mindspore.ops.cholesky

mindspore.ops.cholesky(input_x, upper=False)

Return the Cholesky decomposition of zero or more batch dimensions consisting of symmetric positive-definite matrices.

If upper is True, return an upper-triangular matrix, $U$, and the decomposition has the form:

$$A=U^{T}U$$

If upper is False, return a lower-triangular matrix, $L$, and the decomposition has the form:

$$A=L{L}^T$$

where A is the symmetric positive-definite matrix.

Parameters

• input_x (Tensor) – The input tensor of shape $(\ast ,N,N)$, where $\ast$ is batch dimensions. In the above formula, $A$ .

• upper (bool, optional) – Return an upper-triangular matrix or not. Default: False .

Returns

Tensor

Supported Platforms:

GPU CPU

Examples

>>> import mindspore
>>> input_x = mindspore.tensor([[1.0, 1.0], [1.0, 2.0]])
>>> output = mindspore.ops.cholesky(input_x, upper=False)
>>> print(output)
[[1. 0.]
 [1. 1.]]