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Bug
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Resolution: Unresolved
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Undefined
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None
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rhoai-3.2
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None
pDescription of problem:
The latest releases of rasterio, pyproj, shapely, torchgeo, terratorch, timm, mmsegmentation are building fine with Torch 2.9.0. However Fromager is unable to create an installable set of packages. terratorch==1.1.1 depends on an old version of albucore, which indirectly requires numpy<2.0. Other packages requires numpy>2.0
Version numbers (base image, wheels, builder, etc):
Builder 24.8.0 terratorch==1.1.1 albucore==0.0.16 and 0.0.34 albumentations==1.4.10
Steps to Reproduce:
https://gitlab.com/redhat/rhel-ai/core/testcollections/selfservice/-/jobs/12171173440
Actual results:
10:58:52 ERROR jsonargparse: no single version meets all requirements 10:58:52 ERROR numpy: no single version meets all requirements ... albucore 0.0.16 albucore==0.0.16 matches ['0.0.16'] terratorch==1.1.1 0.0.34 albucore>=0.0.11 matches ['0.0.16', '0.0.34'] albumentations==1.4.10 * albucore==0.0.16 usable by all consumers jsonargparse 4.35.0 jsonargparse<=4.35.0 matches ['4.35.0'] terratorch==1.1.1 4.43.0 jsonargparse[signatures]>=4.25 matches ['4.43.0', '4.35.0'] torchgeo==0.7.2 jsonargparse[typing-extensions]; extra == "signatures" matches ['4.43.0', '4.35.0'] jsonargparse==4.43.0 jsonargparse matches ['4.43.0', '4.35.0'] terratorch==1.1.1 jsonargparse[jsonnet,signatures]<5.0,>=4.39.0; extra == "pytorch-extra" matches ['4.43.0'] lightning==2.5.6 * No single version of jsonargparse meets all requirements numpy 1.26.4 numpy<2,>=1.24.4 matches ['1.26.4'] albumentations==1.4.10 2.3.5 numpy>=1.24 matches ['2.3.5', '1.26.4'] scikit-image==0.25.2 rasterio==1.4.3 geopandas==1.1.1 albucore==0.0.16 numpy>=1.21 matches ['2.3.5', '1.26.4'] shapely==2.1.2 numpy matches ['2.3.5', '1.26.4'] imageio==2.37.2 pycocotools==2.0.10 lightly-utils==0.0.2 mmsegmentation==1.2.2 pythran==0.18.1 tifffile==2025.10.16 tensorboardx==2.6.4 pyogrio==0.11.1 torchvision==0.24.0 numpy>=1.18.1 matches ['2.3.5', '1.26.4'] lightly==1.5.22 numpy>1.20.0 matches ['2.3.5', '1.26.4'] torchmetrics==1.8.2 numpy>=1.25 matches ['2.3.5', '1.26.4'] contourpy==1.3.3 numpy>=1.23 matches ['2.3.5', '1.26.4'] matplotlib==3.10.7 numpy>=1.23.2 matches ['2.3.5', '1.26.4'] torchgeo==0.7.1 torchgeo==0.7.2 numpy>=1.26.0; python_version >= "3.12" matches ['2.3.5', '1.26.4'] pandas==2.3.3 opencv-python-headless==4.11.0.86 numpy>=1.19.3 matches ['2.3.5', '1.26.4'] segmentation-models-pytorch==0.5.0 numpy>=1.21.2; python_version >= "3.10" matches ['2.3.5', '1.26.4'] opencv-python-headless==4.11.0.86 numpy>=1.17.0; python_version >= "3.7" matches ['2.3.5', '1.26.4'] opencv-python-headless==4.11.0.86 numpy>=1.17.3; python_version >= "3.8" matches ['2.3.5', '1.26.4'] opencv-python-headless==4.11.0.86 numpy>=1.23.5; python_version >= "3.11" matches ['2.3.5', '1.26.4'] opencv-python-headless==4.11.0.86 numpy>=1.19.3; python_version >= "3.9" matches ['2.3.5', '1.26.4'] opencv-python-headless==4.11.0.86 numpy>=1.24.4 matches ['2.3.5', '1.26.4'] albucore==0.0.34 numpy<2.6,>=1.25.2 matches ['2.3.5', '1.26.4'] scipy==1.16.3 numpy>=1.22.0 matches ['2.3.5', '1.26.4'] scikit-learn==1.7.2 numpy>=1.21.2 matches ['2.3.5', '1.26.4'] h5py==3.15.1 numpy>=2 matches ['2.3.5'] rioxarray==0.20.0 numpy>=1.26 matches ['2.3.5', '1.26.4'] xarray==2025.11.0 numpy>=1.12.0 matches ['2.3.5', '1.26.4'] tensorboard==2.20.0 numpy>=1.17 matches ['2.3.5', '1.26.4'] bitsandbytes==0.48.2 * No single version of numpy meets all requirements torchgeo 0.7.1 torchgeo<0.7.2,>=0.7.0 matches ['0.7.1'] terratorch==1.1.1 0.7.2 * torchgeo==0.7.1 usable by all consumers
Expected results:
Additional info:
- blocks
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AIPCC-4210 Geospatial libraries for RHAIIS
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- In Progress
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