code: def speaker1(state, threshold, prior):
      s1Optimality = 5.0
      utterance = utterance_prior()
      L0 = listener0(utterance, threshold, prior)
      with poutine.scale(scale=torch.tensor(s1Optimality)):
          pyro.sample("L0_score", L0, obs=state)
      return utterance
  
file_path: pyro/examples/rsa/generics.py
imports: import argparse
  import collections
  import numbers
  import torch
  from search_inference import HashingMarginal, Search, memoize
  import pyro
  import pyro.distributions
  import pyro.poutine
label_desc: Use image node_id 8 for calling a global function with example usage: speaker1(state, threshold, prior) and returns: utterance