pytorch/ignite

Add no improvement handler (similar to early stopping handler)

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#2,314 opened on Nov 9, 2021

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 (8 comments) (0 reactions) (1 assignee)Python (4,313 stars) (602 forks)batch import
enhancementhelp wanted

Description

🚀 Feature

To add a 'no-improvement' handler. It's similar to early stopping, except that early stopping calls the training to terminate, 'no-improvement' handler would've calls a function that user pass in. User could pass in different functions that they want to execute if they find no improvements is made. They may want to try various things before terminate the training.

Contributor guide

Tech stack
pythonpytorch
Domain
machine learning
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
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.
blocked
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
Knowledge of PyTorch Ignite handlersUnderstanding of early stopping handler
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
50
Research direction
Examine the existing early stopping handler implementation in PyTorch Ignite (likely in ignite/handlers/early stopping.py). Understand the callback interface and training termination flow. Review comments in issue #2314 for any user proposed function signatures. The goal is to create a handler that triggers a user defined function when no improvement is observed, rather than terminating training. Implementation should mirror early stopping's logic but invoke the callback instead of stopping.