It seems part of these problems have been solved and the data is automatically downloaded when I run the codes. module 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) venv "C:\ai\stable-diffusion-webui\venv\Scripts\Python.exe" File "C:\ai\stable-diffusion-webui\launch.py", line 360, in It should install the latest version. What is the point of Thrower's Bandolier? 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'") rev2023.3.3.43278. If you sign in, click, Sorry, you must verify to complete this action. How do I check if an object has an attribute? If you have a line like in the example you've linked, it makes perfectly sense to get an error like this. So if there was an error in the old code this error might still occur and the traceback then points to the line you have just corrected. Shouldn't this install latest version? cuDNN version: Could not collect By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Asking for help, clarification, or responding to other answers. Please click the verification link in your email. Later in the night i did the same and got the same error. 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. I have two machines that I need to check my code across one is Ubuntu 18.04 and the other is Ubuntu 20.04. vegan) just to try it, does this inconvenience the caterers and staff? Clang version: Could not collect Have a question about this project? Is it suspicious or odd to stand by the gate of a GA airport watching the planes? As you did not include a full error traceback I can only conjecture what the problem is. How to handle a hobby that makes income in US, Linear Algebra - Linear transformation question. AttributeError: 'datetime' module has no attribute 'strptime', Error: " 'dict' object has no attribute 'iteritems' ". Find centralized, trusted content and collaborate around the technologies you use most. This program is tested with 3.10.6 Python, but you have 3.11.0. ), Implement Seek on /dev/stdin file descriptor in Rust. We tried running your code.The issue seems to be with the quantized.Conv3d, instead you can use normal convolution3d. 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. Have a question about this project? RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available () is Fal. pytorch1.61.6 AC Op-amp integrator with DC Gain Control in LTspice. The text was updated successfully, but these errors were encountered: torch cannot detect cuda anymore, most likely you'll need to reinstall torch. to your account, On a machine with PyTorch version: 1.12.1+cu116, running the following code gets error message module 'torch.cuda' has no attribute '_UntypedStorage'. What's the difference between a Python module and a Python package? Are there tables of wastage rates for different fruit and veg? Find centralized, trusted content and collaborate around the technologies you use most. Is it possible to rotate a window 90 degrees if it has the same length and width? BTW, I have to close this issue because it's not a problem of this repo. PyTorch version: 1.12.1+cu116 Im running from torch.cuda.amp import GradScaler, autocast and got the error as in title. I just checked that, it's strange it's 0.1.12_1. Hi, Could you give us an update? This topic was automatically closed 14 days after the last reply. """, 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. Thanks for contributing an answer to Stack Overflow! Pytorchpthh5python AttributeError: 'module' object has no attribute 'dumps'Keras """, 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. Already on GitHub? 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. Not the answer you're looking for? - the incident has nothing to do with me; can I use this this way? File "", line 1, in yes I reported an issue yesterday and met with much the same response. AttributeError: module 'torch._C' has no attribute '_cuda_setDevice' facebookresearch/detr#346 marco-rudolph mentioned this issue on Sep 1, 2021 error raise RuntimeError(message) Will Gnome 43 be included in the upgrades of 22.04 Jammy? Can we reopen this issue and maybe get a backport to 1.12? To subscribe to this RSS feed, copy and paste this URL into your RSS reader. 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. So something is definitely hostile as you said =P. Nvidia driver version: 510.47.03 Also happened to me and dreambooth was one of the ones that updated! [pip3] torch==1.12.1+cu116 If you don't want to update or if you are not able to do so for some reason. and delete current Python and "venv" folder in WebUI's directory. I could fix this on the 1.12 branch, but will there be a 1.12.2 release? What is the purpose of this D-shaped ring at the base of the tongue on my hiking boots? You might need to install the nightly binary, since Autocasting wasnt shipped in 1.5. d8ahazard/sd_dreambooth_extension#931. In such a case restarting the kernel helps. Can carbocations exist in a nonpolar solvent? 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? I just got the following error when attempting to use amp. Im wondering if my cuda setup is problematic? or in your case: For more complete information about compiler optimizations, see our Optimization Notice. In my case command looks like: But you must obtain package list for yours machine form this site: please help I just sent the iynb model You just need to find the line (or lines) where torch.float is used and change it. message, How to use Slater Type Orbitals as a basis functions in matrix method correctly? The error is unfortunately not super descriptive or guiding me how to fix it. How do I check if an object has an attribute? Sign in Libc version: glibc-2.35, Python version: 3.8.15 (default, Oct 12 2022, 19:15:16) [GCC 11.2.0] (64-bit runtime) WebAttributeError: module tensorflow has no attribute GPUOptionsTensorflow 1.X 2.XTensorflow 1.Xgpu_options = tf.GPUOptions(per_process_gpu_memory_fraction)Tensorflow 2.Xgpu_options =tf.compat.v1.GPUOptions(per_process_gpu_memory_fractio torch.cuda.amptorch1.6torch1.4 1.7.1 Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2, Calling a function of a module by using its name (a string). Does your environment recognize torch.cuda?
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