tf.matrix_inverse
tf.matrix_inverse
tf.matrix_inverse
matrix_inverse( input, adjoint=None, name=None )
Defined in tensorflow/python/ops/gen_linalg_ops.py
.
See the guide: Math > Matrix Math Functions
Computes the inverse of one or more square invertible matrices or their
adjoints (conjugate transposes).
The input is a tensor of shape [..., M, M]
whose inner-most 2 dimensions form square matrices. The output is a tensor of the same shape as the input containing the inverse for all input submatrices [..., :, :]
.
The op uses LU decomposition with partial pivoting to compute the inverses.
If a matrix is not invertible there is no guarantee what the op does. It may detect the condition and raise an exception or it may simply return a garbage result.
Args:
-
input
: ATensor
. Must be one of the following types:float64
,float32
. Shape is[..., M, M]
. -
adjoint
: An optionalbool
. Defaults toFalse
. -
name
: A name for the operation (optional).
Returns:
A Tensor
. Has the same type as input
. Shape is [..., M, M]
.
numpy compatibility
Equivalent to np.linalg.inv
© 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_inverse