Bug#1053302: pytorch-sparse: FTBFS on arm64

[Sebastian Ramacher]

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: sramacher at 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