code: def get_likelihood_model(
      likelihood_model: str, likelihood_parameters: dict[str, Any]
  ) -> Any:
      # Actually returns a Likelihood model, but pytype thinks it returns a
      # Union[NegativeBinomial, ...].
      m = NAME_TO_LIKELIHOOD_MODEL[likelihood_model]()
      for k, v in likelihood_parameters.items():
          if hasattr(m, k):
              setattr(m, k, v)
      return m
  
imports: import dataclasses
  from typing import Any
  import jax
  from tensorflow_probability.substrates.jax.bijectors import softplus
  from tensorflow_probability.substrates.jax.distributions import distribution
  from tensorflow_probability.substrates.jax.distributions import inflated
  from tensorflow_probability.substrates.jax.distributions import logistic
  from tensorflow_probability.substrates.jax.distributions import lognormal
  from tensorflow_probability.substrates.jax.distributions import negative_binomial
  from tensorflow_probability.substrates.jax.distributions import normal
  from tensorflow_probability.substrates.jax.distributions import transformed_distribution
label_desc: Use image node_id 1 for calling a global function with example usage: get_likelihood_model(likelihood_model, likelihood_parameters) and returns: m