Solves systems of linear equations with upper or lower triangular matrices by backsubstitution.
tf.raw_ops.MatrixTriangularSolve(
matrix, rhs, lower=True, adjoint=False, name=None
)
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, N].
The output is a tensor of shape [..., M, N]. If adjoint is
True then the innermost matrices in output satisfy matrix equations
matrix[..., :, :] * output[..., :, :] = rhs[..., :, :].
If adjoint is False then the strictly then the innermost matrices in
output satisfy matrix equations
adjoint(matrix[..., i, k]) * output[..., k, j] = rhs[..., i, j].
Note, the batch shapes for the inputs only need to broadcast.
Example:
a = tf.constant([[3, 0, 0, 0],
[2, 1, 0, 0],
[1, 0, 1, 0],
[1, 1, 1, 1]], dtype=tf.float32)
b = tf.constant([[4],
[2],
[4],
[2]], dtype=tf.float32)
x = tf.linalg.triangular_solve(a, b, lower=True)
x
# <tf.Tensor: shape=(4, 1), dtype=float32, numpy=
# array([[ 1.3333334 ],
# [-0.66666675],
# [ 2.6666665 ],
# [-1.3333331 ]], dtype=float32)>
# in python3 one can use `a@x`
tf.matmul(a, x)
# <tf.Tensor: shape=(4, 1), dtype=float32, numpy=
# array([[4. ],
# [2. ],
# [4. ],
# [1.9999999]], dtype=float32)>
Args |
|---|
matrix
Tensor. Must be one of the following types: bfloat16, float64, float32, half, complex64, complex128.
Shape is [..., M, M].
rhs
Tensor. Must have the same type as matrix.
Shape is [..., M, K].
lower
bool. Defaults to True.
Boolean indicating whether the innermost matrices in matrix are
lower or upper triangular.
adjoint
bool. Defaults to False.
Boolean indicating whether to solve with matrix or its (block-wise)
adjoint.
name
Returns | |
|---|---|
A Tensor. Has the same type as matrix.
|
numpy compatibility
Equivalent to scipy.linalg.solve_triangular