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pyproject.toml
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pyproject.toml
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[build-system]
requires=["flit_core >=3.2,<4"]
build-backend="flit_core.buildapi"
[project]
name="torch_geometric"
version="2.4.0"
authors=[
{name="Matthias Fey", email="matthias@pyg.org"},
]
description="Graph Neural Network Library for PyTorch"
readme="README.md"
requires-python=">=3.7"
keywords=[
"deep-learning",
"pytorch",
"geometric-deep-learning",
"graph-neural-networks",
"graph-convolutional-networks",
]
classifiers=[
"Development Status :: 5 - Production/Stable",
"License :: OSI Approved :: MIT License",
"Programming Language :: Python",
"Programming Language :: Python :: 3.7",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3 :: Only",
]
dependencies=[
"tqdm",
"numpy",
"scipy",
"jinja2",
"requests",
"pyparsing",
"scikit-learn",
"psutil>=5.8.0",
]
[project.optional-dependencies]
graphgym=[
"yacs",
"hydra-core",
"protobuf<4.21",
"pytorch-lightning",
]
modelhub=[
"huggingface_hub"
]
benchmark=[
"protobuf<4.21",
"wandb",
"pandas",
"networkx",
"matplotlib",
]
test=[
"pytest",
"pytest-cov",
"onnx",
"onnxruntime",
]
dev=[
"torch_geometric[test]",
"pre-commit",
]
full = [
"torch_geometric[graphgym, modelhub]",
"ase",
"h5py",
"numba",
"sympy",
"pandas",
"captum",
"rdflib",
"trimesh",
"networkx",
"graphviz",
"tabulate",
"matplotlib",
"pynndescent",
"torchmetrics",
"scikit-image",
"pytorch-memlab",
"pgmpy",
"opt_einsum",
"statsmodels",
"rdkit",
]
[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.pyright]
include = ["torch_geometric/utils/*"]
[tool.isort]
multi_line_output = 3
include_trailing_comma = true
skip = [".gitingore", "__init__.py"]
[tool.pytest.ini_options]
addopts = "--capture=no"
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 `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",
]
[tool.pylint.messages_control]
disable = [
"import-outside-toplevel",
"missing-module-docstring",
"missing-class-docstring",
"missing-function-docstring",
"empty-docstring",
"import-error",
"too-many-arguments",
"arguments-differ",
"invalid-name",
"redefined-builtin",
]
attr-rgx = "[A-Za-z_][A-Za-z0-9_]*$"
argument-rgx = "[A-Za-z_][A-Za-z0-9_]*$"
variable-rgx = "[A-Za-z_][A-Za-z0-9_]*$"
generated-members = ["torch.*"]
[tool.coverage.run]
source = ["torch_geometric"]
omit = [
"torch_geometric/datasets/*",
"torch_geometric/data/extract.py",
"torch_geometric/nn/data_parallel.py",
]
[tool.coverage.report]
exclude_lines = [
"pragma: no cover",
"pass",
"raise",
"except",
"register_parameter",
"warn",
"torch.cuda.is_available",
"WITH_PT2",
]
[tool.flake8]
ignore = ["F811", "W503", "W504"]