UniformTuckerTensorTrain.probe#

t3toolbox.uniform_tucker_tensor_train.UniformTuckerTensorTrain.probe(ww)#

def probe(
        self,
        ww:  Sequence[NDArray],  # len=d, ith elm_shape=W+(Ni,)
) -> Sequence[NDArray]:          # len=d, ith elm_shape=W+stack_shape+(Ni,)

Probe: contract all-but-one mode, for each mode (leaving mode i free), without forming the dense tensor (shares ut3_probe()).

The probe stack W (on ww) is base-inner with the T3 stack: each probe is W + stack_shape + (Ni,). Precondition-free. Uniform mirror of probe().

See also

apply, entries, probe_derivatives

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))
>>> zz = x.probe(ww)
>>> print([z.shape for z in zz])           # one free mode each: (Ni,)
[(10,), (11,), (12,)]
>>> print(bool(np.allclose(zz[0], np.einsum('ijk,j,k->i', x.to_dense(), ww[1], ww[2]))))
True

Parameters:: ww (Sequence[NDArray])
Return type:: Sequence[NDArray]