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python312Packages.torch-geometric: skip failing test on darwin (#350200)

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Sandro 2024-10-22 13:19:41 +02:00 committed by GitHub
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1 changed files with 20 additions and 13 deletions
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33
pkgs/development/python-modules/torch-geometric/default.nix
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@ -1,5 +1,6 @@
{
lib,
stdenv,
buildPythonPackage,
fetchFromGitHub,
@ -153,21 +154,27 @@ buildPythonPackage rec {
export HOME=$(mktemp -d)
'';
disabledTests = [
# TODO: try to re-enable when triton will have been updated to 3.0
# torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised:
# LoweringException: ImportError: cannot import name 'triton_key' from 'triton.compiler.compiler'
"test_compile_hetero_conv_graph_breaks"
"test_compile_multi_aggr_sage_conv"
disabledTests =
[
# TODO: try to re-enable when triton will have been updated to 3.0
# torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised:
# LoweringException: ImportError: cannot import name 'triton_key' from 'triton.compiler.compiler'
"test_compile_hetero_conv_graph_breaks"
"test_compile_multi_aggr_sage_conv"
# RuntimeError: addmm: computation on CPU is not implemented for SparseCsr + SparseCsr @ SparseCsr without MKL.
# PyTorch built with MKL has better support for addmm with sparse CPU tensors.
"test_asap"
"test_graph_unet"
# RuntimeError: addmm: computation on CPU is not implemented for SparseCsr + SparseCsr @ SparseCsr without MKL.
# PyTorch built with MKL has better support for addmm with sparse CPU tensors.
"test_asap"
"test_graph_unet"
# AttributeError: type object 'Any' has no attribute '_name'
"test_type_repr"
];
# AttributeError: type object 'Any' has no attribute '_name'
"test_type_repr"
]
++ lib.optionals stdenv.hostPlatform.isDarwin [
# This test uses `torch.jit` which might not be working on darwin:
# RuntimeError: required keyword attribute 'value' has the wrong type
"test_traceable_my_conv_with_self_loops"
];
meta = {
description = "Graph Neural Network Library for PyTorch";