ut3_weighted_norm#

t3toolbox.uniform_tucker_tensor_train.ut3_weighted_norm(x, weights, use_orthogonalization=True)#
def ut3_weighted_norm(x: 'UniformTuckerTensorTrain', weights: UT3Weights,
                  use_orthogonalization: bool = True) -> NDArray:  # shape=stack_shape

Weighted Hilbert-Schmidt norm ||absorb_weights(x, weights)|| (shape stack_shape; a scalar when unstacked). The plain norm squares the inserted diagonal, so diag(1/sigma) penalises by 1/sigma^2. Uniform twin of t3toolbox.tucker_tensor_train.t3_weighted_norm().

Parameters:
Return type:

NDArray