code: def _letter(i):
      alphabet = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
      if i < len(alphabet):
          return alphabet[i]
      else:
          raise ValueError(
              "Too many latent variables in"
              "`Marginalizable` distribution."
          )
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import joint_distribution
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.experimental.marginalize.logeinsumexp import logeinsumexp
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
label_desc: Use image node_id 6 for calling a global function with example usage: _letter(i) and returns: alphabet