stan-dev/stan

Exposing mu to the services (stepsize warmup)

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#2,670 opened on Oct 18, 2018

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Description

Summary:

Regarding the parameters of the dual averaging optimization for the stepsize in the warmup, all parameters can be set by the user except mu. For certain models, the initial choice of mu can result in a drastic drop of the stepsize for subsequent iterations. This might lead to extra computation time. As mu is adjusted for each window of the mass matrix adjustment, this can in effect add a significant amount of computation time.

Description:

Currently, mu is set to be log(10 * this->nom_epsilon_) which is hardcoded in the algorithm, and the services stan::services::sample::hmc_static_dense_e_adapt, stan::services::sample::hmc_static_diag_e_adapt, stan::services::sample::hmc_nuts_dense_e_adapt and stan::services::sample::hmc_nuts_diag_e_adapt do not expose the factor of epsilon to the user. This issue would entail

  • updating the services API,
  • adding the factor as an attribute to stan::mcmc::stepsize_adaptation with the corresponding getter and setter and
  • updating the corresponding parts in stan::mcmc::adapt_dense_e_nuts, stan::mcmc::adapt_diag_e_nuts, stan::mcmc::adapt_dense_e_static_hmc and stan::mcmc::adapt_diag_e_static_hmc.

There are also the equivalent algorithms in nuts_classic, static_uniform and xhmc.

The default factor of 10 should be kept.

Additional Information:

Issues in Rstan, Pystan and CmdStan would have to be opened as well.

Current Version:

v2.18.0

Contributor guide

Tech stack
cpp
Domain
backend
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-2 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
C++Stan codebaseMCMC algorithms
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
25
Research direction
Start by examining the current implementation in `stan::mcmc::stepsize adaptation` where `mu` is hardcoded. Then update the adapter classes `adapt dense e nuts`, `adapt diag e nuts`, `adapt dense e static hmc`, and `adapt diag e static hmc` to accept a new factor parameter. Modify the service functions `stan::services::sample::hmc * adapt` to expose this parameter. Finally, create corresponding issues in Rstan, Pystan, and CmdStan to propagate the change to higher level interfaces.
Exposing mu to the services (stepsize warmup) · stan-dev/stan#2670 | Good First Issue