dpnp.linalg.tensorinv

dpnp.linalg.tensorinv(a, ind=2)

Compute the 'inverse' of an N-dimensional array.

For full documentation refer to numpy.linalg.tensorinv.

Parameters:

• a ({dpnp.ndarray, usm_ndarray}) -- Tensor to invert. Its shape must be 'square', i. e., prod(a.shape[:ind]) == prod(a.shape[ind:]).

• ind (int, optional) -- Number of first indices that are involved in the inverse sum. Must be a positive integer. Default: 2.

Returns:

out -- The inverse of a tensor whose shape is equivalent to a.shape[ind:] + a.shape[:ind].

Return type:

dpnp.ndarray

See also

dpnp.linalg.tensordot

Compute tensor dot product along specified axes.

dpnp.linalg.tensorsolve

Solve the tensor equation a x = b for x.

Examples

>>> import dpnp as np
>>> a = np.eye(4*6)
>>> a.shape = (4, 6, 8, 3)
>>> ainv = np.linalg.tensorinv(a, ind=2)
>>> ainv.shape
(8, 3, 4, 6)

>>> a = np.eye(4*6)
>>> a.shape = (24, 8, 3)
>>> ainv = np.linalg.tensorinv(a, ind=1)
>>> ainv.shape
(8, 3, 24)