Loading pkgs/development/python-modules/torch-geometric/default.nix +18 −10 Original line number Diff line number Diff line Loading @@ -57,6 +57,8 @@ # tests pytestCheckHook, writableTmpDirAsHomeHook, pythonAtLeast, }: buildPythonPackage rec { Loading Loading @@ -148,20 +150,11 @@ buildPythonPackage rec { nativeCheckInputs = [ pytestCheckHook writableTmpDirAsHomeHook ]; preCheck = '' export HOME=$(mktemp -d) ''; disabledTests = [ # TODO: try to re-enable when triton will have been updated to 3.0 # torch._dynamo.exc.BackendCompilerFailed: backend='inductor' raised: # LoweringException: ImportError: cannot import name 'triton_key' from 'triton.compiler.compiler' "test_compile_hetero_conv_graph_breaks" "test_compile_multi_aggr_sage_conv" # RuntimeError: addmm: computation on CPU is not implemented for SparseCsr + SparseCsr @ SparseCsr without MKL. # PyTorch built with MKL has better support for addmm with sparse CPU tensors. "test_asap" Loading @@ -174,6 +167,21 @@ buildPythonPackage rec { # This test uses `torch.jit` which might not be working on darwin: # RuntimeError: required keyword attribute 'value' has the wrong type "test_traceable_my_conv_with_self_loops" ] ++ lib.optionals (pythonAtLeast "3.13") [ # RuntimeError: Dynamo is not supported on Python 3.13+ "test_compile" # RuntimeError: Python 3.13+ not yet supported for torch.compile "test_compile_graph_breaks" "test_compile_multi_aggr_sage_conv" "test_compile_hetero_conv_graph_breaks" # AttributeError: module 'typing' has no attribute 'io'. Did you mean: 'IO'? "test_packaging" # RuntimeError: Boolean value of Tensor with more than one value is ambiguous "test_feature_store" ]; meta = { Loading Loading
pkgs/development/python-modules/torch-geometric/default.nix +18 −10 Original line number Diff line number Diff line Loading @@ -57,6 +57,8 @@ # tests pytestCheckHook, writableTmpDirAsHomeHook, pythonAtLeast, }: buildPythonPackage rec { Loading Loading @@ -148,20 +150,11 @@ buildPythonPackage rec { nativeCheckInputs = [ pytestCheckHook writableTmpDirAsHomeHook ]; preCheck = '' export HOME=$(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" # 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" Loading @@ -174,6 +167,21 @@ buildPythonPackage rec { # 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" ] ++ lib.optionals (pythonAtLeast "3.13") [ # RuntimeError: Dynamo is not supported on Python 3.13+ "test_compile" # RuntimeError: Python 3.13+ not yet supported for torch.compile "test_compile_graph_breaks" "test_compile_multi_aggr_sage_conv" "test_compile_hetero_conv_graph_breaks" # AttributeError: module 'typing' has no attribute 'io'. Did you mean: 'IO'? "test_packaging" # RuntimeError: Boolean value of Tensor with more than one value is ambiguous "test_feature_store" ]; meta = { Loading