code: def testOptimizationLargeInputFromTensor(self):
      input_t = array_ops.placeholder(dtypes.int32, (None, None, None))
      dataset = dataset_ops.Dataset.from_tensors(input_t)
      options = options_lib.Options()
      options.experimental_optimization.apply_default_optimizations = (
          False
      )
      dataset = dataset.with_options(options)
      iterator = dataset_ops.make_initializable_iterator(dataset)
      init_op = iterator.initializer
      get_next = iterator.get_next()
  
      with self.cached_session() as sess:
          sess.run(
              init_op, {input_t: np.ones([512, 1024, 1025], np.int32)}
          )
          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 2 for calling the OptimizationTest obj's underlying member method code with example usage: obj.testOptimizationLargeInputFromTensor() without return types