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| import torch | |
| from infer.lib.infer_pack.models_onnx import SynthesizerTrnMsNSFsidM | |
| if __name__ == "__main__": | |
| MoeVS = True # 模型是否为MoeVoiceStudio（原MoeSS）使用 | |
| ModelPath = "Shiroha/shiroha.pth" # 模型路径 | |
| ExportedPath = "model.onnx" # 输出路径 | |
| hidden_channels = 256 # hidden_channels，为768Vec做准备 | |
| cpt = torch.load(ModelPath, map_location="cpu") | |
| cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0] # n_spk | |
| print(*cpt["config"]) | |
| test_phone = torch.rand(1, 200, hidden_channels) # hidden unit | |
| test_phone_lengths = torch.tensor([200]).long() # hidden unit 长度（貌似没啥用） | |
| test_pitch = torch.randint(size=(1, 200), low=5, high=255) # 基频（单位赫兹） | |
| test_pitchf = torch.rand(1, 200) # nsf基频 | |
| test_ds = torch.LongTensor([0]) # 说话人ID | |
| test_rnd = torch.rand(1, 192, 200) # 噪声（加入随机因子） | |
| device = "cpu" # 导出时设备（不影响使用模型） | |
| net_g = SynthesizerTrnMsNSFsidM( | |
| *cpt["config"], is_half=False | |
| ) # 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） | |
| net_g.load_state_dict(cpt["weight"], strict=False) | |
| input_names = ["phone", "phone_lengths", "pitch", "pitchf", "ds", "rnd"] | |
| output_names = [ | |
| "audio", | |
| ] | |
| # net_g.construct_spkmixmap(n_speaker) 多角色混合轨道导出 | |
| torch.onnx.export( | |
| net_g, | |
| ( | |
| test_phone.to(device), | |
| test_phone_lengths.to(device), | |
| test_pitch.to(device), | |
| test_pitchf.to(device), | |
| test_ds.to(device), | |
| test_rnd.to(device), | |
| ), | |
| ExportedPath, | |
| dynamic_axes={ | |
| "phone": [1], | |
| "pitch": [1], | |
| "pitchf": [1], | |
| "rnd": [2], | |
| }, | |
| do_constant_folding=False, | |
| opset_version=16, | |
| verbose=False, | |
| input_names=input_names, | |
| output_names=output_names, | |
| ) | |