59d118c256
- generate samples for https://k2-fsa.github.io/sherpa/onnx/tts/all/ - provide int8 model for kokoro v0.19 kokoro-int8-en-v0_19.tar.bz2
78 lines
1.9 KiB
Python
Executable File
78 lines
1.9 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2025 Xiaomi Corp. (authors: Fangjun Kuang)
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import argparse
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import onnx
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import torch
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from generate_voices_bin import speaker2id
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def get_args():
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--model", type=str, required=True, help="input and output onnx model"
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)
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return parser.parse_args()
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def main():
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args = get_args()
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print(args.model)
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model = onnx.load(args.model)
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style = torch.load(
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"./kLegacy/v0.19/voices/af.pt", weights_only=True, map_location="cpu"
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)
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speaker2id_str = ""
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id2speaker_str = ""
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sep = ""
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for s, i in speaker2id.items():
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speaker2id_str += f"{sep}{s}->{i}"
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id2speaker_str += f"{sep}{i}->{s}"
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sep = ","
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meta_data = {
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"model_type": "kokoro",
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"language": "English",
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"has_espeak": 1,
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"sample_rate": 24000,
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"version": 1,
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"voice": "en-us",
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"style_dim": ",".join(map(str, style.shape)),
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"n_speakers": len(speaker2id),
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"speaker2id": speaker2id_str,
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"id2speaker": id2speaker_str,
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"speaker_names": ",".join(map(str, speaker2id.keys())),
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"model_url": "https://huggingface.co/hexgrad/kLegacy/",
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"see_also": "https://huggingface.co/spaces/hexgrad/Kokoro-TTS",
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"maintainer": "k2-fsa",
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"comment": "This is kokoro v0.19 and supports only English",
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}
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print(model.metadata_props)
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while len(model.metadata_props):
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model.metadata_props.pop()
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for key, value in meta_data.items():
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meta = model.metadata_props.add()
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meta.key = key
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meta.value = str(value)
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print("--------------------")
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print(model.metadata_props)
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onnx.save(model, args.model)
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print(f"Please see {args.model}, ./voices.bin, and ./tokens.txt")
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if __name__ == "__main__":
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main()
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