diff --git a/easybuild/easyconfigs/p/pytorch-3dunet/pytorch-3dunet-1.6.0-foss-2022a-CUDA-11.7.0.eb b/easybuild/easyconfigs/p/pytorch-3dunet/pytorch-3dunet-1.6.0-foss-2022a-CUDA-11.7.0.eb new file mode 100644 index 00000000000..7e56318d66d --- /dev/null +++ b/easybuild/easyconfigs/p/pytorch-3dunet/pytorch-3dunet-1.6.0-foss-2022a-CUDA-11.7.0.eb @@ -0,0 +1,57 @@ +# Thomas Hoffmann, EMBL Heidelberg, structures-it@embl.de, 2023/11 +easyblock = 'PythonBundle' + +name = 'pytorch-3dunet' +version = '1.6.0' +versionsuffix = '-CUDA-%(cudaver)s' + +homepage = 'https://github.com/wolny/pytorch-3dunet' +description = """ +PyTorch implementation of 3D U-Net and its variants: + - UNet3D: Standard 3D U-Net based on 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation + - ResidualUNet3D: Residual 3D U-Net based on Superhuman Accuracy on the SNEMI3D + Connectomics Challenge + - ResidualUNetSE3D: Similar to ResidualUNet3D with the addition of Squeeze and + Excitation blocks based on Deep Learning Semantic Segmentation for High- + Resolution Medical Volumes. Original squeeze and excite paper: Squeeze-and- + Excitation Networks +The code allows for training the U-Net for both: semantic segmentation (binary +and multi-class) and regression problems (e.g. de-noising, learning +deconvolutions). +""" +toolchain = {'name': 'foss', 'version': '2022a'} + +builddependencies = [ + ('pkgconf', '1.8.0'), + ('cppy', '1.2.1') +] + +dependencies = [ + ('Python', '3.10.4'), + ('SciPy-bundle', '2022.05'), + ('CUDA', '11.7.0', '', SYSTEM), + ('PyTorch', '1.12.0', versionsuffix), + ('h5py', '3.7.0'), + ('tensorboard', '2.10.0'), + ('scikit-image', '0.19.3'), +] + +use_pip = True +sanity_pip_check = True + +github_account = 'wolny' +exts_list = [ + (name, version, { + 'modulename': 'pytorch3dunet', + 'source_urls': [GITHUB_SOURCE], + 'sources': ['%(version)s.tar.gz'], + 'checksums': ['5323eb8a31ad95c17a3e3d83e3de08b0d3cdd0841b28687aa41039355706b659'], + }), +] + +sanity_check_commands = [ + "train3dunet --help", + "predict3dunet --help" +] + +moduleclass = 'ai'