File size: 2,564 Bytes
46cfe25
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
import torch
from onnxexport.model_onnx_speaker_mix import SynthesizerTrn
import utils

def main(HubertExport, NetExport):
    path = "SummerPockets"
    if NetExport:
        device = torch.device("cpu")
        hps = utils.get_hparams_from_file(f"checkpoints/{path}/config.json")
        SVCVITS = SynthesizerTrn(
            hps.data.filter_length // 2 + 1,
            hps.train.segment_size // hps.data.hop_length,
            **hps.model)
        _ = utils.load_checkpoint(f"checkpoints/{path}/model.pth", SVCVITS, None)
        _ = SVCVITS.eval().to(device)
        for i in SVCVITS.parameters():
            i.requires_grad = False
        test_hidden_unit = torch.rand(1, 10, SVCVITS.gin_channels)
        test_pitch = torch.rand(1, 10)
        test_mel2ph = torch.LongTensor([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]).unsqueeze(0)
        test_uv = torch.ones(1, 10, dtype=torch.float32)
        test_noise = torch.randn(1, 192, 10)

        export_mix = True

        test_sid = torch.LongTensor([0])
        spk_mix = []
        if export_mix:
            n_spk = len(hps.spk)
            for i in range(n_spk):
                spk_mix.append(1.0/float(n_spk))
            test_sid = torch.tensor(spk_mix)
            SVCVITS.export_chara_mix(n_spk)
            test_sid = test_sid.unsqueeze(0)
            test_sid = test_sid.repeat(10, 1)
        
        input_names = ["c", "f0", "mel2ph", "uv", "noise", "sid"]
        output_names = ["audio", ]
        SVCVITS.eval()

        torch.onnx.export(SVCVITS,
                          (
                              test_hidden_unit.to(device),
                              test_pitch.to(device),
                              test_mel2ph.to(device),
                              test_uv.to(device),
                              test_noise.to(device),
                              test_sid.to(device)
                          ),
                          f"checkpoints/{path}/model.onnx",
                          dynamic_axes={
                              "c": [0, 1],
                              "f0": [1],
                              "mel2ph": [1],
                              "uv": [1],
                              "noise": [2],
                              "sid":[0]
                          },
                          do_constant_folding=False,
                          opset_version=16,
                          verbose=False,
                          input_names=input_names,
                          output_names=output_names)


if __name__ == '__main__':
    main(False, True)