# tf.linalg.inv

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Computes the inverse of one or more square invertible matrices or their adjoints (conjugate transposes).

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.linalg.inv`](https://www.tensorflow.org/api_docs/python/tf/linalg/inv), [`tf.compat.v1.matrix_inverse`](https://www.tensorflow.org/api_docs/python/tf/linalg/inv)

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    tf.linalg.inv(
        input, adjoint=False, name=None
    )

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.

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| ## 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). |

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| ## Returns ||
|---|---|
| A `Tensor`. Has the same type as `input`. ||

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