ut3_corewise_frame#

t3toolbox.backend.ufv_conversions.ut3_corewise_frame(data)#
def ut3_corewise_frame(
        data: typ.Tuple[
            NDArray,                          # tucker_supercore
            NDArray,                          # tt_supercore
            typ.Tuple[int, ...],              # shape
            typ.Tuple[NDArray, NDArray],      # (tucker_edge_mask, tt_edge_mask)
        ],
) -> typ.Tuple:                               # uniform frame .data = (U, G, G, G, shape, masks)

The uniform corewise frame: the twin of t3_corewise_frame(), carrying the (U, G, G, G) supercores and the matching (tucker, tucker, tt, tt) frame mask set.

The mask half is the part worth naming – the corewise frame’s four mask slots are the plain tensor’s two, doubled, and getting that pairing wrong produces a frame that validates but gauges the wrong slots.

Parameters:

data (t3toolbox.backend.common.typ.Tuple[NDArray, NDArray, t3toolbox.backend.common.typ.Tuple[int, ...], t3toolbox.backend.common.typ.Tuple[NDArray, NDArray]])

Return type:

t3toolbox.backend.common.typ.Tuple