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Awesome GitHub RepositoriesTraining Hooks
Customizable callback mechanisms for modifying model state or weight updates during the training loop.
Distinguishing note: Focuses on the implementation of custom hooks for weight updates, such as exponential moving averages.
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Awesome Training Hooks 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
Enables registering custom logic to execute at specific lifecycle points during training, validation, or testing.
Pythoncascade-rcnnconvnextdetr
