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* improve memory benchmarking * correct typo * fix current memory * check torch memory allocated * better pytorch function * add total cached gpu memory * add total gpu required * improve torch gpu usage * update memory usage * finalize memory tracing * save intermediate benchmark class * fix conflict * improve benchmark * improve benchmark * finalize * make style * improve benchmarking * correct typo * make train function more flexible * fix csv save * better repr of bytes * better print * fix __repr__ bug * finish plot script * rename plot file * delete csv and small improvements * fix in plot * fix in plot * correct usage of timeit * remove redundant line * remove redundant line * fix bug * add hf parser tests * add versioning and platform info * make style * add gpu information * ensure backward compatibility * finish adding all tests * Update src/transformers/benchmark/benchmark_args.py Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * Update src/transformers/benchmark/benchmark_args_utils.py Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * delete csv files * fix isort ordering * add out of memory handling * add better train memory handling Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
30 lines
1.0 KiB
Python
30 lines
1.0 KiB
Python
# coding=utf-8
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# Copyright 2018 The HuggingFace Inc. team.
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# Copyright (c) 2018, NVIDIA CORPORATION. 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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""" Benchmarking the library on inference and training """
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from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments
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def main():
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parser = HfArgumentParser(PyTorchBenchmarkArguments)
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benchmark_args = parser.parse_args_into_dataclasses()[0]
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benchmark = PyTorchBenchmark(args=benchmark_args)
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benchmark.run()
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if __name__ == "__main__":
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main()
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