Merge pull request easybuilders#19290 from ThomasHoffmann77/202311221…

…54122_new_pr_pytorch-3dunet160

{ai}[foss/2022a] pytorch-3dunet v1.6.0 w/ CUDA 11.7.0

easybuild/easyconfigs/p/pytorch-3dunet/pytorch-3dunet-1.6.0-foss-2022a-CUDA-11.7.0.eb

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+# Thomas Hoffmann, EMBL Heidelberg, [email protected], 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'