code: def qud_prior():
      values = [
          "price",
          "valence",
          "priceValence",
          "approxPrice",
          "approxPriceValence",
      ]
      ix = pyro.sample(
          "qud",
          dist.Categorical(probs=torch.ones(len(values)) / len(values)),
      )
      return values[ix]
  
file_path: pyro/examples/rsa/hyperbole.py
imports: import argparse
  import collections
  import torch
  from search_inference import HashingMarginal, Search, memoize
  import pyro
  import pyro.distributions
  import pyro.poutine
label_desc: Use image node_id 6 for calling a global function with example usage: qud_prior() and returns: values