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Merge pull request #15830 from easybuilders/4.6.x
release EasyBuild v4.6.0
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37 changes: 37 additions & 0 deletions
37
easybuild/easyconfigs/a/Albumentations/Albumentations-1.1.0-foss-2021a-CUDA-11.3.1.eb
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| Original file line number | Diff line number | Diff line change |
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| easyblock = 'PythonBundle' | ||
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| name = 'Albumentations' | ||
| version = '1.1.0' | ||
| versionsuffix = '-CUDA-11.3.1' | ||
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| homepage = 'https://albumentations.ai' | ||
| description = "Albumentations is a Python library for fast and flexible image augmentations" | ||
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| toolchain = {'name': 'foss', 'version': '2021a'} | ||
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| dependencies = [ | ||
| ('Python', '3.9.5'), | ||
| ('SciPy-bundle', '2021.05'), | ||
| ('PyYAML', '5.4.1'), | ||
| ('scikit-image', '0.18.3'), | ||
| ('scikit-learn', '0.24.2'), | ||
| ('OpenCV', '4.5.3', versionsuffix + '-contrib'), | ||
| ('imgaug', '0.4.0', versionsuffix), | ||
| ] | ||
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| preinstallopts = "sed -i 's|CHOOSE_INSTALL_REQUIRES),|[]),|g' setup.py && " | ||
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| use_pip = True | ||
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| exts_list = [ | ||
| ('qudida', '0.0.4', { | ||
| 'checksums': ['db198e2887ab0c9aa0023e565afbff41dfb76b361f85fd5e13f780d75ba18cc8'], | ||
| }), | ||
| ('albumentations', version, { | ||
| 'checksums': ['60b067b3093908bcc52adb2aa5d44f57ebdbb8ab57a47b0b42f3dc1d3b1ce824'], | ||
| }), | ||
| ] | ||
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| sanity_pip_check = True | ||
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| moduleclass = 'vis' |
195 changes: 195 additions & 0 deletions
195
easybuild/easyconfigs/a/AlphaFold/AlphaFold-2.2.2-foss-2021a-CUDA-11.3.1.eb
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| Original file line number | Diff line number | Diff line change |
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| easyblock = 'PythonBundle' | ||
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| name = 'AlphaFold' | ||
| version = '2.2.2' | ||
| versionsuffix = '-CUDA-%(cudaver)s' | ||
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| homepage = 'https://deepmind.com/research/case-studies/alphafold' | ||
| description = "AlphaFold can predict protein structures with atomic accuracy even where no similar structure is known" | ||
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| toolchain = {'name': 'foss', 'version': '2021a'} | ||
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| builddependencies = [ | ||
| # CMake/Doxygen/SWIG are required for building OpenMM | ||
| ('CMake', '3.20.1'), | ||
| ('Doxygen', '1.9.1'), | ||
| # required for installing dm-tree | ||
| ('Bazel', '3.7.2'), | ||
| ('SWIG', '4.0.2'), | ||
| ] | ||
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| dependencies = [ | ||
| ('Python', '3.9.5'), | ||
| ('CUDA', '11.3.1', '', True), | ||
| ('SciPy-bundle', '2021.05'), | ||
| ('PyYAML', '5.4.1'), | ||
| ('TensorFlow', '2.6.0', versionsuffix), | ||
| ('Biopython', '1.79'), | ||
| ('HH-suite', '3.3.0'), | ||
| ('HMMER', '3.3.2'), | ||
| ('Kalign', '3.3.1'), | ||
| ('jax', '0.3.9', versionsuffix), # also provides absl-py | ||
| ('UCX-CUDA', '1.10.0', versionsuffix), | ||
| ('cuDNN', '8.2.1.32', versionsuffix, True), | ||
| ('NCCL', '2.10.3', versionsuffix), | ||
| ] | ||
| local_openmm_preinstallopts = "export OPENMM_INCLUDE_PATH=%(installdir)s/include && " | ||
| local_openmm_preinstallopts += " export OPENMM_LIB_PATH=%(installdir)s/lib && " | ||
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| # required to install OpenMM Python API; | ||
| # avoid that setup.py partially uninstalls existing OpenMM Python bindings... | ||
| local_openmm_installopts = " && cd python && sed -i 's/uninstall()/pass/g' setup.py && " | ||
| local_openmm_installopts += "python setup.py build && python setup.py install --prefix=%(installdir)s" | ||
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| # commit to use for downloading stereo_chemical_props.txt and copy to alphafold/common, | ||
| # see docker/Dockerfile in AlphaFold repository | ||
| local_scp_commit = '7102c6' | ||
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| components = [ | ||
| # for simtk | ||
| ('OpenMM', '7.5.1', { | ||
| 'easyblock': 'CMakeMake', | ||
| 'source_urls': ['https://github.com/openmm/openmm/archive/'], | ||
| 'sources': [{'download_filename': '%(version)s.tar.gz', 'filename': SOURCE_TAR_GZ}], | ||
| 'patches': [('OpenMM-%(version)s_AlphaFold.patch', 'wrappers/python')], | ||
| 'checksums': [ | ||
| 'c88d6946468a2bde2619acb834f57b859b5e114a93093cf562165612e10f4ff7', # OpenMM-7.5.1.tar.gz | ||
| '1b109dfff3af5c6aa70690bca14618612953c68840a7e64f679db7ca33c1aff6', # OpenMM-7.5.1_AlphaFold.patch | ||
| ], | ||
| 'start_dir': 'openmm-%(version)s', | ||
| 'preinstallopts': local_openmm_preinstallopts, | ||
| 'installopts': local_openmm_installopts, | ||
| }), | ||
| (name, version, { | ||
| 'easyblock': 'PythonPackage', | ||
| 'source_urls': [ | ||
| 'https://github.com/deepmind/alphafold/archive/refs/tags/', | ||
| 'https://git.scicore.unibas.ch/schwede/openstructure/-/raw/%s/modules/mol/alg/src/' % local_scp_commit, | ||
| ], | ||
| 'sources': [ | ||
| { | ||
| 'download_filename': 'v%(version)s.tar.gz', | ||
| 'filename': SOURCE_TAR_GZ, | ||
| }, | ||
| { | ||
| 'download_filename': 'stereo_chemical_props.txt', | ||
| 'filename': 'stereo_chemical_props-%s.txt' % local_scp_commit, | ||
| 'extract_cmd': "cp %s .", | ||
| }, | ||
| ], | ||
| 'patches': [ | ||
| 'AlphaFold-2.0.0_fix-packages.patch', | ||
| 'AlphaFold-2.1.2_data-dep-paths.patch', | ||
| 'AlphaFold-2.0.0_n-cpu.patch', | ||
| 'AlphaFold-2.1.0_fix-scp-path.patch', | ||
| 'AlphaFold-2.0.1_setup_rm_tfcpu.patch', | ||
| ], | ||
| 'checksums': [ | ||
| 'aa51dc4a1150b92310d20e63e9e4d9279b15b6a1f7e664360f52827f83256cdd', # v2.2.2.tar.gz | ||
| '24510899eeb49167cffedec8fa45363a4d08279c0c637a403b452f7d0ac09451', # stereo_chemical_props-7102c6.txt | ||
| '826d2d1a5d6ac52c51a60ba210e1947d5631a1e2d76f8815305b5d23f74458db', # AlphaFold-2.0.0_fix-packages.patch | ||
| '6af91706b2a001494ddc0947f89f8b3d3adfcc26177c373824fe8ea1a58c0b48', # AlphaFold-2.1.2_data-dep-paths.patch | ||
| 'dfda4dd5f9aba19fe2b6eb9a0ec583d12dcefdfee8ab8803fc57ad48d582db04', # AlphaFold-2.0.0_n-cpu.patch | ||
| '5363d403baf5ab73f4d3ddd72e19af9ff832de4b1d7ba25a5fbcc5846c1c890f', # AlphaFold-2.1.0_fix-scp-path.patch | ||
| '1a2e4e843bd9a4d15ee39e6c37cc63ba281311cc7a0a5610f0e43b52ef93faac', # AlphaFold-2.0.1_setup_rm_tfcpu.patch | ||
| ], | ||
| 'start_dir': 'alphafold-%(version)s', | ||
| 'use_pip': True, | ||
| }), | ||
| ] | ||
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| use_pip = True | ||
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| exts_list = [ | ||
| ('PDBFixer', '1.7', { | ||
| 'source_urls': ['https://github.com/openmm/pdbfixer/archive/refs/tags/'], | ||
| 'sources': [{'download_filename': 'v%(version)s.tar.gz', 'filename': '%(name)s-%(version)s.tar.gz'}], | ||
| 'checksums': ['a0bef3c52a7bbe69a6aea5333f51f3e7d158339be5829aed19b0344bd66d4eea'], | ||
| }), | ||
| ('toolz', '0.11.2', { | ||
| 'checksums': ['6b312d5e15138552f1bda8a4e66c30e236c831b612b2bf0005f8a1df10a4bc33'], | ||
| }), | ||
| ('chex', '0.1.3', { | ||
| 'checksums': ['2cfa6ccd02addd6b113658d03bd5ce8a7b3bd24fa62e746a246073414ea1e103'], | ||
| }), | ||
| ('tabulate', '0.8.10', { | ||
| 'checksums': ['6c57f3f3dd7ac2782770155f3adb2db0b1a269637e42f27599925e64b114f519'], | ||
| }), | ||
| ('jmp', '0.0.2', { | ||
| 'preinstallopts': "touch requirements.txt && touch requirements-test.txt && ", | ||
| 'checksums': ['fdb5cec0d10aab4116c2770f24b2adf4f503fcfbb96ce8ef583e1879bdbf1b9b'], | ||
| }), | ||
| ('dm-haiku', '0.0.6', { | ||
| 'modulename': 'haiku', | ||
| 'source_urls': ['https://github.com/deepmind/dm-haiku/archive/refs/tags/'], | ||
| 'sources': [{'download_filename': 'v%(version)s.tar.gz', 'filename': '%(name)s-%(version)s.tar.gz'}], | ||
| 'checksums': ['bb038d7b6eae50ad8b59aecaad7b26180261f155c9a789d071133cb2596dc616'], | ||
| }), | ||
| ('dm-tree', '0.1.7', { | ||
| 'modulename': 'tree', | ||
| 'checksums': ['30fec8aca5b92823c0e796a2f33b875b4dccd470b57e91e6c542405c5f77fd2a'], | ||
| }), | ||
| ('websocket-client', '1.3.3', { | ||
| 'modulename': 'websocket', | ||
| 'checksums': ['d58c5f284d6a9bf8379dab423259fe8f85b70d5fa5d2916d5791a84594b122b1'], | ||
| }), | ||
| ('docker', '5.0.3', { | ||
| 'checksums': ['d916a26b62970e7c2f554110ed6af04c7ccff8e9f81ad17d0d40c75637e227fb'], | ||
| }), | ||
| ('immutabledict', '2.2.1', { | ||
| 'checksums': ['1ddb0edf1bb6c70d0197eb90ce1fe2b2d58502334f5fdfde72d7c633d723ec3a'], | ||
| }), | ||
| ('contextlib2', '21.6.0', { | ||
| 'checksums': ['ab1e2bfe1d01d968e1b7e8d9023bc51ef3509bba217bb730cee3827e1ee82869'], | ||
| }), | ||
| ('ml_collections', '0.1.1', { | ||
| 'preinstallopts': "touch requirements.txt && touch requirements-test.txt && ", | ||
| 'checksums': ['3fefcc72ec433aa1e5d32307a3e474bbb67f405be814ea52a2166bfc9dbe68cc'], | ||
| }), | ||
| ] | ||
|
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| postinstallcmds = [ | ||
| "mkdir -p %(installdir)s/bin", | ||
| # run_alphafold.py script is missing a shebang... | ||
| "echo '#!/usr/bin/env python' > %(installdir)s/bin/run_alphafold.py", | ||
| "cat %(builddir)s/alphafold-%(version)s/run_alphafold.py >> %(installdir)s/bin/run_alphafold.py", | ||
| "chmod a+x %(installdir)s/bin/run_alphafold.py", | ||
| "cd %(installdir)s/bin && ln -s run_alphafold.py alphafold", | ||
| "cp -a %(builddir)s/alphafold-%(version)s/scripts %(installdir)s/", | ||
| "cp %%(builddir)s/stereo_chemical_props-%s.txt %%(installdir)s/stereo_chemical_props.txt" % local_scp_commit, | ||
| # run tests for run_alphafold.py script; | ||
| # shouldn't do this in sanity check to avoid breaking use of --module-only | ||
| "PYTHONPATH=%(installdir)s/lib/python%(pyshortver)s/site-packages:$PYTHONPATH " | ||
| "python %(builddir)s/alphafold-%(version)s/run_alphafold_test.py", | ||
| ] | ||
|
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| sanity_check_paths = { | ||
| 'files': ['bin/alphafold', 'bin/pdbfixer', 'bin/run_alphafold.py', 'lib/libOpenMM.%s' % SHLIB_EXT, | ||
| 'lib/python%(pyshortver)s/site-packages/simtk/openmm/openmm.py', 'stereo_chemical_props.txt'], | ||
| 'dirs': ['lib/python%(pyshortver)s/site-packages', 'scripts'], | ||
| } | ||
|
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| sanity_check_commands = [ | ||
| "pdbfixer --help", | ||
| "python -m simtk.testInstallation", | ||
| "python -c 'import alphafold'", | ||
| "alphafold --help 2>&1 | grep 'Full AlphaFold protein structure prediction script'", | ||
| ] | ||
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| sanity_pip_check = True | ||
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| modextrapaths = { | ||
| 'OPENMM_INCLUDE_PATH': 'include', | ||
| 'OPENMM_LIB_PATH': 'lib', | ||
| } | ||
|
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| # these allow to make predictions on proteins that would typically be too long to fit into GPU memory; | ||
| # see https://github.com/deepmind/alphafold/blob/main/docker/run_docker.py | ||
| modextravars = { | ||
| 'TF_FORCE_UNIFIED_MEMORY': '1', | ||
| 'XLA_PYTHON_CLIENT_MEM_FRACTION': '4.0', | ||
| # 'ALPHAFOLD_DATA_DIR': '/path/to/AlphaFold_DBs', # please adapt | ||
| 'OPENMM_RELAX': 'CUDA' # unset or set to 'CPU' in order not to run the energy minimization on GPU; PR#189 | ||
| } | ||
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| moduleclass = 'bio' |
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