zsyzzsoft
commented
2 years ago Maybe you need to use an earlier PyTorch version like 1.4.0...
Open fancyshirt opened 2 years ago
zsyzzsoft
commented
2 years ago Maybe you need to use an earlier PyTorch version like 1.4.0...
I'm trying to create a new model by myself by using the following command:
And I ran into the Error:
return _VF.meshgrid(tensors, kwargs) # type: ignore[attr-defined] Traceback (most recent call last): File "F:\USB Backup\Clemson University\Course\Artificial Intellengent\Project\data-efficient-gans-master\data-efficient-gans-master\DiffAugment-stylegan2-pytorch\train.py", line 554, in main() # pylint: disable=no-value-for-parameter File "C:\Users\Dinner.conda\envs\pytorch\lib\site-packages\click\core.py", line 1130, in call return self.main(args, kwargs) File "C:\Users\Dinner.conda\envs\pytorch\lib\site-packages\click\core.py", line 1055, in main rv = self.invoke(ctx) File "C:\Users\Dinner.conda\envs\pytorch\lib\site-packages\click\core.py", line 1404, in invoke return ctx.invoke(self.callback, ctx.params) File "C:\Users\Dinner.conda\envs\pytorch\lib\site-packages\click\core.py", line 760, in invoke return __callback(args, kwargs) File "C:\Users\Dinner.conda\envs\pytorch\lib\site-packages\click\decorators.py", line 26, in new_func return f(get_current_context(), args, kwargs) File "F:\USB Backup\Clemson University\Course\Artificial Intellengent\Project\data-efficient-gans-master\data-efficient-gans-master\DiffAugment-stylegan2-pytorch\train.py", line 547, in main subprocess_fn(rank=0, args=args, temp_dir=temp_dir) File "F:\USB Backup\Clemson University\Course\Artificial Intellengent\Project\data-efficient-gans-master\data-efficient-gans-master\DiffAugment-stylegan2-pytorch\train.py", line 398, in subprocess_fn training_loop.training_loop(rank=rank, args) File "F:\USB Backup\Clemson University\Course\Artificial Intellengent\Project\data-efficient-gans-master\data-efficient-gans-master\DiffAugment-stylegan2-pytorch\training\training_loop.py", line 284, in training_loop loss.accumulate_gradients(phase=phase.name, real_img=real_img, real_c=real_c, gen_z=gen_z, gen_c=gen_c, sync=sync, gain=gain) File "F:\USB Backup\Clemson University\Course\Artificial Intellengent\Project\data-efficient-gans-master\data-efficient-gans-master\DiffAugment-stylegan2-pytorch\training\loss.py", line 79, in accumulate_gradients loss_Gmain.mean().mul(gain).backward() File "C:\Users\Dinner.conda\envs\pytorch\lib\site-packages\torch_tensor.py", line 363, in backward torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs) File "C:\Users\Dinner.conda\envs\pytorch\lib\site-packages\torch\autograd__init__.py", line 173, in backward Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass File "C:\Users\Dinner.conda\envs\pytorch\lib\site-packages\torch\autograd\function.py", line 253, in apply return user_fn(self, args) File "F:\USB Backup\Clemson University\Course\Artificial Intellengent\Project\data-efficient-gans-master\data-efficient-gans-master\DiffAugment-stylegan2-pytorch\torch_utils\ops\conv2d_gradfix.py", line 133, in backward grad_weight = Conv2dGradWeight.apply(grad_output, input) File "F:\USB Backup\Clemson University\Course\Artificial Intellengent\Project\data-efficient-gans-master\data-efficient-gans-master\DiffAugment-stylegan2-pytorch\torch_utils\ops\conv2d_gradfix.py", line 145, in forward op = torch._C._jit_get_operation('aten::cudnn_convolution_backward_weight' if not transpose else 'aten::cudnn_convolution_transpose_backward_weight') RuntimeError: No such operator aten::cudnn_convolution_backward_weight
My Cuda version: nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2021 NVIDIA Corporation Built on Sun_Mar_21_19:24:09_Pacific_Daylight_Time_2021 Cuda compilation tools, release 11.3, V11.3.58 Build cuda_11.3.r11.3/compiler.29745058_0
Pytorch version: 1.11.0
How should I fix it?