class_docstr: Implements an entropy expectation semiring.
  
  Computes both the log-values and the running distributional entropy.
  
  Based on descriptions in:
  
  * Parameter estimation for probabilistic finite-state transducers :cite:`eisner2002parameter`
  * First-and second-order expectation semirings with applications to minimum-risk training on translation forests :cite:`li2009first`
  * Sample Selection for Statistical Grammar Induction :cite:`hwa2000samplesf`
code: def convert(xs):
      values = torch.zeros((2,) + xs.shape).type_as(xs)
      values[0] = xs
      values[1] = 0
      return values
  
imports: import torch
label_desc: Use image node_id 2 for calling the EntropySemiring obj's underlying member method code with example usage: obj.convert(xs) and returns: values