function

assignment.auto_assignment

def auto_assignment(cost: torch.Tensor, prefer: Prefer | str = Prefer.AUTO) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor]

Solve a single LAP via the empirically-fastest backend.

Parameters

NameTypeDescription
costtorch.Tensor``(N, M)`` cost matrix. May live on any device; non-CUDA paths copy to host transparently.
prefer = Prefer.AUTOPrefer or strBackend preference. See :class:`Prefer`. Default :attr:`Prefer.AUTO`.

Returns

torch.Tensor — ``(K, 2)`` long tensor of matched ``(row, col)`` indices on the input tensor's device.

Raises

  • RuntimeError — If ``prefer="cuda"`` is requested without a CUDA device.

Source: unitrack/assignment/_auto.py:55