t3_weighted_inner#

t3toolbox.tucker_tensor_train.t3_weighted_inner(x_A, weights_A, x_B, weights_B, use_orthogonalization=True)#
def t3_weighted_inner(
        x_A:       'TuckerTensorTrain',
        weights_A: T3Weights,
        x_B:       'TuckerTensorTrain',
        weights_B: T3Weights,

        use_orthogonalization: bool = True,   # for numerical stability (as the backend / uniform twins)
) -> NDArray:  # weighted HS inner product, shape=stack_shape

Weighted Hilbert-Schmidt inner product of two weighted Tucker tensor trains <absorb_weights(x_A, weights_A), absorb_weights(x_B, weights_B)>. Operands share physical shape; ranks/weights may differ (each pair checked separately).

Parameters:
Return type:

NDArray