return run(f'"{python}" -c "{code}"', desc, errdesc) rev2023.3.3.43278. Can carbocations exist in a nonpolar solvent? By clicking Sign up for GitHub, you agree to our terms of service and 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_. Can we reopen this issue and maybe get a backport to 1.12? Libc version: glibc-2.35, Python version: 3.8.15 (default, Oct 12 2022, 19:15:16) [GCC 11.2.0] (64-bit runtime) Making statements based on opinion; back them up with references or personal experience. Please click the verification link in your email. Not the answer you're looking for? This program is tested with 3.10.6 Python, but you have 3.11.0. 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. If you sign in, click, Sorry, you must verify to complete this action. By clicking Sign up for GitHub, you agree to our terms of service and 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. For the code you've posted it makes no sense. I tried to reproduce the code from https://github.com/samet-akcay/ganomaly and run the commands in the git bash software. GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3090 Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. To figure out the exact issue we need yourcode and steps to test from our end.Could you sharethe entire code and steps in a zip file? Sign in Find centralized, trusted content and collaborate around the technologies you use most. AttributeError: 'module' object has no attribute 'urlopen'. Thank you. 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 @harshit_k I added more information and you can see that the 0.1.12 is installed. Error code: 1 I'm stuck with this issue and the problem is I cannot use the latest version of pytorch (currently using 1.12+cu11.3). In my code below, I added this statement: But this seems not right or enough. Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2, Calling a function of a module by using its name (a string). Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. WebAttributeError: module 'torch' has no attribute 'cuda' Press any key to continue . Since this issue is not related to Intel Devcloud can we close the case? prune.global_unstructured when I use prune.global_unstructure I get that error please help Is it possible to rotate a window 90 degrees if it has the same length and width? Are there tables of wastage rates for different fruit and veg? I don't think the function torch._C._cuda_setDevice or torch.cuda.set_device is available in a cpu-only build. The text was updated successfully, but these errors were encountered: This problem doesn't exist in the newer pytorch 1.13. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. and delete current Python and "venv" folder in WebUI's directory. Why are Suriname, Belize, and Guinea-Bissau classified as "Small Island Developing States"? microsoft/Bringing-Old-Photos-Back-to-Life#100. Powered by Discourse, best viewed with JavaScript enabled, AttributeError: module 'torch.cuda' has no attribute 'amp'. Try removing it then reinstalling. I tried to reinstall the pytorch and update to the newest version (1.4.0), still exists error. I havent found this issue anywhere else yet Im running pytorch3D (0.3.0), which requires pytorch (1.12.1). import 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) It should install the latest version. How do I check if an object has an attribute? CUDA used to build PyTorch: 11.6 . Im running from torch.cuda.amp import GradScaler, autocast and got the error as in title. The same code can run correctly on a different machine with PyTorch version: 1.8.2+cu111, Collecting environment information 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'" "After the incident", I started to be more careful not to trip over things. This topic was automatically closed 14 days after the last reply. Why does Mister Mxyzptlk need to have a weakness in the comics? If you don't want to update or if you are not able to do so for some reason. or can I please get some context of why this is occuring? Not the answer you're looking for? 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. File "C:\ai\stable-diffusion-webui\launch.py", line 360, in prepare_environment() Tried doing this and got another error =P Dreambooth can suck it. It seems part of these problems have been solved and the data is automatically downloaded when I run the codes. Making statements based on opinion; back them up with references or personal experience. vegan) just to try it, does this inconvenience the caterers and staff? 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. Clang version: Could not collect Still get this error--module 'torch._C' has no attribute '_cuda_setDevice', https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/issues/360, https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/issues/67, https://github.com/samet-akcay/ganomaly/blob/master/options.py#L40, module 'torch._C' has no attribute '_cuda_setDevice', AttributeError: module 'torch._C' has no attribute '_cuda_setDevice'. Already on GitHub? Already on GitHub? Find centralized, trusted content and collaborate around the technologies you use most. What is the point of Thrower's Bandolier? See instructions here https://pytorch.org/get-started/locally/ 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. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Help for those needing help starting or connecting to the Intel DevCloud, The Intel sign-in experience has changed to support enhanced security controls. BTW, I have to close this issue because it's not a problem of this repo. Normal boot up. For more complete information about compiler optimizations, see our Optimization Notice. """, 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. You may try updating. On a machine with PyTorch version: 1.12.1+cu116, running the following code gets error message module 'torch.cuda' has no attribute '_UntypedStorage'. Error: " 'dict' object has no attribute 'iteritems' ", Getting Nan result out of ResNet101 backbone with Kitti images. In torch.distributed, how to average gradients on different GPUs correctly? RuntimeError: Couldn't install torch. Python platform: Linux-5.15.0-52-generic-x86_64-with-glibc2.35 Please see. Seemed to resolve it for the other people on that thread earlier too. Sign in Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2, Calling a function of a module by using its name (a string). vegan) just to try it, does this inconvenience the caterers and staff? No issues running the same script for a different dataset. Traceback (most recent call last): Now I'm :) and everything is working fine.. conda list torch gives me: But, when asking for the torchvision version in Jupyter Notebook, I get: AttributeError: module 'torch.fft' has no attribute 'fftfreq' Hot Network Questions Add circled letters in titles Commit hash: 0cc0ee1 If you preorder a special airline meal (e.g. Why is this sentence from The Great Gatsby grammatical? You may re-send via your. @emailweixu please reopen if error repros on pytorch 1.13. run_python("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'") In such a case restarting the kernel helps. For the Nozomi from Shinagawa to Osaka, say on a Saturday afternoon, would tickets/seats typically be available - or would you need to book? We tried running your code.The issue seems to be with the quantized.Conv3d, instead you can use normal convolution3d. How to use Slater Type Orbitals as a basis functions in matrix method correctly? File "C:\ai\stable-diffusion-webui\launch.py", line 360, in RuntimeError: Error running command. My code is GPL licensed, can I issue a license to have my code be distributed in a specific MIT licensed project? raise RuntimeError(f"""{errdesc or 'Error running command'}. To learn more, see our tips on writing great answers. i actually reported that to dreambooth extension author 3 weeks ago and got told off. Is debug build: False What pytorch version are you using? Is there a single-word adjective for "having exceptionally strong moral principles"? Thanks a lot! torch.cuda.amp is available in the nightly binaries, so you would have to update. rev2023.3.3.43278. Asking for help, clarification, or responding to other answers. Can you provide the full error stack trace? Will Gnome 43 be included in the upgrades of 22.04 Jammy? --------------------------------------------------------------------------- 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'. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. You signed in with another tab or window. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. The best approach would be to use the same PyTorch release on both machines. You might need to install the nightly binary, since Autocasting wasnt shipped in 1.5. What does the "yield" keyword do in Python? NVIDIA most definitely does have a PyTorch team, but the PyTorch forums are still a great place to ask questions. . Otherwise already loaded modules are omitted during import and changes are not applied. This is kind of confusing because the traceback then shows an error which doesn't make sense for the given line. How do I check if an object has an attribute? If you sign in, click, Sorry, you must verify to complete this action. You signed in with another tab or window. For the Nozomi from Shinagawa to Osaka, say on a Saturday afternoon, would tickets/seats typically be available - or would you need to book? Is XNNPACK available: True, Versions of relevant libraries: PyTorch - "Attribute Error: module 'torch' has no attribute 'float', How Intuit democratizes AI development across teams through reusability. 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: The name of the source file was 'torch.py'. CMake version: version 3.22.1 Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug 1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)] Does ZnSO4 + H2 at high pressure reverses to Zn + H2SO4? """, 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.
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