Experiment_Management_System.md

graph LR
    ExperimentRunner["ExperimentRunner"]
    LearningRateScheduler["LearningRateScheduler"]
    ExperimentRunner -- "utilizes" --> LearningRateScheduler

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Details

The Experiment Management System subsystem is primarily defined by the experiments package, specifically encompassing the functionalities implemented in experiments/main.py and experiments/lr_scheduler.py. This subsystem is responsible for orchestrating the training and evaluation lifecycle of machine learning models within the xLSTM project.

ExperimentRunner

This component orchestrates the entire lifecycle of a single experiment run. It handles the initialization of the model, data loaders, optimizers, and the training loop. It also manages evaluation, logging, and checkpointing.

Related Classes/Methods:

• experiments/main.py

LearningRateScheduler

This component provides mechanisms for dynamically adjusting the learning rate of an optimizer during the training process. It encapsulates various scheduling strategies.

Related Classes/Methods:

• experiments/lr_scheduler.py

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