By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. The same code can run correctly on a different machine with PyTorch version: 1.8.2+cu111, Collecting environment information You might want to ask pytorch questions on a pytorch forum. Sorry, you must verify to complete this action. You just need to find the line (or lines) where torch.float is used and change it. 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). By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Why do I get AttributeError: 'NoneType' object has no attribute 'something'? To learn more, see our tips on writing great answers. Connect and share knowledge within a single location that is structured and easy to search. I'm using Windows, conda environment, installed Pytorch-1.7.1, Torchvision-0.8.2, Cuda-Toolkit-11.0 > all compatible. Error code: 1 Commit hash: 0cc0ee1 vegan) just to try it, does this inconvenience the caterers and staff? Why do many companies reject expired SSL certificates as bugs in bug bounties? Asking for help, clarification, or responding to other answers. Is there a single-word adjective for "having exceptionally strong moral principles"? Does your environment recognize torch.cuda? [conda] Could not collect. Whats the grammar of "For those whose stories they are"? or any other error regarding unsuccessful package (library) installation, By clicking Sign up for GitHub, you agree to our terms of service and How can I import a module dynamically given the full path? @harshit_k I added more information and you can see that the 0.1.12 is installed. Is there a single-word adjective for "having exceptionally strong moral principles"? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Is it possible to rotate a window 90 degrees if it has the same length and width? File "C:\ai\stable-diffusion-webui\launch.py", line 360, in Im running from torch.cuda.amp import GradScaler, autocast and got the error as in title. As the PyTorch forum member with the most posts manages the PyTorch Core team @ NVIDIA. . How can I import a module dynamically given the full path? In my code below, I added this statement: But this seems not right or enough. What is the point of Thrower's Bandolier? I am actually pruning my model using a particular torch library for pruning, device = torch.device("cuda" if torch.cuda.is_available() else "cpu")class C3D(nn.Module): """ The C3D network. """, 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. Why is this sentence from The Great Gatsby grammatical? I am actually pruning my model using a particular torch library for pruning then this is what happens model structure device = torch.device("cuda Connect and share knowledge within a single location that is structured and easy to search. File "", line 1, in Just renamed it to something else and delete the file named 'torch.py' in the directory By clicking Sign up for GitHub, you agree to our terms of service and You may re-send via your WebAttributeError: module 'torch' has no attribute 'cuda' Press any key to continue . 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. How to parse XML and get instances of a particular node attribute? Otherwise already loaded modules are omitted during import and changes are not applied. GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04) 11.3.0 Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cu117 The best approach would be to use the same PyTorch release on both machines. prune.global_unstructured when I use prune.global_unstructure I get that error please help If you preorder a special airline meal (e.g. Also happened to me and dreambooth was one of the ones that updated! 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. This is the first time for me to run Pytorch with GPU on a linux machine. I tried to reinstall the pytorch and update to the newest version (1.4.0), still exists error. Find centralized, trusted content and collaborate around the technologies you use most. Why is there a voltage on my HDMI and coaxial cables? You may re-send via your Traceback (most recent call last): I have not tested it on Linux, but I used the command for Windows and it worked great for me on Anaconda. 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. 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. Windows. [pip3] torchaudio==0.12.1+cu116 run(f'"{python}" -m {torch_command}', "Installing torch and torchvision", "Couldn't install torch", live=True) Asking for help, clarification, or responding to other answers. You might need to install the nightly binary, since Autocasting wasnt shipped in 1.5. New replies are no longer allowed. privacy statement. I had to delete my venv folder in the end and let automatic1111 rebuild it. Is there a single-word adjective for "having exceptionally strong moral principles"? We tried running your code.The issue seems to be with the quantized.Conv3d, instead you can use normal convolution3d. Shouldn't this install latest version? Im wondering if my cuda setup is problematic? Be sure to install PyTorch with CUDA support. If you sign in, click, Sorry, you must verify to complete this action. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. You just need to find the I just checked that, it's strange it's 0.1.12_1. What is the purpose of non-series Shimano components? By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. 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? Please click the verification link in your email. to your account. Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. However, some new errors appear as follows: And I wonder that if it may be impossible to run these codes in the cpu only computer? privacy statement. torch.cuda.amp is available in the nightly binaries, so you would have to update. Do you know how I can fix it? """, 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. Yesterday I installed Pytorch with "conda install pytorch torchvision -c pytorch". By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Pytorchpthh5python AttributeError: 'module' object has no attribute 'dumps'Keras You signed in with another tab or window. Why do small African island nations perform better than African continental nations, considering democracy and human development? --------------------------------------------------------------------------- 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'. I got this error when working with Pytorch 1.12, but the error eliminated with Pytorch 1.10. Please always post the full error traceback. How can we prove that the supernatural or paranormal doesn't exist? In your code example I cannot find anything like it. As you can see, the command you used to install pytorch is different from the one here. AnacondatorchAttributeError: module 'torch' has no attribute 'irfft'module 'torch' has no attribute 'no_grad' How do I check if an object has an attribute? Try removing it then reinstalling. 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? The text was updated successfully, but these errors were encountered: This problem doesn't exist in the newer pytorch 1.13. No, 1.13 is out, thanks for confirming @kurtamohler.

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