Fabio
c36510c21e
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55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
#!/usr/bin/env python3
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"""Convert OuteTTS 1.0's official IBM DAC checkpoint to safetensors.
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The official OuteTTS runtime loads a trusted PyTorch checkpoint. audio.cpp uses
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the resulting plain tensor source for both native safetensors loading and GGUF
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packing; no Python or pickle loader is needed at inference time.
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"""
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from __future__ import annotations
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import argparse
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from pathlib import Path
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import dac
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from safetensors.torch import save_file
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def main() -> None:
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parser = argparse.ArgumentParser()
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parser.add_argument("input", type=Path, help="weights_24khz_1.5kbps_v1.0.pth")
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parser.add_argument("output", type=Path, help="output model.safetensors")
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parser.add_argument("--overwrite", action="store_true")
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args = parser.parse_args()
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if args.output.exists() and not args.overwrite:
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raise SystemExit(f"output exists (pass --overwrite): {args.output}")
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model = dac.DAC.load(str(args.input)).cpu().eval()
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if model.sample_rate != 24000 or model.hop_length != 320:
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raise RuntimeError(
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f"expected OuteTTS DAC at 24 kHz with hop 320, got "
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f"{model.sample_rate} Hz / hop {model.hop_length}"
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)
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if model.n_codebooks != 2 or model.codebook_size != 1024:
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raise RuntimeError(
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f"expected two 1024-entry codebooks, got "
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f"{model.n_codebooks} x {model.codebook_size}"
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)
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tensors = {name: tensor.detach().contiguous() for name, tensor in model.state_dict().items()}
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args.output.parent.mkdir(parents=True, exist_ok=True)
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save_file(
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tensors,
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str(args.output),
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metadata={
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"format": "pt",
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"source": "ibm-research/DAC.speech.v1.0",
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"checkpoint": args.input.name,
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},
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)
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print(f"wrote {args.output} ({len(tensors)} tensors)")
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if __name__ == "__main__":
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main()
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