def testOptimizationNonSerializableAsDirectInput(self):
"""Tests that non-serializable dataset can be OptimizeDataset's input.
"""
dataset = dataset_ops.Dataset.from_tensors(0)
dataset = dataset.apply(optimization.non_serializable())
dataset = dataset_ops._OptimizeDataset(dataset, ["noop_elimination"])
self.assertDatasetProduces(dataset, expected_output=[0])
def testOptimizationNonSerializableAsDirectInput(self): """Tests that non-serializable dataset can be OptimizeDataset's input. """ dataset = dataset_ops.Dataset.from_tensors(0) dataset = dataset.apply(optimization.non_serializable()) dataset = dataset_ops._OptimizeDataset(dataset, ["noop_elimination"]) self.assertDatasetProduces(dataset, expected_output=[0])
def testOptimizationNonSerializableAsDirectInput(self): """Tests that non-serializable dataset can be OptimizeDataset's input.""" dataset = dataset_ops.Dataset.from_tensors(0) dataset = dataset.apply(optimization.non_serializable()) options = dataset_ops.Options() options.experimental_optimization.apply_default_optimizations = False options.experimental_optimization.noop_elimination = True dataset = dataset.with_options(options) self.assertDatasetProduces(dataset, expected_output=[0])
def testOptimizationNonSerializableAsDirectInput(self): """Tests that non-serializable dataset can be OptimizeDataset's input.""" dataset = dataset_ops.Dataset.from_tensors(0) dataset = dataset.apply(optimization.non_serializable()) options = dataset_ops.Options() options.experimental_optimization.apply_default_optimizations = False options.experimental_optimization.noop_elimination = True dataset = dataset.with_options(options) self.assertDatasetProduces(dataset, expected_output=[0])
def testOptimizationNonSerializable(self):
dataset = dataset_ops.Dataset.from_tensors(0)
dataset = dataset.apply(optimization.assert_next(["FiniteSkip"]))
dataset = dataset.skip(0) # Should not be removed by noop elimination
dataset = dataset.apply(optimization.non_serializable())
dataset = dataset.apply(optimization.assert_next(["MemoryCacheImpl"]))
dataset = dataset.skip(0) # Should be removed by noop elimination
dataset = dataset.cache()
dataset = dataset_ops._OptimizeDataset(dataset, ["noop_elimination"])
self.assertDatasetProduces(dataset, expected_output=[0])
def testOptimizationNonSerializable(self): dataset = dataset_ops.Dataset.from_tensors(0) dataset = dataset.apply(optimization.assert_next(["FiniteSkip"])) dataset = dataset.skip(0) # Should not be removed by noop elimination dataset = dataset.apply(optimization.non_serializable()) dataset = dataset.apply(optimization.assert_next(["MemoryCacheImpl"])) dataset = dataset.skip(0) # Should be removed by noop elimination dataset = dataset.cache() dataset = dataset_ops._OptimizeDataset(dataset, ["noop_elimination"]) self.assertDatasetProduces(dataset, expected_output=[0])
def testOptimizationNonSerializableAsDirectInput(self):
"""Tests that non-serializable dataset can be OptimizeDataset's input.
"""
dataset = dataset_ops.Dataset.from_tensors(0)
dataset = dataset.apply(optimization.non_serializable())
dataset = dataset_ops._OptimizeDataset(dataset, ["noop_elimination"])
iterator = dataset.make_one_shot_iterator()
get_next = iterator.get_next()
with self.cached_session() as sess:
self.assertEquals(0, sess.run(get_next))
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
def testOptimizationNonSerializable(self): dataset = dataset_ops.Dataset.from_tensors(0) dataset = dataset.apply(optimization.assert_next(["FiniteSkip"])) dataset = dataset.skip(0) # Should not be removed by noop elimination dataset = dataset.apply(optimization.non_serializable()) dataset = dataset.apply(optimization.assert_next(["MemoryCacheImpl"])) dataset = dataset.skip(0) # Should be removed by noop elimination dataset = dataset.cache() options = dataset_ops.Options() options.experimental_optimization.apply_default_optimizations = False options.experimental_optimization.noop_elimination = True dataset = dataset.with_options(options) self.assertDatasetProduces(dataset, expected_output=[0])
def testOptimizationNonSerializable(self): dataset = dataset_ops.Dataset.from_tensors(0) dataset = dataset.apply(optimization.assert_next(["FiniteSkip"])) dataset = dataset.skip(0) # Should not be removed by noop elimination dataset = dataset.apply(optimization.non_serializable()) dataset = dataset.apply(optimization.assert_next(["MemoryCacheImpl"])) dataset = dataset.skip(0) # Should be removed by noop elimination dataset = dataset.cache() options = dataset_ops.Options() options.experimental_optimization.apply_default_optimizations = False options.experimental_optimization.noop_elimination = True dataset = dataset.with_options(options) self.assertDatasetProduces(dataset, expected_output=[0])
def testOptimizationNonSerializable(self):
dataset = dataset_ops.Dataset.from_tensors(0)
dataset = dataset.apply(optimization.assert_next(["FiniteSkip"]))
dataset = dataset.skip(0) # Should not be removed by noop elimination
dataset = dataset.apply(optimization.non_serializable())
dataset = dataset.apply(optimization.assert_next(["MemoryCacheImpl"]))
dataset = dataset.skip(0) # Should be removed by noop elimination
dataset = dataset.cache()
dataset = dataset_ops._OptimizeDataset(dataset, ["noop_elimination"])
iterator = dataset.make_one_shot_iterator()
get_next = iterator.get_next()
with self.cached_session() as sess:
self.assertEquals(0, sess.run(get_next))
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
