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| # Copyright (c) 2020 Mobvoi Inc. (authors: Binbin Zhang, Di Wu) | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| from __future__ import print_function | |
| import argparse | |
| import logging | |
| import os | |
| import torch | |
| import yaml | |
| from wenet.utils.init_model import init_model | |
| def get_args(): | |
| parser = argparse.ArgumentParser(description='export your script model') | |
| parser.add_argument('--config', required=True, help='config file') | |
| parser.add_argument('--checkpoint', required=True, help='checkpoint model') | |
| parser.add_argument('--output_file', default=None, help='output file') | |
| parser.add_argument('--output_quant_file', | |
| default=None, | |
| help='output quantized model file') | |
| args = parser.parse_args() | |
| return args | |
| def main(): | |
| args = get_args() | |
| args.jit = True | |
| logging.basicConfig(level=logging.DEBUG, | |
| format='%(asctime)s %(levelname)s %(message)s') | |
| # No need gpu for model export | |
| os.environ['CUDA_VISIBLE_DEVICES'] = '-1' | |
| with open(args.config, 'r') as fin: | |
| configs = yaml.load(fin, Loader=yaml.FullLoader) | |
| model, configs = init_model(args, configs) | |
| model.eval() | |
| print(model) | |
| # Export jit torch script model | |
| if args.output_file: | |
| script_model = torch.jit.script(model) | |
| script_model.save(args.output_file) | |
| print('Export model successfully, see {}'.format(args.output_file)) | |
| # Export quantized jit torch script model | |
| if args.output_quant_file: | |
| quantized_model = torch.quantization.quantize_dynamic( | |
| model, {torch.nn.Linear}, dtype=torch.qint8) | |
| print(quantized_model) | |
| script_quant_model = torch.jit.script(quantized_model) | |
| script_quant_model.save(args.output_quant_file) | |
| print('Export quantized model successfully, ' | |
| 'see {}'.format(args.output_quant_file)) | |
| if __name__ == '__main__': | |
| main() | |