Welcome to the MLE-Infrastructure 🔬
|Experiment Logging||Parameter Searches||Experiment Launch||Experiment Protocol||Experiment Manager|
The MLE-Infrastructure provides a reproducible workflow for distributed Machine Learning experimentation (MLE) with minimal engineering overhead. The core consists of 5 packages:
mle-logging: Experiment logging with easy multi-seed and configuration aggregation.
mle-hyperopt: Hyperparameter Optimization with config export, refinement & reloading.
mle-monitor: Monitor cluster/cloud VM resource utilization & protocol experiments.
mle-scheduler: Schedule & monitor jobs on Slurm, GridEngine clusters & GCP VMs.
mle-toolbox: Glues everything together to manage & post-process experiments.