A Simple Demonstration of Experiment Results Tracking Using MLflow and Hydra

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1. Prerequisite knowledge

What is MLflow?

MLflow is a tool that helps people manage and track their machine-learning projects. It provides a way to organize, document, and compare different machine-learning experiments and models. In this article, we focus on the experiment-tracking feature of MLflow.

What is Hydra?

Hydra, developed by Facebook AI Research, serves as a hyperparameter management tool. If you’re new to this library, we recommend the following article for your introduction.

Why Should We Use Hydra for Effective Program Parameter Management?

2. An example combining MLflow with Hydra

Hydra YAML config.yaml

# config.yaml
learning_rate: 0.001
batch_size: 64
num_epochs: 10
mlflow_tracking_uri_dir: "file:///home/person_name/project/mlruns"

In the YAML file, we define the program’s arguments, which are often related to algorithm parameter settings.

Python script

import hydra
from…