wehub-resource-sync
48 lines
1.8 KiB
Python
48 lines
1.8 KiB
Python
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Benchmarks for `tf.data.Dataset.range()`."""
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from tensorflow.python.data.benchmarks import benchmark_base
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from tensorflow.python.data.ops import dataset_ops
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from tensorflow.python.data.ops import options as options_lib
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class RangeBenchmark(benchmark_base.DatasetBenchmarkBase):
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"""Benchmarks for `tf.data.Dataset.range()`."""
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def _benchmark_range(self, num_elements, autotune, benchmark_id):
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options = options_lib.Options()
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options.autotune.enabled = autotune
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dataset = dataset_ops.Dataset.range(num_elements)
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dataset = dataset.with_options(options)
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self.run_and_report_benchmark(
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dataset,
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num_elements=num_elements,
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extras={
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"model_name": "range.benchmark.%d" % benchmark_id,
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"parameters": "%d.%s" % (num_elements, autotune),
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},
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name="modeling_%s" % ("on" if autotune else "off"))
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def benchmark_range_with_modeling(self):
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self._benchmark_range(num_elements=10000000, autotune=True, benchmark_id=1)
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def benchmark_range_without_modeling(self):
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self._benchmark_range(num_elements=50000000, autotune=False, benchmark_id=2)
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if __name__ == "__main__":
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benchmark_base.test.main()
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