784d00f0c38fb5fd77aed0a6dffb93cc98a0c990,gpytorch/likelihoods/gaussian_likelihood.py,GaussianLikelihood,pyro_sample_y,#GaussianLikelihood#Any#Any#Any#Any#,87

Before Change

            noise = noise.squeeze(0)
        y_lazy_covar = DiagLazyTensor(var_f + noise.expand_as(var_f))
        y_dist = MultivariateNormal(y_mean, y_lazy_covar)
        if len(y_dist.batch_shape):
            y_dist = y_dist.__class__(
                y_dist.mean.contiguous().view(-1), BlockDiagLazyTensor(y_dist.lazy_covariance_matrix)
            )
            y_obs = y_obs.view_as(y_dist.mean)
        pyro.sample(name_prefix + "._training_labels", y_dist, obs=y_obs)

After Change

        y_dist = pyro.distributions.Independent(
            pyro.distributions.Normal(y_mean, (var_f + noise.expand_as(var_f)).sqrt()),
            reinterpreted_batch_ndims=y_mean.dim(),
        )

        // See if we"re using a sampled GP distribution

Instances