hiplot-mlflow

A HiPlot experiment fetcher plugin for MLflow, to help visualise your tracked experiments.

Installation

Install this library with pip as:

pip install hiplot_mlflow

Usage

You can visualise experiments either in a Jupyter notebook or using HiPlot's built in server.

Notebook

In a Jupyter notebook, use hiplot_mlflow.fetch to retrieve an MLflow experiment by name, and display it with HiPlot:

import hiplot_mlflow
experiments = hiplot_mlflow.fetch("my-lovely-experiment")
experiments.display(force_full_width=True)

You can also retrieve experiments by their MLflow experiment ID:

experiment = hiplot_mlflow.fetch_by_id(0)

By default, MLflow tags are not shown (only MLflow metrics and parameters are shown). To display them, pass include_tag=True to either of the fetch functions, for example:

experiment = hiplot_mlflow.fetch("my-lovely-experiment", include_tags=True)

See more about what you can do with the returned hiplot.Experiment values in the HiPlot documentation.

HiPlot Server

To use HiPlot's built in webserver with hiplot-mlflow, you can start it up with the custom experiment fetcher implemented by this package:

hiplot hiplot_mlflow.fetch_by_uri

You can then use the mlflow:// schema to access MLflow experiments in HiPlot by either experiment or name, for example:

mlflow://name/experiment-name
mlflow://id/0

You can also add tags=yes as a query string parameter to include tags in the output, for example:

mlflow://name/experiment-name?tags=yes

You can also use the multiple experiments loading syntax. Either the dictionary format (to define your own labels):

multi://{
    "first-experiment": "mlflow://id/1",
    "another-experiment": "mlflow://name/another-experiment?tags=yes"
}

or list format:

multi://[
    "mlflow://id/1",
    "mlflow://name/another-experiment?tags=yes"
]