling_ratio=[1.0, 1.44, 1.73, 1.0],
                  pseudo_random=False,
                  overlapping=False,
                  deterministic=False,
                  seed=0,
                  seed2=0,
                  name=None,
              )
              self.evaluate(result)
  
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 13 for calling the FractionalAvgTest obj's underlying member method code with example usage: obj.testPoolingRatioHasMoreDimThanInput() without return types