Computes the inverse given the LU decomposition(s) of one or more matrices.
View aliases
Compat aliases for migration
See Migration guide for more details.
tf.linalg.lu_matrix_inverse(
lower_upper, perm, validate_args=False, name=None
)
This op is conceptually identical to,
inv_X = tf.lu_matrix_inverse(*tf.linalg.lu(X))
tf.assert_near(tf.matrix_inverse(X), inv_X)
# ==> True
Args | |
---|---|
lower_upper
|
lu as returned by tf.linalg.lu , i.e., if matmul(P,
matmul(L, U)) = X then lower_upper = L + U - eye .
|
perm
|
p as returned by tf.linag.lu , i.e., if matmul(P, matmul(L, U)) =
X then perm = argmax(P) .
|
validate_args
|
Python bool indicating whether arguments should be checked
for correctness. Note: this function does not verify the implied matrix is
actually invertible, even when validate_args=True .
Default value: False (i.e., don't validate arguments).
|
name
|
Python str name given to ops managed by this object.
Default value: None (i.e., 'lu_matrix_inverse').
|
Examples
import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
x = [[[3., 4], [1, 2]],
[[7., 8], [3, 4]]]
inv_x = tf.linalg.lu_matrix_inverse(*tf.linalg.lu(x))
tf.assert_near(tf.matrix_inverse(x), inv_x)
# ==> True