solve_ex

→Tensor

solve_ex(A: Tensor, B: Tensor, left: bool = True, check_errors: bool = False)

source

Solve $AX = B$ with an explicit success flag.

Variant of solve that returns an info code instead of raising on a singular coefficient matrix.

info == 0 — success; $X$ is the unique solution.
info != 0 — $A$ was singular; $X$ is zero-filled.

Parameters

ATensor

Coefficient matrix of shape (*, n, n).

BTensor

Right-hand side of shape (*, n, k) (or (*, n)).

left(bool, keyword - only)= True

Currently must be True. False (X A = B) is not yet implemented and raises NotImplementedError.

check_errors(bool, keyword - only)= False

If True, re-raise the underlying engine error instead of emitting a non-zero info.

Returns

Tensor

Solution (or zero placeholder) shaped like B.

Notes

Implementation calls solve under the hood and converts the raised exception into the info flag. This is the recommended form when calling from inside a batched / jit-compiled / vmapped routine where raising would break control flow; manually inspect info afterwards and decide whether to recover.

Examples

>>> import lucid
>>> from lucid.linalg import solve_ex
>>> A = lucid.tensor([[3.0, 1.0], [1.0, 2.0]])
>>> b = lucid.tensor([9.0, 8.0])
>>> X, info = solve_ex(A, b)
>>> int(info)
0