5f078112011a66a93432cb6d38c03935a10f382e,tensorly/decomposition/candecomp_parafac.py,,non_negative_parafac,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,427

Before Change

            denominator = tl.clip(denominator, a_min=epsilon, a_max=None)
            factor = factors[mode] * numerator / denominator
            
            if normalize_factors:
                weights = tl.norm(factor, order=2, axis=0)
                weights = tl.where(tl.abs(weights) <= tl.eps(tensor.dtype), 
                                   tl.ones(tl.shape(weights), **tl.context(factors[0])),
                                   weights)
                factor = factor/(tl.reshape(weights, (1, -1)))

            factors[mode] = factor

        if tol:
            // ||tensor - rec||^2 = ||tensor||^2 + ||rec||^2 - 2*<tensor, rec>

After Change

            factors[mode] = factor

        if normalize_factors:
            weights, factors = kruskal_normalise((weights, factors))

        if tol:
            // ||tensor - rec||^2 = ||tensor||^2 + ||rec||^2 - 2*<tensor, rec>

Instances