docs: def log_likelihood_top1(data, params):
      """Compute the log-likelihood of model parameters."""
      loglik = 0
      params = np.asarray(params)
      for winner, losers in data:
          idx = np.append(winner, losers)
          loglik -= logsumexp(params.take(idx) - params[winner])
      return loglik