44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
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from infer_pack.models_onnx import SynthesizerTrnMs256NSFsid
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import torch
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person = "Shiroha/shiroha.pth"
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exported_path = "model.onnx"
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cpt = torch.load(person, map_location="cpu")
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cpt["config"][-3]=cpt["weight"]["emb_g.weight"].shape[0]#n_spk
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print(*cpt["config"])
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net_g = SynthesizerTrnMs256NSFsid(*cpt["config"], is_half=False)
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net_g.load_state_dict(cpt["weight"], strict=False)
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test_phone = torch.rand(1, 200, 256)
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test_phone_lengths = torch.tensor([200]).long()
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test_pitch = torch.randint(size=(1 ,200),low=5,high=255)
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test_pitchf = torch.rand(1, 200)
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test_ds = torch.LongTensor([0])
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test_rnd = torch.rand(1, 192, 200)
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input_names = ["phone", "phone_lengths", "pitch", "pitchf", "ds", "rnd"]
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output_names = ["audio", ]
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device="cpu"
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torch.onnx.export(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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exported_path,
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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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