tf.matrix_triangular_solve
tf.matrix_triangular_solve
tf.matrix_triangular_solve
matrix_triangular_solve( matrix, rhs, lower=None, adjoint=None, name=None )
Defined in tensorflow/python/ops/gen_linalg_ops.py
.
See the guide: Math > Matrix Math Functions
Solves systems of linear equations with upper or lower triangular matrices by
backsubstitution.
matrix
is a tensor of shape [..., M, M]
whose inner-most 2 dimensions form square matrices. If lower
is True
then the strictly upper triangular part of each inner-most matrix is assumed to be zero and not accessed. If lower
is False then the strictly lower triangular part of each inner-most matrix is assumed to be zero and not accessed. rhs
is a tensor of shape [..., M, K]
.
The output is a tensor of shape [..., M, K]
. If adjoint
is True
then the innermost matrices in outputsatisfy matrix equations
matrix[..., :, :] * output[..., :, :] = rhs[..., :, :]. If
adjointis
Falsethen the strictly then the innermost matrices in
outputsatisfy matrix equations
adjoint(matrix[..., i, k]) * output[..., k, j] = rhs[..., i, j]`.
Args:
-
matrix
: ATensor
. Must be one of the following types:float64
,float32
. Shape is[..., M, M]
. -
rhs
: ATensor
. Must have the same type asmatrix
. Shape is[..., M, K]
. -
lower
: An optionalbool
. Defaults toTrue
. Boolean indicating whether the innermost matrices inmatrix
are lower or upper triangular. -
adjoint
: An optionalbool
. Defaults toFalse
. Boolean indicating whether to solve withmatrix
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]
.
numpy compatibility
Equivalent to np.linalg.triangular_solve
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/matrix_triangular_solve