Commits on Feb 23, 2022

1. Enabling algorithm-specific default num_adaptive_samples …

   Summary:
   The number of adaptive samples for all algorithm is set to 0 by default, which is okay for algorithms like ancestral MH or NMC, but not for HMC and NUTS. Per our previous discussion, instead of using the same default value for all algorithms, a better solution is to let each algorithm determine how many adaptive iterations are necessary. For compositional inference, it will look up the number of adaptive samples required by each inference method in the config and default to the maximum among them (see [Option 3 in Warmup Design](https://fb.quip.com/jzFvAai8ogWV#temp:C:WMIc97e2ffd843b4ab19bbe40c7c) for details).
   
   This diff implement this idea by introducing a `_get_default_num_adaptive_samples` private method on `BaseInference`, which is default to 0. Algorithms can override the default behavior by overloading the method.
   
   Differential Revision: D34404061
   
   fbshipit-source-id: 5c073abb3abb993cf96ba5ef13e0923e859e6b09

   

   horizon-blue authored and facebook-github-bot committed Feb 23, 2022
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