mindspore.ops.geqrf

mindspore.ops.geqrf(input)[source]

Perform a QR decomposition on the input tensor $A = Q R$ .

The tensor is decomposed into the product of an orthogonal matrix Q and an upper triangular matrix R.

Warning

This is an experimental API that is subject to change or deletion.

Parameters

input (Tensor) – The input tensor.

Returns

Tuple(y, tau) of 2 tensors.

y (Tensor) - Store the matrices Q and R implicitly. The matrix Q (Householder vectors) is stored below the diagonal, and the elements of matrix R are stored on and above the diagonal.
tau (Tensor) - Store the scaling factors of each Householder transformation (Householder reflection coefficients).

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> input = mindspore.tensor([[-2.0, -1.0], [1.0, 2.0]])
>>> y, tau = mindspore.ops.geqrf(input)
>>> print(y)
>>> [[ 2.236068   1.7888544]
>>>  [-0.236068   1.3416407]]
>>> print(tau)
>>> [1.8944271 0.       ]