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Original file line number Diff line number Diff line change
@@ -0,0 +1,43 @@
easyblock = 'PythonBundle'

name = 'LightlySSL'
version = '1.5.22'
versionsuffix = '-CUDA-%(cudaver)s'

homepage = 'https://docs.lightly.ai/self-supervised-learning/'
description = """
LightlySSL is a computer vision framework for self-supervised learning.
With LightlySSL you can train deep learning models using self-supervision. This means, that you
don’t require any labels to train a model. LightlySSL has been built to help you understand and work
with large unlabeled datasets. It is built on top of PyTorch and therefore fully compatible with
other frameworks such as Fast.ai.
"""

toolchain = {'name': 'foss', 'version': '2025a'}

dependencies = [
('Python', '3.13.1'),
('CUDA', '12.8.0', '', SYSTEM),
('SciPy-bundle', '2025.06'),
('PyTorch', '2.9.1', f'{versionsuffix}-whl'),
('PyTorch-bundle', '2.9.1', f'{versionsuffix}-whl'),
('PyTorch-Lightning', '2.6.1', versionsuffix),
# optional
('pydantic', '2.11.7'),
('matplotlib', '3.10.3'),
('timm', '1.0.24', versionsuffix),
]

exts_list = [
('aenum', '3.1.16', {
'checksums': ['bfaf9589bdb418ee3a986d85750c7318d9d2839c1b1a1d6fe8fc53ec201cf140'],
}),
('lightly_utils', '0.0.2', {
'checksums': ['a351f3d600f0ab08d12f294725c6457ae000645cb0a1083d0845cb196ccfe698'],
}),
('lightly', version, {
'checksums': ['7bb8939976ea5e8fabb20d049812700d51e44f6461f15510a784afd1252a3dbd'],
}),
]

moduleclass = 'geo'
41 changes: 41 additions & 0 deletions easybuild/easyconfigs/l/LightlySSL/LightlySSL-1.5.22-foss-2025a.eb
Original file line number Diff line number Diff line change
@@ -0,0 +1,41 @@
easyblock = 'PythonBundle'

name = 'LightlySSL'
version = '1.5.22'

homepage = 'https://docs.lightly.ai/self-supervised-learning/'
description = """
LightlySSL is a computer vision framework for self-supervised learning.
With LightlySSL you can train deep learning models using self-supervision. This means, that you
don’t require any labels to train a model. LightlySSL has been built to help you understand and work
with large unlabeled datasets. It is built on top of PyTorch and therefore fully compatible with
other frameworks such as Fast.ai.
"""

toolchain = {'name': 'foss', 'version': '2025a'}

dependencies = [
('Python', '3.13.1'),
('SciPy-bundle', '2025.06'),
('PyTorch', '2.9.1', '-whl'),
('PyTorch-bundle', '2.9.1', '-whl'),
('PyTorch-Lightning', '2.6.1'),
# optional
('pydantic', '2.11.7'),
('matplotlib', '3.10.3'),
('timm', '1.0.24'),
]

exts_list = [
('aenum', '3.1.16', {
'checksums': ['bfaf9589bdb418ee3a986d85750c7318d9d2839c1b1a1d6fe8fc53ec201cf140'],
}),
('lightly_utils', '0.0.2', {
'checksums': ['a351f3d600f0ab08d12f294725c6457ae000645cb0a1083d0845cb196ccfe698'],
}),
('lightly', version, {
'checksums': ['7bb8939976ea5e8fabb20d049812700d51e44f6461f15510a784afd1252a3dbd'],
}),
]

moduleclass = 'geo'
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