I am currently starting to do basic Machine Learning via Pytorch on Linux Mint. However, I have this very weird issue. I have some imports, normally they only take at most 10s to run, and I can go on doing my things. However, today, I run the exact same code, and now, importing suddenly becomes a massive problem, as this code to import torch, suddenly went from taking some time to literally eternity: import torch x = torch.rand(5, 3) print(x) I run this code in a venv, and I installed with it a bunch of other packages: Package Version ------------------------- -------------- aiohappyeyeballs 2.4.3 aiohttp 3.10.8 aiosignal 1.3.1 anyio 4.6.0 argon2-cffi 23.1.0 argon2-cffi-bindings 21.2.0 arrow 1.3.0 asttokens 2.4.1 async-lru 2.0.4 attrs 24.2.0 autograd 1.7.0 autograd-gamma 0.5.0 babel 2.16.0 beautifulsoup4 4.12.3 bleach 6.1.0 certifi 2024.8.30 cffi 1.17.1 charset-normalizer 3.3.2 comm 0.2.2 contourpy 1.3.0 cycler 0.12.1 debugpy 1.8.6 decorator 5.1.1 defusedxml 0.7.1 executing 2.1.0 fastjsonschema 2.20.0 filelock 3.16.1 fonttools 4.54.1 formulaic 1.0.2 fqdn 1.5.1 frozenlist 1.4.1 fsspec 2024.9.0 h11 0.14.0 httpcore 1.0.6 httpx 0.27.2 idna 3.10 interface-meta 1.3.0 ipykernel 6.29.5 ipython 8.28.0 ipywidgets 8.1.5 ISLP 0.4.0 isoduration 20.11.0 jedi 0.19.1 Jinja2 3.1.4 joblib 1.4.2 json5 0.9.25 jsonpointer 3.0.0 jsonschema 4.23.0 jsonschema-specifications 2023.12.1 jupyter 1.1.1 jupyter_client 8.6.3 jupyter-console 6.6.3 jupyter_core 5.7.2 jupyter-events 0.10.0 jupyter-lsp 2.2.5 jupyter_server 2.14.2 jupyter_server_terminals 0.5.3 jupyterlab 4.2.5 jupyterlab_pygments 0.3.0 jupyterlab_server 2.27.3 jupyterlab_widgets 3.0.13 kiwisolver 1.4.7 lifelines 0.29.0 lightning-utilities 0.11.7 lxml 5.3.0 MarkupSafe 2.1.5 matplotlib 3.9.2 matplotlib-inline 0.1.7 mistune 3.0.2 mpmath 1.3.0 multidict 6.1.0 nbclient 0.10.0 nbconvert 7.16.4 nbformat 5.10.4 nest-asyncio 1.6.0 networkx 3.3 notebook 7.2.2 notebook_shim 0.2.4 numpy 1.26.4 nvidia-cublas-cu12 12.1.3.1 nvidia-cuda-cupti-cu12 12.1.105 nvidia-cuda-nvrtc-cu12 12.1.105 nvidia-cuda-runtime-cu12 12.1.105 nvidia-cudnn-cu12 9.1.0.70 nvidia-cufft-cu12 11.0.2.54 nvidia-curand-cu12 10.3.2.106 nvidia-cusolver-cu12 11.4.5.107 nvidia-cusparse-cu12 12.1.0.106 nvidia-nccl-cu12 2.20.5 nvidia-nvjitlink-cu12 12.6.77 nvidia-nvtx-cu12 12.1.105 overrides 7.7.0 packaging 24.1 pandas 2.2.3 pandocfilters 1.5.1 parso 0.8.4 patsy 0.5.6 pexpect 4.9.0 pillow 10.4.0 pip 24.0 platformdirs 4.3.6 progressbar2 4.5.0 prometheus_client 0.21.0 prompt_toolkit 3.0.48 psutil 6.0.0 ptyprocess 0.7.0 pure_eval 0.2.3 pycparser 2.22 pygam 0.9.1 Pygments 2.18.0 pyparsing 3.1.4 python-dateutil 2.9.0.post0 python-json-logger 2.0.7 python-utils 3.9.0 pytorch-lightning 2.4.0 pytz 2024.2 PyYAML 6.0.2 pyzmq 26.2.0 referencing 0.35.1 requests 2.32.3 rfc3339-validator 0.1.4 rfc3986-validator 0.1.1 rpds-py 0.20.0 scikit-learn 1.5.2 scipy 1.11.4 Send2Trash 1.8.3 setuptools 75.1.0 six 1.16.0 sniffio 1.3.1 soupsieve 2.6 stack-data 0.6.3 statsmodels 0.14.3 sympy 1.13.3 terminado 0.18.1 threadpoolctl 3.5.0 tinycss2 1.3.0 torch 2.4.1+cpu torchaudio 2.4.1+cpu torchinfo 1.8.0 torchmetrics 1.4.2 torchvision 0.19.1+cpu tornado 6.4.1 tqdm 4.66.5 traitlets 5.14.3 triton 3.0.0 types-python-dateutil 2.9.0.20241003 typing_extensions 4.12.2 tzdata 2024.2 uri-template 1.3.0 urllib3 2.2.3 wcwidth 0.2.13 webcolors 24.8.0 webencodings 0.5.1 websocket-client 1.8.0 widgetsnbextension 4.0.13 wrapt 1.16.0 yarl 1.13.1 I decided to investigate and run python -v -c "import torch", and I noted that it gets stuck on this line: import 'torch.torch_version' # <_frozen_importlib_external.SourceFileLoader object at 0x7ec23812f470> This happened when I ran the code inside a Jupyter Notebook on VSCode, so I tried restarting the kernel, reloading VSCode, and even running the file outside (by taking that import torch code above and paste it to another file, with again forever running time), and alternative kernels doesn't work either. What should I do? Update 1: I tried an older version of torch, namely torch==2.3.1. However it still locks in the exact same place My Python version is 3.12.3, for anyone interested. Update 2: I have wrote this as an github issue: https://github.com/pytorch/pytorch/issues/137260 Continue reading...
