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import argparse |
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from argparse import ArgumentParser |
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import os |
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from models.codec.facodec.facodec_inference import FAcodecInference |
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from utils.util import load_config |
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import torch |
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def build_inference(args, cfg): |
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supported_inference = { |
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"FAcodec": FAcodecInference, |
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} |
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inference_class = supported_inference[cfg.model_type] |
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inference = inference_class(args, cfg) |
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return inference |
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def cuda_relevant(deterministic=False): |
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torch.cuda.empty_cache() |
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torch.backends.cuda.matmul.allow_tf32 = True |
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torch.backends.cudnn.enabled = True |
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torch.backends.cudnn.allow_tf32 = True |
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torch.backends.cudnn.deterministic = deterministic |
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torch.backends.cudnn.benchmark = not deterministic |
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torch.use_deterministic_algorithms(deterministic) |
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def build_parser(): |
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parser = argparse.ArgumentParser() |
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parser.add_argument( |
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"--config", |
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type=str, |
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required=True, |
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help="JSON/YAML file for configurations.", |
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) |
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parser.add_argument( |
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"--checkpoint_path", |
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type=str, |
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default=None, |
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help="Acoustic model checkpoint directory. If a directory is given, " |
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"search for the latest checkpoint dir in the directory. If a specific " |
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"checkpoint dir is given, directly load the checkpoint.", |
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) |
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parser.add_argument( |
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"--source", |
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type=str, |
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required=True, |
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help="Path to the source audio file", |
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) |
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parser.add_argument( |
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"--reference", |
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type=str, |
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default=None, |
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help="Path to the reference audio file, passing an", |
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) |
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parser.add_argument( |
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"--output_dir", |
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type=str, |
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default=None, |
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help="Output dir for saving generated results", |
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) |
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return parser |
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def main(): |
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parser = build_parser() |
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args = parser.parse_args() |
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print(args) |
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cfg = load_config(args.config) |
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cuda_relevant() |
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inferencer = build_inference(args, cfg) |
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_ = inferencer.inference(args.source, args.output_dir) |
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if args.reference is not None: |
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_ = inferencer.voice_conversion(args.source, args.reference, args.output_dir) |
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if __name__ == "__main__": |
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main() |
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