TraceGraph_ELBO implementation using provenance tracking #1412
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fehiepsi
reviewed
May 27, 2022
fehiepsi
reviewed
May 27, 2022
fehiepsi
reviewed
May 27, 2022
ordabayevy
commented
May 28, 2022
| """ | ||
| Returns log probabilities at each site for the guide and the model that is run against it. | ||
| """ | ||
| model_tr, guide_tr = get_importance_trace(model, guide, args, kwargs, params) |
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Changed since yesterday: Instead of manually tracing guide and then replaying/tracing model I changed this to just reuse the get_importance_trace function.
ordabayevy
commented
May 28, 2022
ordabayevy
commented
May 28, 2022
ordabayevy
commented
May 28, 2022
added 3 commits
May 28, 2022 09:22
|
@fehiepsi per our discussion added the tests back and fixed the |
fehiepsi
reviewed
May 30, 2022
| and (not msg["fn"].has_rsample) | ||
| ): | ||
| new_provenance = frozenset({msg["name"]}) | ||
| old_provenance = msg["value"].aval.named_shape.get( |
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Could you add a comment that this is intended to be used in eval_provenance
numpyro/infer/elbo.py
Outdated
| surrogate = jnp.sum( | ||
| guide_site["log_prob"] * stop_gradient(downstream_cost) | ||
| ) | ||
| elbo += surrogate - stop_gradient(surrogate) |
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nit: in jax it is clearer to use elbo = elbo + (...)
added 2 commits
May 30, 2022 22:01
|
Thanks Du for reviewing my first PR to NumPyro! |
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Porting pyro-ppl/pyro#3081
TraceGraph_ELBOimplementation from Pyro that uses provenance tracking.