180 lines
3 KiB
Nix
180 lines
3 KiB
Nix
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{
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lib,
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buildPythonPackage,
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fetchFromGitHub,
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# build-system
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flit-core,
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# dependencies
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aiohttp,
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fsspec,
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jinja2,
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numpy,
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psutil,
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pyparsing,
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requests,
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torch,
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tqdm,
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# optional-dependencies
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matplotlib,
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networkx,
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pandas,
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protobuf,
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wandb,
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ipython,
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matplotlib-inline,
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pre-commit,
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torch-geometric,
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ase,
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# captum,
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graphviz,
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h5py,
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numba,
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opt-einsum,
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pgmpy,
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pynndescent,
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# pytorch-memlab,
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rdflib,
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rdkit,
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scikit-image,
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scikit-learn,
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scipy,
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statsmodels,
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sympy,
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tabulate,
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torchmetrics,
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trimesh,
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pytorch-lightning,
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yacs,
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huggingface-hub,
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onnx,
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onnxruntime,
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pytest,
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pytest-cov,
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# tests
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pytestCheckHook,
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}:
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buildPythonPackage rec {
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pname = "torch-geometric";
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version = "2.6.1";
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pyproject = true;
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src = fetchFromGitHub {
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owner = "pyg-team";
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repo = "pytorch_geometric";
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rev = "refs/tags/${version}";
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hash = "sha256-Zw9YqPQw2N0ZKn5i5Kl4Cjk9JDTmvZmyO/VvIVr6fTU=";
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};
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build-system = [
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flit-core
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];
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dependencies = [
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aiohttp
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fsspec
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jinja2
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numpy
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psutil
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pyparsing
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requests
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torch
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tqdm
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];
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optional-dependencies = {
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benchmark = [
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matplotlib
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networkx
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pandas
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protobuf
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wandb
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];
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dev = [
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ipython
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matplotlib-inline
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pre-commit
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torch-geometric
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];
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full = [
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ase
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# captum
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graphviz
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h5py
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matplotlib
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networkx
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numba
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opt-einsum
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pandas
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pgmpy
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pynndescent
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# pytorch-memlab
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rdflib
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rdkit
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scikit-image
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scikit-learn
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scipy
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statsmodels
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sympy
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tabulate
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torch-geometric
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torchmetrics
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trimesh
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];
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graphgym = [
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protobuf
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pytorch-lightning
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yacs
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];
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modelhub = [
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huggingface-hub
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];
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test = [
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onnx
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onnxruntime
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pytest
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pytest-cov
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];
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};
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pythonImportsCheck = [
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"torch_geometric"
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];
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nativeCheckInputs = [
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pytestCheckHook
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];
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preCheck = ''
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export HOME=$(mktemp -d)
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'';
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disabledTests = [
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# TODO: try to re-enable when triton will have been updated to 3.0
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# torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised:
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# LoweringException: ImportError: cannot import name 'triton_key' from 'triton.compiler.compiler'
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"test_compile_hetero_conv_graph_breaks"
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"test_compile_multi_aggr_sage_conv"
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# RuntimeError: addmm: computation on CPU is not implemented for SparseCsr + SparseCsr @ SparseCsr without MKL.
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# PyTorch built with MKL has better support for addmm with sparse CPU tensors.
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"test_asap"
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"test_graph_unet"
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# AttributeError: type object 'Any' has no attribute '_name'
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"test_type_repr"
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];
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meta = {
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description = "Graph Neural Network Library for PyTorch";
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homepage = "https://github.com/pyg-team/pytorch_geometric";
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changelog = "https://github.com/pyg-team/pytorch_geometric/blob/${src.rev}/CHANGELOG.md";
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license = lib.licenses.mit;
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maintainers = with lib.maintainers; [ GaetanLepage ];
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};
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}
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