Increase transparency when setting global input / parameters

Open
#692 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
25/100
Issue type
Refactor
Clarity
Needs clarification
Activity status
Stale
Tech stack
python
Domain
machine-learning

Research direction

Start by tracing the forecaster workflow to find where default inputs and sampling parameters are inserted; no files, tests, or entry points are named in the issue. The desired result is a central, transparent place for these insertion rules, with global constants if needed, and a way for new model developers to see the complete defaults.

Written by the indexing model from the issue text.

Description

enhancement

Right now, we allow insertion of an input to the probabilistic programming dict happen anywhere within the forecaster workflow. However, developer who wants to extend a new model has no visibility what are the full list of default inputs will be inserted. Same story applied to sampling parameters. I wonder if there is any way to maintain a central all-in-one place to operate all those insertion logics. Meanwhile, we can also maintain a global constants to inform this if necessary.

Dominant language
Python
Stars
2.1k
Forks
147
No merged PRs in 30d

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

More from uber/orbit

All issues in uber/orbit

Similar issues

More Python issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.