60 lines
2.2 KiB
Python
60 lines
2.2 KiB
Python
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# Copyright (c) 2020 Mobvoi Inc. (authors: Binbin Zhang, Di Wu)
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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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from __future__ import print_function
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import argparse
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import os
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import torch
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import yaml
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from wenet.transformer.asr_model import init_asr_model
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from wenet.utils.checkpoint import load_checkpoint
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='export your script model')
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parser.add_argument('--config', required=True, help='config file')
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parser.add_argument('--checkpoint', required=True, help='checkpoint model')
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parser.add_argument('--output_file', required=True, help='output file')
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parser.add_argument('--output_quant_file',
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default=None,
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help='output quantized model file')
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args = parser.parse_args()
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# No need gpu for model export
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os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
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with open(args.config, 'r') as fin:
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configs = yaml.load(fin, Loader=yaml.FullLoader)
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model = init_asr_model(configs)
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print(model)
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load_checkpoint(model, args.checkpoint)
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# Export jit torch script model
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script_model = torch.jit.script(model)
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script_model.save(args.output_file)
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print('Export model successfully, see {}'.format(args.output_file))
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# Export quantized jit torch script model
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if args.output_quant_file:
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quantized_model = torch.quantization.quantize_dynamic(
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model, {torch.nn.Linear}, dtype=torch.qint8
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)
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print(quantized_model)
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script_quant_model = torch.jit.script(quantized_model)
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script_quant_model.save(args.output_quant_file)
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print('Export quantized model successfully, '
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'see {}'.format(args.output_quant_file))
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