| | |
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| | | import json |
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| | | from typing import Union, Dict |
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| | | from pathlib import Path |
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| | | from typeguard import check_argument_types |
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| | | |
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| | | import os |
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| | | import logging |
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| | |
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| | | from funasr.export.models import get_model |
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| | | import numpy as np |
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| | | import random |
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| | | from funasr.utils.types import str2bool |
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| | | from funasr.utils.types import str2bool, str2triple_str |
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| | | # torch_version = float(".".join(torch.__version__.split(".")[:2])) |
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| | | # assert torch_version > 1.9 |
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| | | |
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| | |
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| | | calib_num: int = 200, |
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| | | model_revision: str = None, |
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| | | ): |
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| | | assert check_argument_types() |
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| | | self.set_all_random_seed(0) |
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| | | |
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| | | self.cache_dir = cache_dir |
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| | |
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| | | config, model_file, cmvn_file, 'cpu' |
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| | | ) |
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| | | self.frontend = model.frontend |
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| | | self.export_config["feats_dim"] = 560 |
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| | | elif mode.startswith('offline'): |
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| | | from funasr.tasks.vad import VADTask |
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| | | config = os.path.join(model_dir, 'vad.yaml') |
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| | |
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| | | if __name__ == '__main__': |
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| | | import argparse |
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| | | parser = argparse.ArgumentParser() |
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| | | parser.add_argument('--model-name', type=str, required=True) |
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| | | # parser.add_argument('--model-name', type=str, required=True) |
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| | | parser.add_argument('--model-name', type=str, action="append", required=True, default=[]) |
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| | | parser.add_argument('--export-dir', type=str, required=True) |
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| | | parser.add_argument('--type', type=str, default='onnx', help='["onnx", "torch"]') |
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| | | parser.add_argument('--device', type=str, default='cpu', help='["cpu", "cuda"]') |
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| | |
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| | | calib_num=args.calib_num, |
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| | | model_revision=args.model_revision, |
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| | | ) |
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| | | export_model.export(args.model_name) |
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| | | for model_name in args.model_name: |
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| | | print("export model: {}".format(model_name)) |
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| | | export_model.export(model_name) |
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