TorchGeo 0.6.0-foss-2023a

TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data.

Accessing TorchGeo 0.6.0-foss-2023a

To load the module for TorchGeo 0.6.0-foss-2023a please use this command on the BEAR systems (BlueBEAR and BEAR Cloud VMs):

📋 module load bear-apps/2023a
module load TorchGeo/0.6.0-foss-2023a

There is a GPU enabled version of this module: TorchGeo 0.6.0-foss-2023a-CUDA-12.1.1

BEAR Apps Version

2023a

Architectures

EL8-cascadelake — EL8-icelake — EL8-sapphirerapids

The listed architectures consist of two part: OS-CPU. The OS used is represented by EL and there are several different processor (CPU) types available on BlueBEAR. More information about the processor types on BlueBEAR is available on the BlueBEAR Job Submission page.

Extensions

• aenum 3.1.15
• affine 2.4.0
• antlr4-python3-runtime-4.9.3
• click-plugins-1.1.1
• cligj 0.7.2
• efficientnet_pytorch 0.7.1
• huggingface_hub 0.24.6
• hydra-core-1.3.2
• kornia 0.7.3
• kornia_rs 0.1.5
• laspy 2.5.4
• lightly 1.5.12
• lightly_utils 0.0.2
• omegaconf 2.3.0
• pretrainedmodels 0.7.4
• rasterio 1.3.9
• safetensors 0.4.4
• segmentation_models_pytorch 0.3.4
• snuggs 1.4.7
• timm 0.9.7
• TorchGeo 0.6.0

More Information

For more information visit the TorchGeo website.

Dependencies

This version of TorchGeo has a direct dependency on: einops/0.7.0-GCCcore-12.3.0 Fiona/1.9.5-foss-2023a foss/2023a GDAL/3.7.1-foss-2023a h5py/3.9.0-foss-2023a Lightning/2.2.1-foss-2023a matplotlib/3.7.2-gfbf-2023a OpenCV/4.8.1-foss-2023a-contrib pyproj/3.6.0-GCCcore-12.3.0 Python/3.11.3-GCCcore-12.3.0 PyTorch/2.1.2-foss-2023a PyTorch-Lightning/2.2.1-foss-2023a Rtree/1.2.0-GCCcore-12.3.0 scikit-image/0.22.0-foss-2023a SciPy-bundle/2023.07-gfbf-2023a Shapely/2.0.1-gfbf-2023a torchvision/0.16.0-foss-2023a

Other Versions

These versions of TorchGeo are available on the BEAR systems (BlueBEAR and BEAR Cloud VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Last modified on 4th September 2024