tf.linalg.inv | TensorFlow v2.16.1 (original) (raw)
tf.linalg.inv
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Computes the inverse of one or more square invertible matrices or their adjoints (conjugate transposes).
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Compat aliases for migration
SeeMigration guide for more details.
tf.compat.v1.linalg.inv, tf.compat.v1.matrix_inverse
tf.linalg.inv(
input: Annotated[Any, TV_MatrixInverse_T], adjoint: bool = False, name=None
) -> Annotated[Any, TV_MatrixInverse_T]
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. |