43 lines
1.6 KiB
Python
43 lines
1.6 KiB
Python
# 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.
|
|
# ==============================================================================
|
|
"""Benchmarks for `tf.data.Dataset.range()`."""
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
|
|
from tensorflow.python.data.benchmarks import benchmark_base
|
|
from tensorflow.python.data.ops import dataset_ops
|
|
|
|
|
|
class RangeBenchmark(benchmark_base.DatasetBenchmarkBase):
|
|
"""Benchmarks for `tf.data.Dataset.range()`."""
|
|
|
|
def benchmark_range(self):
|
|
for modeling_enabled in [False, True]:
|
|
num_elements = 10000000 if modeling_enabled else 50000000
|
|
options = dataset_ops.Options()
|
|
options.experimental_optimization.autotune = modeling_enabled
|
|
dataset = dataset_ops.Dataset.range(num_elements)
|
|
dataset = dataset.with_options(options)
|
|
|
|
self.run_and_report_benchmark(
|
|
dataset,
|
|
num_elements=num_elements,
|
|
name="modeling_%s" % ("on" if modeling_enabled else "off"))
|
|
|
|
|
|
if __name__ == "__main__":
|
|
benchmark_base.test.main()
|