- jax.numpy.linalg.tensorsolve(a, b, axes=None)#
Solve the tensor equation
a x = bfor x.
LAX-backend implementation of
Original docstring below.
It is assumed that all indices of x are summed over in the product, together with the rightmost indices of a, as is done in, for example,
tensordot(a, x, axes=x.ndim).
a (array_like) – Coefficient tensor, of shape
b.shape + Q. Q, a tuple, equals the shape of that sub-tensor of a consisting of the appropriate number of its rightmost indices, and must be such that
prod(Q) == prod(b.shape)(in which sense a is said to be ‘square’).
b (array_like) – Right-hand tensor, which can be of any shape.
axes (tuple of ints, optional) – Axes in a to reorder to the right, before inversion. If None (default), no reordering is done.
- Return type:
ndarray, shape Q