# tf.raw_ops.SelfAdjointEigV2

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Computes the eigen decomposition of one or more square self-adjoint matrices.

#### View aliases


**Compat aliases for migration**

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

[`tf.compat.v1.raw_ops.SelfAdjointEigV2`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/SelfAdjointEigV2)

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    tf.raw_ops.SelfAdjointEigV2(
        input, compute_v=True, name=None
    )

Computes the eigenvalues and (optionally) eigenvectors of each inner matrix in
`input` such that `input[..., :, :] = v[..., :, :] * diag(e[..., :])`. The eigenvalues
are sorted in non-decreasing order.

    # a is a tensor.
    # e is a tensor of eigenvalues.
    # v is a tensor of eigenvectors.
    e, v = self_adjoint_eig(a)
    e = self_adjoint_eig(a, compute_v=False)

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| ## Args ||
|---|---|
| `input` | A `Tensor`. Must be one of the following types: `float64`, `float32`, `half`, `complex64`, `complex128`. `Tensor` input of shape `[N, N]`. |
| `compute_v` | An optional `bool`. Defaults to `True`. If `True` then eigenvectors will be computed and returned in `v`. Otherwise, only the eigenvalues will be computed. |
| `name` | A name for the operation (optional). |

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| ## Returns ||
|---|---|
| A tuple of `Tensor` objects (e, v). ||
| `e` | A `Tensor`. Has the same type as `input`. |
| `v` | A `Tensor`. Has the same type as `input`. |

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