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mindspore.ops.matrix_solve

mindspore.ops.matrix_solve(matrix, rhs, adjoint=False)[source]

Solves systems of linear equations.

matrix[...,M,M]x[...,M,K]=rhs[...,M,K]adjoint(matrix[...,M,M])x[...,M,K]=rhs[...,M,K]

Warning

On GPU, if the matrix is irreversible, an error may be reported or an unknown result may be returned.

Parameters
  • matrix (Tensor) – The shape of tensor is [...,M,M].

  • rhs (Tensor) – The shape of tensor is [...,M,K]. rhs must have the same dtype as matrix.

  • adjoint (bool) – Indicating whether to solve with matrix or its (block-wise) adjoint. Default: False.

Returns

The dtype and shape is the same as ‘rhs’.

Return type

x (Tensor)

Raises
  • TypeError – If adjoint is not the type of bool.

  • TypeError – If the type of matrix is not one of the following dtype: mstype.float16, mstype.float32, mstype.float64, mstype.complex64, mstype.complex128.

  • TypeError – If the type of matrix is not the same as that of rhs.

  • ValueError – If the rank of matrix less than 2.

  • ValueError – If the dimension of matrix is not the same as rhs.

  • ValueError – If the inner-most 2 dimension of matrix is not the same.

  • ValueError – If the inner-most 2 dimension of rhs does not match matrix.

  • ValueError – If the matrix is irreversible.

Supported Platforms:

GPU CPU

Examples

>>> matrix = Tensor([[5, 4], [3, 1]], mindspore.float32)
>>> rhs = Tensor([[7], [2]], mindspore.float32)
>>> result = ops.matrix_solve(matrix, rhs)
>>> print(result)
[[0.14285707]
 [1.5714287 ]]