code: def testOptimizationStatefulFunction(self):
      dataset = (
          dataset_ops.Dataset.range(10)
          .map(lambda _: random_ops.random_uniform([]))
          .batch(10)
      )
      options = options_lib.Options()
      options.experimental_optimization.apply_default_optimizations = (
          False
      )
      dataset = dataset.with_options(options)
      get_next = self.getNext(dataset)
      self.evaluate(get_next())
  
imports: import functools
  import time
  from absl.testing import parameterized
  import numpy
  from tensorflow.python.data.experimental.ops import batching
  from tensorflow.python.data.experimental.ops import grouping
  from tensorflow.python.data.experimental.ops import scan_ops
  from tensorflow.python.data.experimental.ops import testing
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the OptimizationTest obj's underlying member method code with example usage: obj.testOptimizationStatefulFunction() without return types