RuntimeError: Given groups=1, weight of size [192, 768, 5], expected input[1, 256, 725] to have 768

[zutyhcx]

Describe the bug

I trained the model by Google Colab ,but it can't infer by my computer.

But it not occurs last time.

Traceback (most recent call last): File "inference_main.py", line 101, in main() File "inference_main.py", line 85, in main out_audio, out_sr = svc_model.infer(spk, tran, raw_path, File "C:\python\vits4.0\inference\infer_tool.py", line 177, in infer audio = self.net_g_ms.infer(c, f0=f0, g=sid, uv=uv, predict_f0=auto_predict_f0, noice_scale=noice_scale)[0,0].data.float() File "C:\python\vits4.0\models.py", line 409, in infer x = self.pre(c) * x_mask + self.emb_uv(uv.long()).transpose(1,2) File "C:\python\vits4.0\python38\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl return forward_call(*input, **kwargs) File "C:\python\vits4.0\python38\lib\site-packages\torch\nn\modules\conv.py", line 313, in forward return self._conv_forward(input, self.weight, self.bias) File "C:\python\vits4.0\python38\lib\site-packages\torch\nn\modules\conv.py", line 309, in _conv_forward return F.conv1d(input, weight, bias, self.stride, RuntimeError: Given groups=1, weight of size [192, 768, 5], expected input[1, 256, 1803] to have 768 channels, but got 256 channels instead

To Reproduce

I found that the model has changed.

Additional context

No response

Version

4.0.1

Platform

Windows 10

Code of Conduct

• [X] I agree to follow this project's Code of Conduct.

No Duplicate

• [X] I have checked existing issues to avoid duplicates.

[devcooch]

a dup of #657

[KatieBelli]

I have the same error but when I want to train.

[hotpussy]

vec768

[34j]

Duplicate of #253

[hotpussy]

这是来自QQ邮箱的假期自动回复邮件。   您好，我最近正在休假中，无法亲自回复您的邮件。我将在假期结束后，尽快给您回复。

[ZhiwenDeng-dev]

I have the same error，pls help

Traceback (most recent call last): File "C:\Users\Edwin\AppData\Local\Programs\Python\Python310\lib\runpy.py", line 196, in _run_module_as_main return _run_code(code, main_globals, None, File "C:\Users\Edwin\AppData\Local\Programs\Python\Python310\lib\runpy.py", line 86, in run_code exec(code, run_globals) File "E:\dev\so-vits-svc-fork\easy-installation\venv\Scripts\svcf.exe_main.py", line 7, in File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\click\core.py", line 1130, in call return self.main(*args, **kwargs) File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\click\core.py", line 1055, in main rv = self.invoke(ctx) File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\click\core.py", line 1657, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\click\core.py", line 1404, in invoke return ctx.invoke(self.callback, **ctx.params) File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\click\core.py", line 760, in invoke return _callback(*args, **kwargs) File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\so_vits_svc_fork_main.py", line 438, in vc realtime( File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\so_vits_svc_fork\inference\main.py", line 208, in realtime svc_model.infer( File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\so_vits_svc_fork\inference\core.py", line 228, in infer audio = self.net_g.infer( File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\so_vits_svc_fork\modules\synthesizers.py", line 213, in infer x = self.pre(c) * x_mask + self.emb_uv(uv.long()).transpose(1, 2) File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\torch\nn\modules\conv.py", line 313, in forward return self._conv_forward(input, self.weight, self.bias) File "E:\dev\so-vits-svc-fork\easy-installation\venv\lib\site-packages\torch\nn\modules\conv.py", line 309, in _conv_forward return F.conv1d(input, weight, bias, self.stride, RuntimeError: Given groups=1, weight of size [192, 768, 5], expected input[1, 256, 86] to have 768 channels, but got 256 channels instead

[laurentbenaroya]

Solved here

so-vits-svc produce model, can not in use with so-vits-svc-fork #836 Still get the warning : UserWarning: Shape mismatch: ['emb_g.weight: torch.Size([1, 256]) -> torch.Size([1, 768])', 'pre.weight: torch.Size([192, 256, 5]) -> torch.Size([192, 768, 5])', 'dec.cond.weight: torch.Size([512, 256, 1]) -> torch.Size([512, 768, 1])', 'enc_q.enc.cond_layer.weight_v: torch.Size([6144, 256, 1]) -> torch.Size([6144, 768, 1])', 'flow.flows.0.enc.cond_layer.weight_v: torch.Size([1536, 256, 1]) -> torch.Size([1536, 768, 1])', 'flow.flows.2.enc.cond_layer.weight_v: torch.Size([1536, 256, 1]) -> torch.Size([1536, 768, 1])', 'flow.flows.4.enc.cond_layer.weight_v: torch.Size([1536, 256, 1]) -> torch.Size([1536, 768, 1])', 'flow.flows.6.enc.cond_layer.weight_v: torch.Size([1536, 256, 1]) -> torch.Size([1536, 768, 1])', 'f0_decoder.cond.weight: torch.Size([192, 256, 1]) -> torch.Size([192, 768, 1])']

[hotpussy]

这是来自QQ邮箱的假期自动回复邮件。   您好，我最近正在休假中，无法亲自回复您的邮件。我将在假期结束后，尽快给您回复。