from infer_pack.models_onnx import SynthesizerTrnMs256NSFsid 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 = SynthesizerTrnMs256NSFsid(*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, )