UniformTuckerTensorTrain.apply

t3toolbox.uniform_tucker_tensor_train.UniformTuckerTensorTrain.apply(vecs)

def apply(
        self,
        vecs:  Sequence[NDArray],  # len=d, ith elm_shape=vec_stack+(Ni,)
) -> NDArray:                      # shape=vec_stack+stack_shape (a scalar per stack element)

Contract the represented tensor with vectors in all modes, without forming it (shares ut3_apply(); a scalar per stack element).

Precondition-free (exact for any cores). Uniform mirror of apply().

Examples

>>> import numpy as np
>>> import t3toolbox.tucker_tensor_train as t3
>>> import t3toolbox.uniform_tucker_tensor_train as ut3
>>> np.random.seed(0)
>>> x = ut3.UniformTuckerTensorTrain.from_t3(t3.TuckerTensorTrain.randn((10, 11, 12), (5, 6, 4), (1, 2, 3, 1)))
>>> ww = (np.random.randn(10), np.random.randn(11), np.random.randn(12))
>>> print(bool(np.allclose(x.apply(ww), np.einsum('ijk,i,j,k->', x.to_dense(), *ww))))
True

Parameters:

vecs (Sequence[NDArray])

Return type:

NDArray