tf.linalg.inv
Computes the inverse of one or more square invertible matrices or their
tf.linalg.inv(
input, adjoint=False, name=None
)
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 |
A Tensor. Must be one of the following types: float64, float32, half, complex64, complex128. Shape is [..., M, M]. |
adjoint |
An optional bool. Defaults to False. |
name |
A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor. Has the same type as input. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/linalg/inv