blob: 646f306f51954a4646983a66ecedefe7e8a67add [file] [log] [blame]
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for the OptimizeDataset serialization."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.data.experimental.kernel_tests.serialization import dataset_serialization_test_base
from tensorflow.python.data.experimental.ops import optimization
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.platform import test
class OptimizeDatasetSerializationTest(
dataset_serialization_test_base.DatasetSerializationTestBase):
def testCore(self):
def build_dataset(num_elements, batch_size):
return dataset_ops.Dataset.range(num_elements).map(lambda x: x * x).batch(
batch_size).apply(optimization.optimize(["map_and_batch_fusion"]))
self.run_core_tests(lambda: build_dataset(200, 10), 20)
def testWithNewFunction(self):
"""Tests that optimized datasets with new functions work."""
def build_dataset():
dataset = dataset_ops.Dataset.range(100)
dataset = dataset.map(lambda x: x)
dataset = dataset.batch(5)
# map_vectorization adds a new vectorized function to the function
# library.
dataset = dataset.apply(optimization.optimize(["map_vectorization"]))
return dataset
self.run_core_tests(build_dataset, 20)
if __name__ == "__main__":
test.main()