class_docstr: ExponentialFamily inherits from Distribution. ExponentialFamily is a base
  class for distributions whose density function has the form:
  p_F(x;\theta) = exp(
      <t(x), \theta> -
      F(\theta) +
      k(x)
  ) where
  t(x): sufficient statistics
  \theta: natural parameters
  F(\theta): log_normalizer
  k(x): carrier measure
docstr: Return the mean of carrier measure k(x) based on input x,
  this method is required for calculating the entropy.
docstr_tok: ["Return","the","mean","of","carrier","measure","k","(","x",")","based","on","input","x",",","this","method","is","required","for","calculating","the","entropy","."]
code: def _mean_carrier_measure(self, x):
      r"""
      Return the mean of carrier measure k(x) based on input x,
      this method is required for calculating the entropy.
      """
      raise NotImplementedError
  
imports: from .distribution import Distribution
label_desc: Use image node_id 3 for calling the ExponentialFamily obj's underlying member method code with example usage: obj._mean_carrier_measure(x) without return types