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|
[build-system]
requires=["flit_core >=3.12,<4"]
build-backend="flit_core.buildapi"
[project]
name="torch-geometric"
version="2.7.0"
authors=[
{name="Matthias Fey", email="matthias@pyg.org"},
]
description="Graph Neural Network Library for PyTorch"
readme="README.md"
requires-python=">=3.10"
keywords=[
"deep-learning",
"pytorch",
"geometric-deep-learning",
"graph-neural-networks",
"graph-convolutional-networks",
]
license = "MIT"
license-files = ["LICENSE"]
classifiers=[
"Development Status :: 5 - Production/Stable",
"Programming Language :: Python",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3 :: Only",
]
dependencies=[
"aiohttp",
"fsspec",
"jinja2",
"numpy",
"psutil>=5.8.0",
"pyparsing",
"requests",
"tqdm",
"xxhash",
]
[project.optional-dependencies]
graphgym=[
"protobuf<4.21",
"pytorch-lightning",
"yacs",
]
modelhub=[
"huggingface_hub"
]
benchmark=[
"matplotlib",
"networkx",
"pandas",
"protobuf<4.21",
"wandb",
]
rag=[
"pcst_fast",
"datasets",
"transformers",
"pandas",
"sentencepiece",
"accelerate",
"torchmetrics",
]
test=[
"onnx",
"onnxruntime",
"onnxscript",
"pytest",
"pytest-cov",
]
dev=[
"ipython",
"matplotlib-inline",
"pre-commit",
"torch_geometric[test]",
]
full = [
"scipy",
"scikit-learn",
"ase",
"captum<0.7.0",
"graphviz",
"h5py",
"matplotlib",
"networkx",
"numba<0.60.0",
"opt_einsum",
"pandas",
# See https://github.com/pgmpy/pgmpy/issues/2360.
# "pgmpy",
"pynndescent",
"pytorch-memlab",
"rdflib",
"rdkit",
"scikit-image",
"statsmodels",
"sympy",
"tabulate",
"torch_geometric[graphgym, modelhub]",
"torchmetrics",
"trimesh",
]
[project.urls]
homepage="https://pyg.org"
documentation="https://pytorch-geometric.readthedocs.io"
repository="https://github.com/pyg-team/pytorch_geometric.git"
changelog="https://github.com/pyg-team/pytorch_geometric/blob/master/CHANGELOG.md"
[tool.flit.module]
name="torch_geometric"
[tool.yapf]
based_on_style = "pep8"
split_before_named_assigns = false
blank_line_before_nested_class_or_def = false
[tool.mypy]
files = ["torch_geometric"]
install_types = true
non_interactive = true
ignore_missing_imports = true
show_error_codes = true
warn_redundant_casts = true
warn_unused_configs = true
warn_unused_ignores = true
disallow_untyped_defs = true
disallow_incomplete_defs = true
[[tool.mypy.overrides]]
ignore_errors = true
module = [
"torch_geometric.data.*",
"torch_geometric.sampler.*",
"torch_geometric.loader.*",
"torch_geometric.nn.*",
"torch_geometric.explain.*",
"torch_geometric.profile.*",
"torch_geometric.contrib.*",
"torch_geometric.graphgym.*",
"torch_geometric.distributed.*",
"torch_geometric.llm.*",
]
[tool.isort]
multi_line_output = 3
include_trailing_comma = true
skip = [".gitignore", "__init__.py"]
[tool.ruff] # https://docs.astral.sh/ruff/rules
src = ["torch_geometric"]
line-length = 80
indent-width = 4
target-version = "py310"
[tool.ruff.lint]
select = [
"B", # flake8-bugbear
"D", # pydocstyle
]
ignore = [
"B905", # TODO Don't ignore "zip with strict=False"
"D100", # TODO Don't ignore "Missing docstring in public module"
"D101", # TODO Don't ignore "Missing docstring in public class"
"D102", # TODO Don't ignore "Missing docstring in public method"
"D103", # TODO Don't ignore "Missing docstring in public function"
"D104", # TODO Don't ignore "Missing docstring in public package"
"D105", # Ignore "Missing docstring in magic method"
"D107", # Ignore "Missing docstring in __init__"
"D205", # Ignore "blank line required between summary line and description"
]
[tool.ruff.format]
quote-style = "single"
[tool.ruff.lint.pydocstyle]
convention = "google"
[tool.pytest.ini_options]
addopts = [
"--capture=no",
"--color=yes",
"-vv",
]
filterwarnings = [
"ignore:distutils:DeprecationWarning",
"ignore:'torch_geometric.contrib' contains experimental code:UserWarning",
# Filter `torch` warnings:
"ignore:The PyTorch API of nested tensors is in prototype stage:UserWarning",
"ignore:scatter_reduce():UserWarning",
"ignore:Sparse CSR tensor support is in beta state:UserWarning",
"ignore:Sparse CSC tensor support is in beta state:UserWarning",
"ignore:torch.distributed._sharded_tensor will be deprecated:DeprecationWarning",
# Filter `torch.compile` warnings:
"ignore:pkg_resources is deprecated as an API",
"ignore:Deprecated call to `pkg_resources.declare_namespace",
# Filter `captum` warnings:
"ignore:Setting backward hooks on ReLU activations:UserWarning",
"ignore:.*did not already require gradients, required_grads has been set automatically:UserWarning",
# Filter `pytorch_lightning` warnings:
"ignore:GPU available but not used:UserWarning",
"error::DeprecationWarning",
# TODO(rishipuri98): Remove usage of `torch_geometric.distributed` from `torch_geometric.llm`
"ignore:.*torch_geometric.distributed.*:DeprecationWarning",
]
markers = [
"rag: mark test as RAG test",
]
[tool.coverage.run]
source = ["torch_geometric"]
omit = [
"torch_geometric/distributed/*",
"torch_geometric/datasets/*",
"torch_geometric/data/extract.py",
"torch_geometric/nn/data_parallel.py",
]
[tool.coverage.report]
exclude_lines = [
"pragma: no cover",
"pass",
"raise NotImplementedError",
"register_parameter",
"torch.cuda.is_available",
]
[tool.setuptools]
py-modules = []
|
