tf.contrib.distributions.quadrature_scheme_lognormal_gauss_hermite(
loc,
scale,
quadrature_size,
validate_args=False,
name=None
)
Defined in tensorflow/contrib/distributions/python/ops/poisson_lognormal.py
.
Use Gauss-Hermite quadrature to form quadrature on positive-reals. (deprecated)
THIS FUNCTION IS DEPRECATED. It will be removed after 2018-10-01.
Instructions for updating:
The TensorFlow Distributions library has moved to TensorFlow Probability (https://github.com/tensorflow/probability). You should update all references to use tfp.distributions
instead of tf.contrib.distributions
.
Args:
loc
:float
-like (batch of) scalarTensor
; the location parameter of the LogNormal prior.scale
:float
-like (batch of) scalarTensor
; the scale parameter of the LogNormal prior.quadrature_size
: Pythonint
scalar representing the number of quadrature points.validate_args
: Pythonbool
, defaultFalse
. WhenTrue
distribution parameters are checked for validity despite possibly degrading runtime performance. WhenFalse
invalid inputs may silently render incorrect outputs.name
: Pythonstr
name prefixed to Ops created by this class.
Returns:
grid
: (Batch of) length-quadrature_size
vectors representing thelog_rate
parameters of aPoisson
.probs
: (Batch of) length-quadrature_size
vectors representing the weight associate with eachgrid
value.