Computes log of the determinant of a hermitian positive definite matrix.
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
Args |
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 .
|
Returns |
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.