Minibatch ADVI ppc dimensions

Questions
2

Hi,
And thanks for the kind words, always nice to hear :slight_smile:

You want PPC back with the shape (16770, 50), right? Did you try not passing samples explicitly to sample_posterior_predictive? I think it’ll automatically default to the number of samples in the train set.

Also, I don’t think you need total_size=len(df) in your likelihood: since you’re passing observations, it should pick the shape up automatically.

Finally, note that since PyMC 3.9.0, you can replace:

corr_multi_packed = pm.LKJCholeskyCov(
        'corr_multi', 
        n = cov_dims, 
        eta = 5., 
        sd_dist = sigma_multi_effects
)
corr_multi_effects = pm.expand_packed_triangular(cov_dims, corr_multi_packed)

by the simple one-liner:

# PyMC >= 3.9 extracts the expanded Cholesky, stds and matrix of correlations automatically
corr_multi_effects, Rho, sigmas = pm.LKJCholeskyCov(
        "corr_multi", n=cov_dims, eta=5, sd_dist=sigma_multi_effects, compute_corr=True
    )

Hope this helps :vulcan_salute: