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