pyproject.toml

[project]
name = "mussel"
version = "1.3.3"
description = "weakly supervised computational pathology on whole slide images"
license = { text = "GPL-3.0 license" }
readme = "README.md"
requires-python = ">=3.10, <3.12"  # NOTE: flash-attn prebuilt wheels (see lines 112–113) are only provided for 3.10/3.11; update wheel URLs if raising this upper bound.
dependencies = [
  "pandas",
  "numpy",
  "h5py",
  "matplotlib",
  "tiffslide",
  "opencv-python-headless",
  "hydra-core",
  "geopandas",
  "scikit-learn",
  # NOTE: Upper bound kept in sync with the fastattn extra, which pins transformers==4.36.2
  # and a narrow huggingface-hub range. Relax this once the fastattn stack is updated/tested.
  "transformers<4.46",
  "gdown>=4.6.0",
  "shapely>=2.0.7",
  "einops>=0.8.1",
  "einops-exts>=0.0.4",
  "setuptools",
  "configargparse>=1.7.1",
  "environs",
  "sacremoses",
  "tqdm",
  "pyarrow>=23.0.1",
]

[dependency-groups]
dev = [
    "mypy",
    "isort",
    "black",
    "pytest",
    "pytest-timeout",
    "ipython>=8.37.0",
]

[project.optional-dependencies]
"tensorflow-gpu" = [
  "tensorflow[and-cuda]<=2.19.0",
  "keras",
  "tf-keras",
  "huggingface_hub<0.20",
  "torch < 2.6",
  "torchvision",
  "open-clip-torch",
]
"tensorflow-cpu" = [
  "tensorflow",
  "keras",
  "tf-keras",
  "torch < 2.6",
  "torchvision",
  "open-clip-torch",
]
"torch-cpu" = ["torch < 2.6", "torchvision", "open-clip-torch", "segmentation-models-pytorch"]
"torch-gpu" = ["torch < 2.6", "torchvision", "open-clip-torch", "segmentation-models-pytorch"]
"fastattn" = [
  "gigapath@git+https://github.com/prov-gigapath/prov-gigapath",
  "fairscale",
  "torch==2.11.0",
  "torchvision",
  "xformers>=0.0.34",
  "flash-attn==2.6.3",
  "timm>=1.0.3",
  "omegaconf",
  "torchmetrics==0.10.3",
  "fvcore",
  "iopath",
  "webdataset",
  "lifelines",
  "scikit-survival",
  "wandb",
  "open-clip-torch",
  "ninja==1.11.1.1",
]
"distributed" = [
  "azure-batch",
  "azure-storage-blob",
  "azure-storage-file-share",
  "azure-identity",
  "boto3",
  "fsspec",
  "s3fs",
  "adlfs",
]
"convert" = [
  "pyvips",
  "aicsimageio",
]
"cucim" = [
  "cucim",
]
"zarr" = [
  "zarr",
  "ome-zarr",
]

[tool.uv]
conflicts = [
  # These are mutually exclusive: torch/tensorflow and fastattn pin incompatible torch versions.
  # fastattn uses torch==2.11.0+cu126; torch-gpu/cpu use torch 2.x+cu121/cpu.
  [
    { extra = "tensorflow-gpu" },
    { extra = "tensorflow-cpu" },
    { extra = "torch-cpu" },
    { extra = "torch-gpu" },
    { extra = "fastattn" },
  ],
]

[tool.uv.sources]
torch = [
  { index = "torch-cpu", extra = "tensorflow-gpu" },
  { index = "torch-cpu", extra = "tensorflow-cpu" },
  { index = "torch-cpu", extra = "torch-cpu" },
  { index = "torch-gpu", extra = "torch-gpu" },
  { index = "torch-gpu-cu126", extra = "fastattn" },
]
torchvision = [
  { index = "torch-cpu", extra = "tensorflow-gpu" },
  { index = "torch-cpu", extra = "tensorflow-cpu" },
  { index = "torch-cpu", extra = "torch-cpu" },
  { index = "torch-gpu", extra = "torch-gpu" },
  { index = "torch-gpu-cu126", extra = "fastattn" },
]
xformers = [{ index = "torch-gpu-cu126", extra = "fastattn" }]
flash-attn = [
  { url = "https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/v0.9.4/flash_attn-2.6.3%2Bcu126torch2.11-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", marker = "python_version == '3.11'" },
  { url = "https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/v0.9.4/flash_attn-2.6.3%2Bcu126torch2.11-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", marker = "python_version == '3.10'" },
]

[[tool.uv.index]]
name = "torch-cpu"
url = "https://download.pytorch.org/whl/cpu"
explicit = true

[[tool.uv.index]]
name = "torch-gpu"
url = "https://download.pytorch.org/whl/cu121"
explicit = true

[[tool.uv.index]]
name = "torch-gpu-cu118"
url = "https://download.pytorch.org/whl/cu118"
explicit = true

[[tool.uv.index]]
name = "torch-gpu-cu126"
url = "https://download.pytorch.org/whl/cu126"
explicit = true

[tool.setuptools.packages.find]
include = ["mussel*"]

[build-system]
requires = ["setuptools"]
build-backend = "setuptools.build_meta"

[tool.pytest.ini_options]
addopts = "-v --tb=short --import-mode=importlib"
markers = [
    "slow: marks tests as slow and require significant time to run (deselect with '-m \"not slow\"')",
    "integration: marks integration tests that perform actual model inference",
    "gpu_compatible: marks tests that support --use-gpu flag for faster execution (use the use_gpu fixture to check)",
    "requires_tensorflow: marks tests that require the tensorflow extra (run via tests/slurm/test_tensorflow.sh)",
    "requires_fastattn: marks tests that require the fastattn extra (run via tests/slurm/test_fastattn.sh)",
]

[project.scripts]
annotate = 'mussel.cli.annotate:main'
cache_tiles = 'mussel.cli.cache_tiles:main'
extract_features = 'mussel.cli.extract_features:main'
aggregate_slide_features = 'mussel.cli.aggregate_slide_features:main'
aggregate_sample_features = 'mussel.cli.aggregate_sample_features:main'
filter_features = 'mussel.cli.filter_features:main'
filter_tessellate = 'mussel.cli.filter_tessellate:main'
tessellate = 'mussel.cli.tessellate:main'
tessellate_extract_features = 'mussel.cli.tessellate_extract_features:main'
create_class_embeddings = 'mussel.cli.create_class_embeddings:main'
merge_annotation_features = 'mussel.cli.merge_annotation_features:main'
linear_probe_benchmark = 'mussel.cli.linear_probe_benchmark:main'
export_tiles = 'mussel.cli.export_tiles:main'
save_model = 'mussel.cli.save_model:main'
convert = 'mussel.cli.convert:main'