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# Copyright (c) 2021 PaddlePaddle 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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"""Trainer for U2 model."""
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import cProfile
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import os
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from paddle import distributed as dist
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from yacs.config import CfgNode
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from deepspeech.training.cli import default_argument_parser
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from deepspeech.utils.dynamic_import import dynamic_import
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from deepspeech.utils.utility import print_arguments
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model_train_alias = {
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"u2": "deepspeech.exps.u2.model:U2Trainer",
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"u2_kaldi": "deepspeech.exps.u2_kaldi.model:U2Trainer",
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}
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def main_sp(config, args):
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class_obj = dynamic_import(args.model_name, model_train_alias)
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exp = class_obj(config, args)
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exp.setup()
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exp.run()
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def main(config, args):
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if args.device == "gpu" and args.nprocs > 1:
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dist.spawn(main_sp, args=(config, args), nprocs=args.nprocs)
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else:
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main_sp(config, args)
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if __name__ == "__main__":
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parser = default_argument_parser()
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parser.add_argument(
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'--model-name',
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type=str,
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default='u2_kaldi',
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help='model name, e.g: deepspeech2, u2, u2_kaldi, u2_st')
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args = parser.parse_args()
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print_arguments(args, globals())
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config = CfgNode()
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config.set_new_allowed(True)
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config.merge_from_file(args.config)
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if args.opts:
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config.merge_from_list(args.opts)
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config.freeze()
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print(config)
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if args.dump_config:
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with open(args.dump_config, 'w') as f:
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print(config, file=f)
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# Setting for profiling
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pr = cProfile.Profile()
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pr.runcall(main, config, args)
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pr.dump_stats(os.path.join(args.output, 'train.profile'))
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