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https://github.com/liuhaozhe6788/voice-cloning-collab.git
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56 lines
2.9 KiB
Python
56 lines
2.9 KiB
Python
import argparse
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from pathlib import Path
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from utils.argutils import print_args
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from vocoder.train import train
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="Trains the vocoder from the synthesizer audios and the GTA synthesized mels, "
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"or ground truth mels.",
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formatter_class=argparse.ArgumentDefaultsHelpFormatter
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)
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parser.add_argument("run_id", type=str, 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("datasets_root", type=Path, help= \
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"Path to the directory containing your SV2TTS directory. Specifying --syn_dir or --voc_dir "
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"will take priority over this argument.")
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parser.add_argument("--syn_dir", type=Path, default=argparse.SUPPRESS, help= \
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"Path to the synthesizer directory that contains the ground truth mel spectrograms, "
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"the wavs and the embeds. Defaults to <datasets_root>/SV2TTS/synthesizer/.")
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parser.add_argument("--voc_dir", type=Path, default=argparse.SUPPRESS, help= \
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"Path to the vocoder directory that contains the GTA synthesized mel spectrograms. "
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"Defaults to <datasets_root>/SV2TTS/vocoder/. Unused if --ground_truth is passed.")
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parser.add_argument("-m", "--models_dir", type=Path, default="saved_models", help=\
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"Path to the directory that will contain the saved model weights, as well as backups "
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"of those weights and wavs generated during training.")
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parser.add_argument("-g", "--ground_truth", action="store_true", help= \
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"Train on ground truth spectrograms (<datasets_root>/SV2TTS/synthesizer/mels).")
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parser.add_argument("-s", "--save_every", type=int, default=100, help= \
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"Number of steps between updates of the model on the disk. Set to 0 to never save the "
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"model.")
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parser.add_argument("-b", "--backup_every", type=int, default=10000, help= \
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"Number of steps between backups of the model. Set to 0 to never make backups of the "
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"model.")
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parser.add_argument("-f", "--force_restart", action="store_true", help= \
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"Do not load any saved model and restart from scratch.")
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parser.add_argument("--use_tb", action="store_true", help= \
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"Use Tensorboard support")
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args = parser.parse_args()
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# Process the arguments
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if not hasattr(args, "syn_dir"):
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args.syn_dir = args.datasets_root / "SV2TTS" / "synthesizer"
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if not hasattr(args, "voc_dir"):
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args.voc_dir = args.datasets_root / "SV2TTS" / "vocoder"
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del args.datasets_root
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args.models_dir.mkdir(exist_ok=True)
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# Run the training
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print_args(args, parser)
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train(**vars(args))
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