NVIDIA GeForce RTX 5080 with CUDA capability sm_120 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90.
If you want to use the NVIDIA GeForce RTX 5080 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/
Traceback (most recent call last):
File "train_reflow.py", line 78, in
train(args, initial_global_step, model, optimizer, scheduler, vocoder, loader_train, loader_valid)
File "F:\So-VITS-SVC\DDSP-barbara-6.1\reflow\solver.py", line 232, in train
ddsp_loss, reflow_loss=model(data['units'], data['f0'], data['volume'], data['spk_id'],
File "F:\So-VITS-SVC\DDSP-barbara-6.1\env\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "F:\So-VITS-SVC\DDSP-barbara-6.1\env\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
File "F:\So-VITS-SVC\DDSP-barbara-6.1\reflow\vocoder.py", line 195, in forward
ddsp_wav, hidden = self.ddsp_model(units, f0, volume, spk_id=spk_id, spk_mix_dict=spk_mix_dict, aug_shift=aug_shift, infer=infer)
File "F:\So-VITS-SVC\DDSP-barbara-6.1\env\lib\site-packages\torch\nn\modules\module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "F:\So-VITS-SVC\DDSP-barbara-6.1\env\lib\site-packages\torch\nn\modules\module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
File "F:\So-VITS-SVC\DDSP-barbara-6.1\ddsp\vocoder.py", line 535, in forward
combtooth = self.fast_source_gen(f0_frames)
File "F:\So-VITS-SVC\DDSP-barbara-6.1\ddsp\vocoder.py", line 515, in fast_source_gen
n = torch.arange(self.block_size, device=f0_frames.device)
RuntimeError: CUDA error: no kernel image is available for execution on the device
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.
Hi all! Update from our NVIDIA team.
To use PyTorch for Linux x86_64 and Linux SBSA on NVIDIA 5080, 5090 Blackwell RTX GPUs use the latest nightly builds, or the command below.
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128
Stay tuned for further updates
Is it only available on Linux? Then I still need to wait for the Windows version......
@ldxldx123 Windows version now available...
Update from our NVIDIA team.
To use PyTorch for Windows on NVIDIA 5080, 5090 Blackwell RTX GPUs use the latest nightly builds, or the command below.
pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128
Let us know if you have any questions, Thanks!
yxlllc
