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Awesome GitHub RepositoriesLifecycle Hook Systems
Mechanisms for attaching custom logic to specific stages of an execution loop.
Distinguishing note: Focuses on pluggable event observers within training or inference loops.
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Awesome Lifecycle Hook Systems GitHub Repositories
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- open-mmlab/mmdetection
open-mmlab/mmdetection
32,409View on GitHubThis project is a modular research toolkit designed for developing, training, and evaluating deep learning models for object detection, segmentation, and video instance tracking. It provides a flexible training engine that manages complex neural network execution, including distributed training, custom lifecycle hooks, and weight optimization. The framework is built around a hierarchical configuration system that allows users to define architectures, data pipelines, and training hyperparameters through composable, inheritable files. The project distinguishes itself through its highly modular
Implements a pluggable event system for executing custom logic at specific training or inference stages.
Pythoncascade-rcnnconvnextdetr
