mirror of
https://github.com/storytold/storyteller-ml.git
synced 2026-10-17 00:23:14 +00:00
Paul Sajna
f86b44d8fc
* 48KHz softvc * add some notes * almost forgot the inference script * fix readme link * requirements.txt
61 lines
1.8 KiB
Python
61 lines
1.8 KiB
Python
from pathlib import Path
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import numpy as np
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import argparse
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import torch
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import torchaudio
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from tqdm import tqdm
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from torch.nn.modules.utils import consume_prefix_in_state_dict_if_present
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from hifigan.generator import HifiganGenerator
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def generate(args):
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print("Loading checkpoint")
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#model_name = f"hifigan_hubert_{args.model}" if args.model != "base" else "hifigan"
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#hifigan = torch.hub.load("bshall/hifigan:main", model_name).cuda()
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checkpoint = torch.load("exp/vctk/model-66000.pt")["generator"]["model"]
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consume_prefix_in_state_dict_if_present(checkpoint, "module.")
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hifigan = HifiganGenerator()
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hifigan.load_state_dict(checkpoint)
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hifigan.remove_weight_norm()
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hifigan.eval()
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hifigan.cuda()
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print(f"Generating audio from {args.in_dir}")
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for path in tqdm(list(args.in_dir.rglob("*.npy"))):
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mel = torch.from_numpy(np.load(path))
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mel = mel.unsqueeze(0).cuda()
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wav, sr = hifigan.generate(mel)
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wav = wav.squeeze(0).cpu()
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out_path = args.out_dir / path.relative_to(args.in_dir)
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out_path.parent.mkdir(exist_ok=True, parents=True)
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torchaudio.save(out_path.with_suffix(".wav"), wav, 48000)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="Generate audio for a directory of mel-spectrogams using HiFi-GAN."
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)
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parser.add_argument(
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"model",
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help="available models (HuBERT-Soft, HuBERT-Discrete, or Base).",
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choices=["soft", "discrete", "base"],
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)
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parser.add_argument(
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"in_dir",
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metavar="in-dir",
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help="path to input directory containing the mel-spectrograms.",
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type=Path,
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)
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parser.add_argument(
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"out_dir",
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metavar="out-dir",
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help="path to output directory.",
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type=Path,
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)
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args = parser.parse_args()
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generate(args)
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