Comments (4)
eps696
commented on June 7, 2024
from the logs above i see it was trying to install pytorch 1.7.1 [required to run CLIP] and has failed downloading it, due to the network errors. i can't help with network issues obviously, but the obvious solution is to install pytorch 1.7.1 first, then go ahead with this repo.
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squinonescolon
commented on June 7, 2024
Torch is already installed:
Requirement already satisfied: torch in /home/steven/anaconda3/lib/python3.8/site-packages (1.8.1)
Requirement already satisfied: numpy in /home/steven/anaconda3/lib/python3.8/site-packages (from torch) (1.18.5)
Requirement already satisfied: typing-extensions in /home/steven/anaconda3/lib/python3.8/site-packages (from torch) (3.7.4.2)
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squinonescolon
commented on June 7, 2024
Do I need to install 1.7.1 instead of 1.8.1?
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eps696
commented on June 7, 2024
yes
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Related Issues (20)
- RuntimeError: CUDA out of memory. Tried to allocate 60.00 MiB (GPU 0; 6.00 GiB total capacity; 4.11 GiB already allocated; 34.82 MiB free; 4.42 GiB reserved in total by PyTorch) HOT 3
- Pytorch Import torch.irfft Update to torch.fft.irfft HOT 1
- Specify GPU HOT 2
- DeepSpeed integration for training on local cheaper GPUs. HOT 3
- Invalid Syntax when trying to run the first time HOT 10
- Error when running "Generate" HOT 2
- Illustrip3D - problems with video output quality HOT 3
- Can't generate video HOT 14
- init_image support HOT 4
- Colab notebook "How to just use Aphantasia" HOT 3
- clip_fft.py won't start HOT 4
- Error HOT 2
- IndexError in IllusTrip3D HOT 1
- TypeError: 'float' object is not subscriptable HOT 3
- integrate with Lightning ecosystem CI HOT 1
- Something changed since 04/19/2022 HOT 1
- Incorporating the -notext option into IllusTrip3D.ipynb HOT 2
- NameError: name 'aug_transform' is not defined HOT 1
- AssertionError: Torch not compiled with CUDA enabled HOT 1
- torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 58.00 MiB (GPU 0; 2.00 GiB total capacity; 1.58 GiB already allocated; 0 bytes free; 1.74 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF HOT 1
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