Problems transforming a pymc3 model to pyro (mcmc)

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First, I find initialization to be quite important in SVI. You might try initializing p_s_loc to data and p_s_scale to either overestimate or underestimate variance

pyro.param("p_s_loc", torch.abs(data_vec).log1p())  # or similar
pyro.param("p_s_scale", 0.1 * torch.ones(N),
           constraint=constraints.positive)

or maybe

pyro.param("p_s_scale", 10.0 * torch.ones(N),
           constraint=constraints.positive)

Second, I believe your guide can be automatically constructed via

guide = pyro.contrib.autoguide.AutoDiagonalNormal(model)

though you would need to interact with it a bit differently.