Closed bertsky closed 2 years ago
CUDA version 11.2 (default for Debian stable) is also unsupported.
OCR-D CUDA docker images use CUDA version 11.3.
but CUDA 10.0 – which still is OCR-D's main target platform for CUDA builds – is out.
OCR-D CUDA docker images use CUDA version 11.3.
That's due to the changes I introduced since I wrote this. They support all CUDA versions.
CUDA version 11.2 (default for Debian stable) is also unsupported.
Yes, so it seems. I have two options now: add that case to the CPU fallbacks, or run with the Pytorch for that platform and introduce a fallback source build for Detectron2. I tend towards the latter, as it would also cover other platforms.
I just had a failing build on Debian stable with Python 3.7 and CUDA version 11.4. What about building from source as a fallback as you already suggested above? pip install 'git+https://github.com/facebookresearch/detectron2.git'
works fine for me and does not take excessive time.
pip install 'git+https://github.com/facebookresearch/detectron2.git'
works fine for me and does not take excessive time.
If it worked for you, that's sheer luck I'm afraid. I get:
Collecting scikit-image>=0.17.2
Downloading scikit_image-0.19.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (14.0 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 14.0/14.0 MB 82.5 MB/s eta 0:00:00
Collecting torch>=1.10.1
Downloading https://download.pytorch.org/whl/cu117/torch-1.13.0%2Bcu117-cp38-cp38-linux_x86_64.whl (1806.8 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.8/1.8 GB 96.7 MB/s eta 0:00:00
Collecting torchvision>=0.11.2
Downloading https://download.pytorch.org/whl/cu117/torchvision-0.14.0%2Bcu117-cp38-cp38-linux_x86_64.whl (24.3 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 24.3/24.3 MB 82.7 MB/s eta 0:00:00
ERROR: Could not find a version that satisfies the requirement detectron2>=0.6 (from versions: none)
ERROR: No matching distribution found for detectron2>=0.6
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Looking in links: https://dl.fbaipublicfiles.com/detectron2/wheels/cu117/torch1.10/index.html, https://download.pytorch.org/whl/cu117/torch_stable.html
Collecting detectron2==0.6
Cloning https://github.com/facebookresearch/detectron2 (to revision v0.6) to /tmp/pip-install-onelriyc/detectron2_aa9a864f0fa24ef58c4a7ee45be7edd2
Running command git clone --filter=blob:none --quiet https://github.com/facebookresearch/detectron2 /tmp/pip-install-onelriyc/detectron2_aa9a864f0fa24ef58c4a7ee45be7edd2
Running command git checkout -q d1e04565d3bec8719335b88be9e9b961bf3ec464
Resolved https://github.com/facebookresearch/detectron2 to commit d1e04565d3bec8719335b88be9e9b961bf3ec464
Preparing metadata (setup.py) ... error
error: subprocess-exited-with-error
× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> [6 lines of output]
Traceback (most recent call last):
File "<string>", line 2, in <module>
File "<pip-setuptools-caller>", line 34, in <module>
File "/tmp/pip-install-onelriyc/detectron2_aa9a864f0fa24ef58c4a7ee45be7edd2/setup.py", line 10, in <module>
import torch
ModuleNotFoundError: No module named 'torch'
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed
× Encountered error while generating package metadata.
╰─> See above for output.
Facebook Research has obviously failed to set up the package in a way that either torch
becomes a build-time dependency, or is not needed by setuptools:
EDIT: just found this issue describing the problem
I am at a loss what we should do going forward TBH.
https://github.com/bertsky/ocrd_detectron2/pull/11/commits/a82513e673902107de999ab803b7be7a22a078c7 should be sufficient. So #11 now is the fix – I hope :crossed_fingers:
It seems the latest versions we can get any
detectron2
for are:detectron==0.6
[Python 3.6-3.9]detectron==0.6
[Python 3.6-3.9]detectron==0.5
[Python 3.6-3.8]detectron==0.6
[Python 3.6-3.9]detectron==0.6
[Python 3.6-3.9]detectron==0.2.1
[Python 3.6-3.8]What a mess! So as with Tensorflow, older CUDA versions quickly tend to not get supported. It's not as bad regarding Python version ranges, but CUDA 10.0 – which still is OCR-D's main target platform for CUDA builds – is out.