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https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
synced 2026-02-20 19:30:49 +00:00
768VecOnnxExport (#328)
* Delete export_onnx.py * Delete export_onnx_old.py * Delete models_onnx_moess.py * Support 768 Vec * Add files via upload * Support 768 Vec Support 768 Vec * Support 768 Vec Onnx Export Support 768 Vec Onnx Export
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@@ -1,5 +1,4 @@
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from infer_pack.models_onnx_moess import SynthesizerTrnMs256NSFsidM
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from infer_pack.models_onnx import SynthesizerTrnMs256NSFsidO
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from infer_pack.models_onnx import SynthesizerTrnMsNSFsidM
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import torch
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if __name__ == "__main__":
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@@ -21,65 +20,36 @@ if __name__ == "__main__":
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device = "cpu" # 导出时设备(不影响使用模型)
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if MoeVS:
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net_g = SynthesizerTrnMs256NSFsidM(
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*cpt["config"], is_half=False
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) # fp32导出(C++要支持fp16必须手动将内存重新排列所以暂时不用fp16)
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net_g.load_state_dict(cpt["weight"], strict=False)
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input_names = ["phone", "phone_lengths", "pitch", "pitchf", "ds", "rnd"]
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output_names = [
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"audio",
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]
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torch.onnx.export(
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net_g,
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(
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test_phone.to(device),
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test_phone_lengths.to(device),
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test_pitch.to(device),
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test_pitchf.to(device),
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test_ds.to(device),
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test_rnd.to(device),
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),
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ExportedPath,
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dynamic_axes={
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"phone": [1],
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"pitch": [1],
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"pitchf": [1],
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"rnd": [2],
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},
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do_constant_folding=False,
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opset_version=16,
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verbose=False,
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input_names=input_names,
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output_names=output_names,
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)
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else:
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net_g = SynthesizerTrnMs256NSFsidO(
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*cpt["config"], is_half=False
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) # fp32导出(C++要支持fp16必须手动将内存重新排列所以暂时不用fp16)
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net_g.load_state_dict(cpt["weight"], strict=False)
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input_names = ["phone", "phone_lengths", "pitch", "pitchf", "ds"]
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output_names = [
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"audio",
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]
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torch.onnx.export(
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net_g,
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(
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test_phone.to(device),
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test_phone_lengths.to(device),
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test_pitch.to(device),
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test_pitchf.to(device),
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test_ds.to(device),
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),
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ExportedPath,
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dynamic_axes={
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"phone": [1],
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"pitch": [1],
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"pitchf": [1],
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},
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do_constant_folding=False,
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opset_version=16,
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verbose=False,
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input_names=input_names,
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output_names=output_names,
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)
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net_g = SynthesizerTrnMsNSFsidM(
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*cpt["config"], is_half=False
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) # fp32导出(C++要支持fp16必须手动将内存重新排列所以暂时不用fp16)
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net_g.load_state_dict(cpt["weight"], strict=False)
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input_names = ["phone", "phone_lengths", "pitch", "pitchf", "ds", "rnd"]
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output_names = [
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"audio",
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]
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# net_g.construct_spkmixmap(n_speaker) 多角色混合轨道导出
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torch.onnx.export(
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net_g,
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(
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test_phone.to(device),
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test_phone_lengths.to(device),
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test_pitch.to(device),
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test_pitchf.to(device),
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test_ds.to(device),
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test_rnd.to(device),
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),
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ExportedPath,
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dynamic_axes={
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"phone": [1],
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"pitch": [1],
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"pitchf": [1],
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"rnd": [2],
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},
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do_constant_folding=False,
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opset_version=16,
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verbose=False,
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input_names=input_names,
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output_names=output_names,
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)
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