tf.linalg.solve  |  TensorFlow v2.16.1 (original) (raw)

Solves systems of linear equations.

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Compat aliases for migration

SeeMigration 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 satisfiesadjoint(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.