MLflow

MLflow enables us to log parameters, code, and results in machine learning experiments and compare them using an interactive UI. This MLflow plugin enables seamless use of MLFlow within Flyte, and render the metrics and parameters on Flyte Deck.

To install the plugin, run the following command:

pip install flytekitplugins-mlflow

Example

from flytekit import task, workflow
from flytekitplugins.mlflow import mlflow_autolog
import mlflow

@task(enable_deck=True)
@mlflow_autolog(framework=mlflow.keras)
def train_model():
    ...