tf.matrix_solve(matrix, rhs, adjoint=None, name=None)

tf.matrix_solve(matrix, rhs, adjoint=None, name=None)

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. Shape is [..., M, K].

Defined in tensorflow/python/ops/gen_linalg_ops.py.