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 log_normalizer F(\theta) based the natural parameters.
docstr_tok: ["Return","the","log_normalizer","F","(","\\theta",")","based","the","natural","parameters","."]
code: def _log_normalizer(self, *natural_params):
      r"""
      Return the log_normalizer F(\theta) based the natural parameters.
      """
      raise NotImplementedError
  
imports: from .distribution import Distribution
label_desc: Use image node_id 2 for calling the ExponentialFamily obj's underlying member method code with example usage: obj._log_normalizer() without return types