mirror of
https://github.com/liuhaozhe6788/voice-cloning-collab.git
synced 2025-12-16 11:48:12 +01:00
42 lines
1.7 KiB
Python
42 lines
1.7 KiB
Python
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import argparse
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import os
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os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
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from pathlib import Path
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from toolbox import Toolbox
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from utils.argutils import print_args
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from utils.default_models import ensure_default_models
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(
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description="Runs the toolbox.",
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formatter_class=argparse.ArgumentDefaultsHelpFormatter
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)
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parser.add_argument("--run_id", type=str, default="20230609", help= \
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"Name for this model. By default, training outputs will be stored to saved_models/<run_id>/. If a model state "
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"from the same run ID was previously saved, the training will restart from there. Pass -f to overwrite saved "
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"states and restart from scratch.")
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parser.add_argument("-d", "--datasets_root", type=Path, help= \
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"Path to the directory containing your datasets. See toolbox/__init__.py for a list of "
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"supported datasets.", default=None)
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parser.add_argument("-m", "--models_dir", type=Path, default="saved_models",
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help="Directory containing all saved models")
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parser.add_argument("--cpu", action="store_true", help=\
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"If True, all inference will be done on CPU")
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parser.add_argument("--seed", type=int, default=None, help=\
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"Optional random number seed value to make toolbox deterministic.")
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args = parser.parse_args()
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arg_dict = vars(args)
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print_args(args, parser)
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# Hide GPUs from Pytorch to force CPU processing
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if arg_dict.pop("cpu"):
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os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
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# Remind the user to download pretrained models if needed
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ensure_default_models(args.run_id, args.models_dir)
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# Launch the toolbox
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Toolbox(**arg_dict)
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