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Hiroshiba
commented
Dec 1, 2024
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フォーマッターが働いてしまったので空行が多いです。
?w=1を付けると差が見やすいかも。
Hiroshiba
commented
Dec 1, 2024
| Python 3.9.19 で開発しました。 3.9 台なら動くと思います。 | ||
| Python 3.11.9 で開発しました。 3.11 台なら動くと思います。 |
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Files not reviewed (4)
- vv_core_inference/make_yukarin_sa_forwarder.py: Evaluated as low risk
- vv_core_inference/make_yukarin_sosf_forwarder.py: Evaluated as low risk
- vv_core_inference/make_yukarin_sosoa_forwarder.py: Evaluated as low risk
- vv_core_inference/utility.py: Evaluated as low risk
Hiroshiba
commented
Dec 1, 2024
| @@ -120,7 +120,6 @@ def convert_intonation(model_dir: Path, device: str, offset: int, working_dir: P | |||
| "end_accent_phrase_list", | |||
| "speaker_id", | |||
| ], | |||
| example_outputs=output, | |||
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pytorchのバージョンが上がってこの引数がなくなっていました。
Hiroshiba
commented
Dec 1, 2024
pyproject.toml
Outdated
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yukarin_sosoaのバージョンを上げて、伴ってtorchやnumpyやpythonのバージョンを上げています。
_sと_saはtorchのバージョンはそのままですが、ちょっと変わったのでついでにアプデしています。
Hiroshiba
commented
Dec 1, 2024
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なぜかtorch.jit.scriptが@torch.no_grad()でエラーを吐いたので、場所を移しました。
Hiroshiba
commented
Dec 1, 2024
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| from torch.onnx.symbolic_helper import _onnx_main_opset, _onnx_stable_opsets | ||
| OPSET = _onnx_stable_opsets[-1] | ||
| from torch.onnx import _constants | ||
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| OPSET = _constants.ONNX_DEFAULT_OPSET | ||
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たぶん大丈夫だと思うのでマージします 🙇 |
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sosoaの学習が遅かったのでtorch.compile等のリファクタリングをしたところ、pytorchのバージョンが上がってこっちの変更も必要になってしまいました。
model.zipも新しくアップロードしました。ストリーミングタスクの方は0.0.1だと思うので、別であることがわかるように0.0.2としてアップロードしました。
https://github.com/Hiroshiba/vv_core_inference/releases/tag/0.0.2
↓変更点まとめ