Source: pytorch-sparse Version: 0.6.17-1 Severity: serious Tags: ftbfs sid trixie Justification: fails to build from source (but built successfully in the past) X-Debbugs-Cc: sramac...@debian.org
https://buildd.debian.org/status/fetch.php?pkg=pytorch-sparse&arch=arm64&ver=0.6.17-1&stamp=1694243524&raw=0 =================================== FAILURES =================================== ________________________ test_spmm[dtype5-device5-sum] _________________________ dtype = torch.float32, device = device(type='cpu'), reduce = 'sum' @pytest.mark.parametrize('dtype,device,reduce', product(grad_dtypes, devices, reductions)) def test_spmm(dtype, device, reduce): if device == torch.device('cuda:0') and dtype == torch.bfloat16: return # Not yet implemented. src = torch.randn((10, 8), dtype=dtype, device=device) src[2:4, :] = 0 # Remove multiple rows. src[:, 2:4] = 0 # Remove multiple columns. src = SparseTensor.from_dense(src).requires_grad_() row, col, value = src.coo() other = torch.randn((2, 8, 2), dtype=dtype, device=device, requires_grad=True) src_col = other.index_select(-2, col) * value.unsqueeze(-1) expected = torch_scatter.scatter(src_col, row, dim=-2, reduce=reduce) if reduce == 'min': expected[expected > 1000] = 0 if reduce == 'max': expected[expected < -1000] = 0 grad_out = torch.randn_like(expected) expected.backward(grad_out) expected_grad_value = value.grad value.grad = None expected_grad_other = other.grad other.grad = None out = matmul(src, other, reduce) out.backward(grad_out) atol = 1e-7 if dtype == torch.float16 or dtype == torch.bfloat16: atol = 1e-1 assert torch.allclose(expected, out, atol=atol) assert torch.allclose(expected_grad_value, value.grad, atol=atol) > assert torch.allclose(expected_grad_other, other.grad, atol=atol) E assert False E + where False = <built-in method allclose of type object at 0xffff8bbd1d90>(tensor([[[-1.2813e+00, -1.5149e+00],\n [-5.9411e-02, -3.7580e-01],\n [ 0.0000e+00, 0.0000e+00],\n ...e+00],\n [ 1.9554e+00, 2.9660e+00],\n [-2.2483e+00, -2.2663e+00],\n [ 4.1025e-03, -9.0971e-01]]]), tensor([[[-1.2813e+00, -1.5149e+00],\n [-5.9411e-02, -3.7580e-01],\n [ 0.0000e+00, 0.0000e+00],\n ...e+00],\n [ 1.9554e+00, 2.9660e+00],\n [-2.2483e+00, -2.2663e+00],\n [ 4.1023e-03, -9.0971e-01]]]), atol=1e-07) E + where <built-in method allclose of type object at 0xffff8bbd1d90> = torch.allclose E + and tensor([[[-1.2813e+00, -1.5149e+00],\n [-5.9411e-02, -3.7580e-01],\n [ 0.0000e+00, 0.0000e+00],\n ...e+00],\n [ 1.9554e+00, 2.9660e+00],\n [-2.2483e+00, -2.2663e+00],\n [ 4.1023e-03, -9.0971e-01]]]) = tensor([[[ 4.5925e-01, -1.0188e+00],\n [ 1.6147e-03, 1.0610e+00],\n [-1.3520e+00, -9.0994e-01],\n ...0452e-01, 7.3244e-01],\n [-1.1243e+00, 6.4083e-01],\n [ 6.1791e-01, 2.0024e-01]]], requires_grad=True).grad test/test_matmul.py:51: AssertionError =============================== warnings summary =============================== .pybuild/cpython3_3.11_torch-sparse/build/test/test_matmul.py::test_spspmm[dtype1-device1] /<<PKGBUILDDIR>>/.pybuild/cpython3_3.11_torch-sparse/build/torch_sparse/matmul.py:97: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at ./aten/src/ATen/SparseCsrTensorImpl.cpp:54.) C = torch.sparse.mm(A, B) -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html =========================== short test summary info ============================ FAILED test/test_matmul.py::test_spmm[dtype5-device5-sum] - assert False Cheers -- Sebastian Ramacher