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# tf.linalg.logdet

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

``````# 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
``````

`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`.

The natural log of the determinant of `matrix`.

#### Numpy Compatibility

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

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