module 'torch' has no attribute 'cuda

It is lazily initialized, so you can How to fix "Attempted relative import in non-package" even with __init__.py, Equation alignment in aligned environment not working properly, Trying to understand how to get this basic Fourier Series. To learn more, see our tips on writing great answers. Easiest way would be just updating PyTorch to 0.4.0 or higher. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. return run(f'"{python}" -c "{code}"', desc, errdesc) Does ZnSO4 + H2 at high pressure reverses to Zn + H2SO4? raise RuntimeError(message) Hi, Sorry for the late response. We tried running your code.The issue seems to be with the quantized.Conv3d, instead you can use normal convolution Can we reopen this issue and maybe get a backport to 1.12? How do/should administrators estimate the cost of producing an online introductory mathematics class? rev2023.3.3.43278. Commit hash: 0cc0ee1 File "C:\ai\stable-diffusion-webui\launch.py", line 360, in What platforms do you use to access the UI ? torch.cuda.amptorch1.6torch1.4 1.7.1 I ran into this problem as well. I could fix this on the 1.12 branch, but will there be a 1.12.2 release? How do I check if an object has an attribute? What is the purpose of non-series Shimano components? and delete current Python and "venv" folder in WebUI's directory. You have to call the decorator as given in the docs and examples: Powered by Discourse, best viewed with JavaScript enabled, Older version of PyTorch: with torch.autocast('cuda'): AttributeError: module 'torch' has no attribute 'autocast'. In the __init__.py of the module named torch-sparse, it is so bizarre and confusing .And torch.__version__ == 1.8.0 , torch-sparse == 0.6.11. or can I please get some context of why this is occuring? Webimport torch.nn.utils.prune as prune device = torch.device("cuda" if torch.cuda.is_available() else "cpu") model = C3D(num_classes=2).to(device=device) I'm using Windows, conda environment, installed Pytorch-1.7.1, Torchvision-0.8.2, Cuda-Toolkit-11.0 > all compatible. to your account, Everything was working well, I then proceeded to update some extensions, and when i restarted stable, I got this error message, Already up to date. --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) in 1 get_ipython().system('pip3 install torch==1.2.0+cu92 torchvision==0.4.0+cu92 -f https://download.pytorch.org/whl/torch_stable.html') ----> 2 torch.is_cuda AttributeError: module 'torch' has no attribute 'is_cuda'. ERROR: Could not find a version that satisfies the requirement torch==1.13.1+cu117 (from versions: none) Thanks for contributing an answer to Stack Overflow! Steps to reproduce the problem. Later in the night i did the same and got the same error. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Well occasionally send you account related emails. cuDNN version: Could not collect vegan) just to try it, does this inconvenience the caterers and staff? Recovering from a blunder I made while emailing a professor, Linear regulator thermal information missing in datasheet, How to handle a hobby that makes income in US, Minimising the environmental effects of my dyson brain. Commit hash: 0cc0ee1 We tried running your code.The issue seems to be with the quantized.Conv3d, instead you can use normal convolution3d. You may re-send via your. Since this issue is not related to Intel Devcloud can we close the case? Why does Mister Mxyzptlk need to have a weakness in the comics? AC Op-amp integrator with DC Gain Control in LTspice. Did any DOS compatibility layers exist for any UNIX-like systems before DOS started to become outmoded? So for example when changing in the imported code: torch.tensor([1, 0, 0, 0, 1, 0], dtype=torch.float) to torch.FloatTensor([1,0,0,0,1,0]) it might still complain about torch.float even if the line then doesn't contain a torch.floatanymore (it even shows the new code in the traceback). Im running from torch.cuda.amp import GradScaler, autocast and got the error as in title. "After the incident", I started to be more careful not to trip over things. We tried running your code.The issue seems to be with the quantized.Conv3d, instead you can use normal convolution3d. For more complete information about compiler optimizations, see our Optimization Notice. For the Nozomi from Shinagawa to Osaka, say on a Saturday afternoon, would tickets/seats typically be available - or would you need to book? Command: "C:\ai\stable-diffusion-webui\venv\Scripts\python.exe" -c "import torch; assert torch.cuda.is_available(), 'Torch is not able to use GPU; add --skip-torch-cuda-test to COMMANDLINE_ARGS variable to disable this check'" NVIDIA doesnt develop, maintain, or support pytorch. NVIDIA most definitely does have a PyTorch team, but the PyTorch forums are still a great place to ask questions. [pip3] numpy==1.23.4 """, def __init__(self, num_classes, pretrained=False): super(C3D, self).__init__() self.conv1 = nn.quantized.Conv3d(3, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1))#..54.14ms self.pool1 = nn.MaxPool3d(kernel_size=(1, 2, 2), stride=(1, 2, 2)), self.conv2 = nn.quantized.Conv3d(64, 128, kernel_size=(3, 3, 3), padding=(1, 1, 1))#**395.749ms** self.pool2 = nn.MaxPool3d(kernel_size=(2, 2, 2), stride=(2, 2, 2)), self.conv3a = nn.quantized.Conv3d(128, 256, kernel_size=(3, 3, 3), padding=(1, 1, 1))#..208.237ms self.conv3b = nn.quantized.Conv3d(256, 256, kernel_size=(3, 3, 3), padding=(1, 1, 1))#***..348.491ms*** self.pool3 = nn.MaxPool3d(kernel_size=(2, 2, 2), stride=(2, 2, 2)), self.conv4a = nn.quantized.Conv3d(256, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1))#..64.714ms self.conv4b = nn.quantized.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1))#..169.855ms self.pool4 = nn.MaxPool3d(kernel_size=(2, 2, 2), stride=(2, 2, 2)), self.conv5a = nn.quantized.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1))#.27.173ms self.conv5b = nn.quantized.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1))#.25.972ms self.pool5 = nn.MaxPool3d(kernel_size=(2, 2, 2), stride=(2, 2, 2), padding=(0, 1, 1)), self.fc6 = nn.Linear(8192, 4096)#21.852ms self.fc7 = nn.Linear(4096, 4096)#.10.288ms self.fc8 = nn.Linear(4096, num_classes)#0.023ms, self.relu = nn.ReLU() self.softmax = nn.Softmax(dim=1), x = self.relu(self.conv1(x)) x = least_squares(self.pool1(x)), x = self.relu(self.conv2(x)) x = least_squares(self.pool2(x)), x = self.relu(self.conv3a(x)) x = self.relu(self.conv3b(x)) x = least_squares(self.pool3(x)), x = self.relu(self.conv4a(x)) x = self.relu(self.conv4b(x)) x = least_squares(self.pool4(x)), x = self.relu(self.conv5a(x)) x = self.relu(self.conv5b(x)) x = least_squares(self.pool5(x)), x = x.view(-1, 8192) x = self.relu(self.fc6(x)) x = self.dropout(x) x = self.relu(self.fc7(x)) x = self.dropout(x), def __init_weight(self): for m in self.modules(): if isinstance(m, nn.Conv3d): init.xavier_normal_(m.weight.data) init.constant_(m.bias.data, 0.01) elif isinstance(m, nn.Linear): init.xavier_normal_(m.weight.data) init.constant_(m.bias.data, 0.01), import torch.nn.utils.prune as prunedevice = torch.device("cuda" if torch.cuda.is_available() else "cpu")model = C3D(num_classes=2).to(device=device)prune.random_unstructured(module, name="weight", amount=0.3), parameters_to_prune = ( (model.conv2, 'weight'), (model.conv3a, 'weight'), (model.conv3b, 'weight'), (model.conv4a, 'weight'), (model.conv4b, 'weight'), (model.conv5a, 'weight'), (model.conv5b, 'weight'), (model.fc6, 'weight'), (model.fc7, 'weight'), (model.fc8, 'weight'),), prune.global_unstructured( parameters_to_prune, pruning_method=prune.L1Unstructured, amount=0.2), --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) in 19 parameters_to_prune, 20 pruning_method=prune.L1Unstructured, ---> 21 amount=0.2 22 ) ~/.local/lib/python3.7/site-packages/torch/nn/utils/prune.py in global_unstructured(parameters, pruning_method, **kwargs) 1017 1018 # flatten parameter values to consider them all at once in global pruning -> 1019 t = torch.nn.utils.parameters_to_vector([getattr(*p) for p in parameters]) 1020 # similarly, flatten the masks (if they exist), or use a flattened vector 1021 # of 1s of the same dimensions as t ~/.local/lib/python3.7/site-packages/torch/nn/utils/convert_parameters.py in parameters_to_vector(parameters) 18 for param in parameters: 19 # Ensure the parameters are located in the same device ---> 20 param_device = _check_param_device(param, param_device) 21 22 vec.append(param.view(-1)) ~/.local/lib/python3.7/site-packages/torch/nn/utils/convert_parameters.py in _check_param_device(param, old_param_device) 71 # Meet the first parameter 72 if old_param_device is None: ---> 73 old_param_device = param.get_device() if param.is_cuda else -1 74 else: 75 warn = False AttributeError: 'function' object has no attribute 'is_cuda', prune.global_unstructured when I use prune.global_unstructure I get that error. Is there a workaround? Now I'm :) and everything is working fine.. class GradScaler(torch.cuda.amp.GradScaler): AttributeError: module torch.cuda has no attribute amp Environment: GPU : RTX 8000 CUDA: 10.0 Pytorch How to handle a hobby that makes income in US, Linear Algebra - Linear transformation question. What is the point of Thrower's Bandolier? What's the difference between a Python module and a Python package? WebAttributeError: module 'torch' has no attribute 'cuda' Press any key to continue . d8ahazard/sd_dreambooth_extension#931. or in your case: If you sign in, click, Sorry, you must verify to complete this action. RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available () is Fal. pytorch1.61.6 I had to delete my venv folder in the end and let automatic1111 rebuild it. I got this error when working with Pytorch 1.12, but the error eliminated with Pytorch 1.10. If you are wondering whether you have a proper CUDA setup, that question belongs on the CUDA setup forum, and the verification steps are provided in the CUDA linux install guide. As you can see, the command you used to install pytorch is different from the one here. If you encounter an error with "RuntimeError: Couldn't install torch." How to parse XML and get instances of a particular node attribute? Steps to reproduce the problem. ERROR: No matching distribution found for torch==1.13.1+cu117. Thanks a lot! 0cc0ee1. Implement Seek on /dev/stdin file descriptor in Rust. Thanks! stderr: Traceback (most recent call last): didnt work as well. So I've ditched this extension for now, since I was no longer really using it anyway and updating it regularly breaks my Automatic1111 environment. Command: "C:\ai\stable-diffusion-webui\venv\Scripts\python.exe" -m pip install torch==1.13.1+cu117 torchvision==0.14.1+cu117 --extra-index-url https://download.pytorch.org/whl/cu117 This is more of a comment then an answer. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. I am actually pruning my model using a particular torch library for pruning then this is what happens model structure device = torch.device("cuda The text was updated successfully, but these errors were encountered: This problem doesn't exist in the newer pytorch 1.13. For more complete information about compiler optimizations, see our Optimization Notice. You can download 3.10 Python from here: https://www.python.org/downloads/release/python-3109/, Alternatively, use a binary release of WebUI: https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases, Python 3.11.0 (main, Oct 24 2022, 18:26:48) [MSC v.1933 64 bit (AMD64)] Please see. We are closing the case assuming that your issue got resolved.Please raise a new thread in case of any further issues. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Have a question about this project? Libc version: glibc-2.35, Python version: 3.8.15 (default, Oct 12 2022, 19:15:16) [GCC 11.2.0] (64-bit runtime) Re:AttributeError: module 'torch' has no attribute AttributeError: module 'torch' has no attribute 'is_cuda', Intel Connectivity Research Program (Private), oneAPI Registration, Download, Licensing and Installation, Intel Trusted Execution Technology (Intel TXT), Intel QuickAssist Technology (Intel QAT), Gaming on Intel Processors with Intel Graphics. I'm running without dreambooth now as I had to use CPU training anyway with my 4Gb card and they made that harder recently so I'd gone to Colab, which is much quicker anyway. GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0 This is kind of confusing because the traceback then shows an error which doesn't make sense for the given line. What else should I do to get right running? Pytorchpthh5python AttributeError: 'module' object has no attribute 'dumps'Keras What is the difference between paper presentation and poster presentation? Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. 3cuda 4killpidnvidia-smigpu 5pytorch pytorchcuda torch : 1.12.1/ python: 3.7.6 / cuda : """, def __init__(self, num_classes, pretrained=False): super(C3D, self).__init__() self.conv1 = nn.quantized.Conv3d(3, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1))#..54.14ms self.pool1 = nn.MaxPool3d(kernel_size=(1, 2, 2), stride=(1, 2, 2)), self.conv2 = nn.quantized.Conv3d(64, 128, kernel_size=(3, 3, 3), padding=(1, 1, 1))#**395.749ms** self.pool2 = nn.MaxPool3d(kernel_size=(2, 2, 2), stride=(2, 2, 2)), self.conv3a = nn.quantized.Conv3d(128, 256, kernel_size=(3, 3, 3), padding=(1, 1, 1))#..208.237ms self.conv3b = nn.quantized.Conv3d(256, 256, kernel_size=(3, 3, 3), padding=(1, 1, 1))#***..348.491ms*** self.pool3 = nn.MaxPool3d(kernel_size=(2, 2, 2), stride=(2, 2, 2)), self.conv4a = nn.quantized.Conv3d(256, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1))#..64.714ms self.conv4b = nn.quantized.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1))#..169.855ms self.pool4 = nn.MaxPool3d(kernel_size=(2, 2, 2), stride=(2, 2, 2)), self.conv5a = nn.quantized.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1))#.27.173ms self.conv5b = nn.quantized.Conv3d(512, 512, kernel_size=(3, 3, 3), padding=(1, 1, 1))#.25.972ms self.pool5 = nn.MaxPool3d(kernel_size=(2, 2, 2), stride=(2, 2, 2), padding=(0, 1, 1)), self.fc6 = nn.Linear(8192, 4096)#21.852ms self.fc7 = nn.Linear(4096, 4096)#.10.288ms self.fc8 = nn.Linear(4096, num_classes)#0.023ms, self.relu = nn.ReLU() self.softmax = nn.Softmax(dim=1), x = self.relu(self.conv1(x)) x = least_squares(self.pool1(x)), x = self.relu(self.conv2(x)) x = least_squares(self.pool2(x)), x = self.relu(self.conv3a(x)) x = self.relu(self.conv3b(x)) x = least_squares(self.pool3(x)), x = self.relu(self.conv4a(x)) x = self.relu(self.conv4b(x)) x = least_squares(self.pool4(x)), x = self.relu(self.conv5a(x)) x = self.relu(self.conv5b(x)) x = least_squares(self.pool5(x)), x = x.view(-1, 8192) x = self.relu(self.fc6(x)) x = self.dropout(x) x = self.relu(self.fc7(x)) x = self.dropout(x), def __init_weight(self): for m in self.modules(): if isinstance(m, nn.Conv3d): init.xavier_normal_(m.weight.data) init.constant_(m.bias.data, 0.01) elif isinstance(m, nn.Linear): init.xavier_normal_(m.weight.data) init.constant_(m.bias.data, 0.01), import torch.nn.utils.prune as prunedevice = torch.device("cuda" if torch.cuda.is_available() else "cpu")model = C3D(num_classes=2).to(device=device)prune.random_unstructured(module, name="weight", amount=0.3), parameters_to_prune = ( (model.conv2, 'weight'), (model.conv3a, 'weight'), (model.conv3b, 'weight'), (model.conv4a, 'weight'), (model.conv4b, 'weight'), (model.conv5a, 'weight'), (model.conv5b, 'weight'), (model.fc6, 'weight'), (model.fc7, 'weight'), (model.fc8, 'weight'),), prune.global_unstructured( parameters_to_prune, pruning_method=prune.L1Unstructured, amount=0.2), --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) in 19 parameters_to_prune, 20 pruning_method=prune.L1Unstructured, ---> 21 amount=0.2 22 ) ~/.local/lib/python3.7/site-packages/torch/nn/utils/prune.py in global_unstructured(parameters, pruning_method, **kwargs) 1017 1018 # flatten parameter values to consider them all at once in global pruning -> 1019 t = torch.nn.utils.parameters_to_vector([getattr(*p) for p in parameters]) 1020 # similarly, flatten the masks (if they exist), or use a flattened vector 1021 # of 1s of the same dimensions as t ~/.local/lib/python3.7/site-packages/torch/nn/utils/convert_parameters.py in parameters_to_vector(parameters) 18 for param in parameters: 19 # Ensure the parameters are located in the same device ---> 20 param_device = _check_param_device(param, param_device) 21 22 vec.append(param.view(-1)) ~/.local/lib/python3.7/site-packages/torch/nn/utils/convert_parameters.py in _check_param_device(param, old_param_device) 71 # Meet the first parameter 72 if old_param_device is None: ---> 73 old_param_device = param.get_device() if param.is_cuda else -1 74 else: 75 warn = False AttributeError: 'function' object has no attribute 'is_cuda', prune.global_unstructured when I use prune.global_unstructure I get that error. python AttributeError: 'module' object has no attribute 'dumps' pre_dict = {k: v for k, v in pre_dict.items () if k in model_dict} 1. If you preorder a special airline meal (e.g. ROCM used to build PyTorch: N/A, OS: Ubuntu 22.04.1 LTS (x86_64) This is just a side node, because your code and error message do not match: When importing code to Jupyter Notebook it is safest to restart the kernel after doing changes to the imported code. prune.global_unstructured when I use prune.global_unstructure I get that error please help Sorry for late response Since this issue is not related to Intel Devcloud can we close the case? run(f'"{python}" -m {torch_command}', "Installing torch and torchvision", "Couldn't install torch", live=True) To subscribe to this RSS feed, copy and paste this URL into your RSS reader. First of all usetorch.cuda.is_available() to detemine the CUDA availability also weneed more details tofigure out the issue.Could you provide us the commands and stepsyou followed?