Retrieval-based-Voice-Conve.../export_onnx_old.py

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from infer_pack.models_onnx_moess import SynthesizerTrnMs256NSFsidM
import torch
person = "Shiroha/shiroha.pth"
exported_path = "model.onnx"
cpt = torch.load(person, map_location="cpu")
cpt["config"][-3] = cpt["weight"]["emb_g.weight"].shape[0] # n_spk
print(*cpt["config"])
net_g = SynthesizerTrnMs256NSFsidM(*cpt["config"], is_half=False)
net_g.load_state_dict(cpt["weight"], strict=False)
test_phone = torch.rand(1, 200, 256)
test_phone_lengths = torch.tensor([200]).long()
test_pitch = torch.randint(size=(1, 200), low=5, high=255)
test_pitchf = torch.rand(1, 200)
test_ds = torch.LongTensor([0])
test_rnd = torch.rand(1, 192, 200)
input_names = ["phone", "phone_lengths", "pitch", "pitchf", "ds", "rnd"]
output_names = [
"audio",
]
device = "cpu"
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),
),
exported_path,
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,
)