# tf.linalg.logdet

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/linalg/linalg_impl.py#L68-L99) |

Computes log of the determinant of a hermitian positive definite matrix.

#### View aliases


**Compat aliases for migration**

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

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

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    tf.linalg.logdet(
        matrix, name=None
    )

    # Compute the determinant of a matrix while reducing the chance of over- or
    underflow:
    A = ... # shape 10 x 10
    det = tf.exp(tf.linalg.logdet(A))  # scalar

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| ## Args ||
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| `matrix` | A `Tensor`. Must be `float16`, `float32`, `float64`, `complex64`, or `complex128` with shape `[..., M, M]`. |
| `name` | A name to give this `Op`. Defaults to `logdet`. |

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| ## Returns ||
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| The natural log of the determinant of `matrix`. ||

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## numpy compatibility

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Equivalent to numpy.linalg.slogdet, although no sign is returned since only
hermitian positive definite matrices are supported.

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