Clang version: Could not collect PyTorch - "Attribute Error: module 'torch' has no attribute 'float', How Intuit democratizes AI development across teams through reusability. I could fix this on the 1.12 branch, but will there be a 1.12.2 release? https://pytorch.org/. Later in the night i did the same and got the same error. ERROR: Could not find a version that satisfies the requirement torch==1.13.1+cu117 (from versions: none) By clicking Sign up for GitHub, you agree to our terms of service and I got this error when working with Pytorch 1.12, but the error eliminated with Pytorch 1.10. Thank you. 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'" privacy statement. [pip3] torch==1.12.1+cu116 AttributeError:partially initialized module 'torch' has no attribute 'cuda', How Intuit democratizes AI development across teams through reusability. What does the "yield" keyword do in Python? The text was updated successfully, but these errors were encountered: torch cannot detect cuda anymore, most likely you'll need to reinstall torch. Why does Mister Mxyzptlk need to have a weakness in the comics? Traceback (most recent call last): File "D:/anaconda/envs/ml/Lib/site-packages/torch_sparse/__init__.py", line 4, in import torch File "D:\anaconda\envs\ml\lib\site-packages\torch_, File "D:\anaconda\envs\ml\lib\platform.py", line 897, in system return uname().system File "D:\anaconda\envs\ml\lib\platform.py", line 785, in uname node = _node() File "D:\anaconda\envs\ml\lib\platform.py", line 588, in _node import socket File "D:\anaconda\envs\ml\lib\socket.py", line 52, in import os, sys, io, selectors, File "D:\anaconda\envs\ml\lib\selectors.py", line 12, in import select File "D:\anaconda\envs\ml\Lib\site-packages\torch_sparse\select.py", line 1, in from torch_sparse.tensor import SparseTensor File "D:\anaconda\envs\ml\lib\site-packages\torch_sparse_. Commit hash: 0cc0ee1 Please click the verification link in your email. prune.global_unstructured when I use prune.global_unstructure I get that error please help In my code below, I added this statement: But this seems not right or enough. torch.cuda.amptorch1.6torch1.4 1.7.1 # Note: the code can run if the following two lines are commented out. The text was updated successfully, but these errors were encountered: This problem doesn't exist in the newer pytorch 1.13. By clicking Sign up for GitHub, you agree to our terms of service and Yes twice updates to dreambooth have screwed my python environment badly. I have two machines that I need to check my code across one is Ubuntu 18.04 and the other is Ubuntu 20.04. CUDA runtime version: Could not collect 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). How can we prove that the supernatural or paranormal doesn't exist? Sorry for late response Error code: 1 Did any DOS compatibility layers exist for any UNIX-like systems before DOS started to become outmoded? torch cannot detect cuda anymore, most likely you'll need to reinstall torch. You just need to find the line (or lines) where torch.float is used and change it. CUDA used to build PyTorch: 11.6 By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. For more complete information about compiler optimizations, see our Optimization Notice. The nature of simulating nature: A Q&A with IBM Quantum researcher Dr. Jamie We've added a "Necessary cookies only" option to the cookie consent popup. that is, I change the code torch.cuda.set_device(self.opt.gpu_ids[0]) to torch.cuda.set_device(self.opt.gpu_ids[-1]) and torch._C._cuda_setDevice(device) to torch._C._cuda_setDevice(-1)but it still not works. Will Gnome 43 be included in the upgrades of 22.04 Jammy? However, the link you referenced for the code contains the following line: PyTorch data types like torch.float came with PyTorch 0.4.0, so when you use something like torch.float in earlier versions like 0.3.1 you will see this error, because torch then actually has no attribute float. As you can see, the version 0.1.12 is installed: Although this question is very old, I would recommend those who are facing this problem to visit pytorch.org and check the command to install pytorch from there, there is a section dedicated to this: Have you installed the CUDA version of pytorch? Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. 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 Does ZnSO4 + H2 at high pressure reverses to Zn + H2SO4? Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. If you preorder a special airline meal (e.g. [notice] To update, run: C:\ai\stable-diffusion-webui\venv\Scripts\python.exe -m pip install --upgrade pip Thanks for contributing an answer to Stack Overflow! What pytorch version are you using? Find centralized, trusted content and collaborate around the technologies you use most. Is there a single-word adjective for "having exceptionally strong moral principles"? You may just comment it out. 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? Already on GitHub? please downgrade (or upgrade) to the latest version of 3.10 Python """, 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. RuntimeError: Error running command. Well occasionally send you account related emails. How would "dark matter", subject only to gravity, behave? Im running from torch.cuda.amp import GradScaler, autocast and got the error as in title. i actually reported that to dreambooth extension author 3 weeks ago and got told off. As you can see, the command you used to install pytorch is different from the one here. See instructions here https://pytorch.org/get-started/locally/ What else should I do to get right running? Edit: running the same script with the less extensive dataset also produces the AttributeError in the subject. At this moment we are not planning to move to pytorch 1.13 yet. The text was updated successfully, but these errors were encountered: I don't think the function torch._C._cuda_setDevice or torch.cuda.set_device is available in a cpu-only build. File "", line 1, in Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cu117 I havent found this issue anywhere else yet Im running pytorch3D (0.3.0), which requires pytorch (1.12.1). prepare_environment() [notice] A new release of pip available: 22.3 -> 23.0.1 New replies are no longer allowed. What is the difference between paper presentation and poster presentation? Have a question about this project? 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. Also happened to me and dreambooth was one of the ones that updated! CUDA_MODULE_LOADING set to: Why is this sentence from The Great Gatsby grammatical? I'm stuck with this issue and the problem is I cannot use the latest version of pytorch (currently using 1.12+cu11.3). The best approach would be to use the same PyTorch release on both machines. . 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