tf.linalg.solve

Solves systems of linear equations.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.linalg.solve, tf.compat.v1.matrix_solve

tf.linalg.solve(
    matrix: Annotated[Any, TV_MatrixSolve_T],
    rhs: Annotated[Any, TV_MatrixSolve_T],
    adjoint: bool = False,
    name=None
) -> Annotated[Any, TV_MatrixSolve_T]

Used in the notebooks

Used in the guide	Used in the tutorials
Advanced automatic differentiation	A Tour of TensorFlow Probability

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, half, 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.