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81 lines
2.5 KiB
81 lines
2.5 KiB
# 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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import argparse
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import paddle
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from paddleslim.quant import quant_post_dynamic
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def parse_args():
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parser = argparse.ArgumentParser(
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description="Paddle Slim Dynamic with acoustic model & vocoder.")
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# acoustic model
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parser.add_argument(
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'--model_name',
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type=str,
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default='fastspeech2_csmsc',
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choices=[
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'speedyspeech_csmsc',
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'fastspeech2_csmsc',
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'fastspeech2_aishell3',
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'fastspeech2_ljspeech',
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'fastspeech2_vctk',
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'tacotron2_csmsc',
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'fastspeech2_mix',
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'pwgan_csmsc',
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'pwgan_aishell3',
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'pwgan_ljspeech',
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'pwgan_vctk',
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'mb_melgan_csmsc',
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'hifigan_csmsc',
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'hifigan_aishell3',
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'hifigan_ljspeech',
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'hifigan_vctk',
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'wavernn_csmsc',
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],
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help='Choose model type of tts task.')
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parser.add_argument(
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"--inference_dir", type=str, help="dir to save inference models")
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parser.add_argument(
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"--weight_bits",
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type=int,
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default=8,
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choices=[8, 16],
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help="The bits for the quantized weight, and it should be 8 or 16. Default is 8.",
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)
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args, _ = parser.parse_known_args()
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return args
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# only inference for models trained with csmsc now
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def main():
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args = parse_args()
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paddle.enable_static()
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quant_post_dynamic(
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model_dir=args.inference_dir,
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save_model_dir=args.inference_dir,
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model_filename=args.model_name + ".pdmodel",
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params_filename=args.model_name + ".pdiparams",
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save_model_filename=args.model_name + "_" + str(args.weight_bits) +
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"bits.pdmodel",
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save_params_filename=args.model_name + "_" + str(args.weight_bits) +
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"bits.pdiparams",
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weight_bits=args.weight_bits, )
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if __name__ == "__main__":
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main()
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