class_docstr: The logit-normal distribution.
class_docstr_tok: ["The","logit-normal","distribution","."]
docstr: Largest scale using Gauss-Hermite quadrature in `*_approx` functions.
docstr_tok: ["Largest","scale","using","Gauss-Hermite","quadrature","in","`","*","_approx","`","functions","."]
code: def gauss_hermite_scale_limit(self):
      """Largest scale using Gauss-Hermite quadrature in `*_approx` functions."""
      return self._gauss_hermite_scale_limit
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.math import special
label_desc: Use image node_id 6 for calling the LogitNormal obj's underlying member method code with example usage: obj.gauss_hermite_scale_limit() and returns: self