| import torch |
| from onnxexport.model_onnx import SynthesizerTrn |
| import utils |
|
|
| def main(NetExport): |
| path = "SoVits4.0" |
| 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, 256) |
| 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) |
| test_sid = torch.LongTensor([0]) |
| input_names = ["c", "f0", "mel2ph", "uv", "noise", "sid"] |
| output_names = ["audio", ] |
| |
| 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], |
| }, |
| do_constant_folding=False, |
| opset_version=16, |
| verbose=False, |
| input_names=input_names, |
| output_names=output_names) |
|
|
|
|
| if __name__ == '__main__': |
| main(True) |
|
|
