3cfd3e489b9d5f20027663c3fddbd7759c5831f4,tensorly/decomposition/candecomp_parafac.py,,parafac,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,119

Before Change

            // kr_factors = khatri_rao(factors, skip_matrix=mode)
            // mttkrp = tl.dot(unfolded, kr_factors)

            tensor = tensor*mask + kruskal_to_tensor(factors)*(1 - mask)

            mttkrp_parts = []
            for r in range(rank):
                if verbose:

After Change

                    pseudo_inverse = pseudo_inverse*tl.dot(tl.transpose(factor), factor)

            if mask is not None:
                tensor = tensor*mask + kruskal_to_tensor(factors, mask=1-mask)

            // The below is equivalent to (but more efficient than)

            // unfolded = unfold(tensor, mode)

Instances