return run(f'"{python}" -c "{code}"', desc, errdesc) File "C:\ai\stable-diffusion-webui\launch.py", line 360, in How can I import a module dynamically given the full path? File "", line 1, in """, 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. Sorry, you must verify to complete this action. 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. Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2, Calling a function of a module by using its name (a string). Please click the verification link in your email. Im wondering if my cuda setup is problematic? 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? Well occasionally send you account related emails. Is there a single-word adjective for "having exceptionally strong moral principles"? message, Making statements based on opinion; back them up with references or personal experience. So something is definitely hostile as you said =P. WebThis package adds support for CUDA tensor types, that implement the same function as CPU tensors, but they utilize GPUs for computation. vegan) just to try it, does this inconvenience the caterers and staff? Installing torch and torchvision 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. profile. See instructions here https://pytorch.org/get-started/locally/ How can I check before my flight that the cloud separation requirements in VFR flight rules are met? If you sign in, click, Sorry, you must verify to complete this action. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Nvidia driver version: 510.47.03 privacy statement. [pip3] torch==1.12.1+cu116 This 100% happened after an extension update. 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_. In my code below, I added this statement: device = torch.device ("cuda:0" if torch.cuda.is_available () else "cpu") net.to (device) But this seems not right or enough. torch torch.rfft torch.irfft torch.rfft rfft ,torch.irfft irfft Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cu117 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 What browsers do you use to microsoft/Bringing-Old-Photos-Back-to-Life#100. How do I unload (reload) a Python module? It should install the latest version. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. https://github.com/samet-akcay/ganomaly/blob/master/options.py#L40 File "C:\ai\stable-diffusion-webui\launch.py", line 272, in prepare_environment 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. 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? I tried to reinstall the pytorch and update to the newest version (1.4.0), still exists error. The error is unfortunately not super descriptive or guiding me how to fix it. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. 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? The same code can run correctly on a different machine with PyTorch version: 1.8.2+cu111, Collecting environment information Thanks for contributing an answer to Stack Overflow! In torch.distributed, how to average gradients on different GPUs correctly? Im running from torch.cuda.amp import GradScaler, autocast and got the error as in title. I had to delete my venv folder in the end and let automatic1111 rebuild it. 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. However, the code that works in Ubuntu 20.04, throws this error: I have this version of PyTorch on Ubuntu 20.04: Ideally I want the same code to run across two machines. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. 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. What is the point of Thrower's Bandolier? Making statements based on opinion; back them up with references or personal experience. For the Nozomi from Shinagawa to Osaka, say on a Saturday afternoon, would tickets/seats typically be available - or would you need to book? I'm trying to implement the Spatial Transformer Network from here and I am running into this issue: This AttributeError implies that somewhere in the code must be something like torch.float. This happened to me too the last dreambooth update made some requirements change that screwed the python environment. I have two machines that I need to check my code across one is Ubuntu 18.04 and the other is Ubuntu 20.04. [pip3] torchvision==0.13.1+cu116 """, 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? Powered by Discourse, best viewed with JavaScript enabled, AttributeError: module 'torch.cuda' has no attribute 'amp'. raise RuntimeError(message) Now I'm :) and everything is working fine.. 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. What It seems that you need to add --device cpu in the command line to make it work. Why is there a voltage on my HDMI and coaxial cables? 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. Why are Suriname, Belize, and Guinea-Bissau classified as "Small Island Developing States"? Traceback (most recent call last): If you encounter an error with "RuntimeError: Couldn't install torch." Why do small African island nations perform better than African continental nations, considering democracy and human development? How do/should administrators estimate the cost of producing an online introductory mathematics class? 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.