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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def normal_mb_neg_loglik(self, beta, mini_batch):
 """ Calculates the negative log-likelihood of the Normal model for a minibatch Parameters beta : np.ndarray Contains untransformed starting values for latent variables mini_batch : int Size of each mini batch of data Returns The negative logliklihood of the model """
     

        mu, Y = self._mb_model(beta, mini_batch)
        return -np.sum(ss.norm.logpdf(Y, loc=mu, scale=self.latent_variables.z_list[-1].prior.transform(beta[-1])))