# tf.matrix_solve

### Aliases:

• `tf.linalg.solve`
• `tf.matrix_solve`
``````tf.matrix_solve(
matrix,
rhs,
name=None
)
``````

Defined in generated file: `tensorflow/python/ops/gen_linalg_ops.py`.

See the guide: Math > Matrix Math Functions

Solves systems of linear equations.

`Matrix` is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions form square matrices. `Rhs` is a tensor of shape `[..., M, K]`. The `output` is a tensor shape `[..., M, K]`. If `adjoint` is `False` then each output matrix satisfies `matrix[..., :, :] * output[..., :, :] = rhs[..., :, :]`. If `adjoint` is `True` then each output matrix satisfies `adjoint(matrix[..., :, :]) * output[..., :, :] = rhs[..., :, :]`.

#### Args:

• `matrix`: A `Tensor`. Must be one of the following types: `float64`, `float32`, `complex64`, `complex128`. Shape is `[..., M, M]`.
• `rhs`: A `Tensor`. Must have the same type as `matrix`. Shape is `[..., M, K]`.
• `adjoint`: An optional `bool`. Defaults to `False`. Boolean indicating whether to solve with `matrix` or its (block-wise) adjoint.
• `name`: A name for the operation (optional).

#### Returns:

A `Tensor`. Has the same type as `matrix`.