class_docstr: A class that knows how to compute the likelihood of some data.
class_docstr_tok: ["A","class","that","knows","how","to","compute","the","likelihood","of","some","data","."]
docstr: Return the distribution underlying the likelihood.
docstr_tok: ["Return","the","distribution","underlying","the","likelihood","."]
code: def dist(self, params, nn_out) -> distribution_lib.Distribution:
      """Return the distribution underlying the likelihood."""
      raise NotImplementedError()
  
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 the LikelihoodModel obj's underlying member method code with example usage: obj.dist(params, nn_out) without return types