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mlflow

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A minimal, Wolfi-based image for MLflow, an open source platform for the machine learning lifecycle.

Download this Image

The image is available on cgr.dev:

docker pull cgr.dev/chainguard/mlflow:latest

MLflow Usage

MLflow's default entrypoint is Python, enabling us to run experiments directly:

docker run -it cgr.dev/chainguard/mlflow:latest <your experiment>.py

Otherwise, we can override the entrypoint and interact with MLflow:

docker run -it --entrypoint mlflow cgr.dev/chainguard/mlflow:latest <options>

MLflow Tracking Usage

MLflow provides a UI, MLflow Tracking, that allows the user to track 'runs' (the execution of data science code) via visualizations of metrics, parameters, and artifacts.

To start the UI, open a terminal and run:

docker run -it -p 5000:5000 --entrypoint mlflow cgr.dev/chainguard/mlflow:latest ui

While the UI defaults to running on port 5000, you can use a different port via passing -p <PORT> as a command line option. Ensure Docker also maps to the correct port.

You should now be able to access the UI at localhost:5000.

The Tracking API can now be leveraged to record metrics, parameters, and artifacts:

import mlflow

# Set the MLflow tracking URI
mlflow.set_tracking_uri("http://localhost:5000")

# Start an experiment
mlflow.set_experiment("my_experiment")

with mlflow.start_run():
    # Log parameters, metrics, and artifacts
    mlflow.log_param("param1", value1)
    mlflow.log_metric("metric1", value2)
    mlflow.log_artifact("path/to/artifact")
    # Train and log model
    mlflow.sklearn.log_model(model, "model")

Ensure that the tracking URI correctly reflects where the MLflow server is running.

For additional documentation covering MLflow Tracking, see the official docs.

Licenses

Chainguard Images contain software packages that are direct or transitive dependencies. The following licenses were found in the "latest" version of this image:

  • Apache-2.0

  • BSD-3-Clause

  • GCC-exception-3.1

  • GPL-2.0-only

  • GPL-2.0-or-later

  • GPL-3.0-or-later

  • LGPL-2.1-or-later

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For a complete list of licenses, please refer to this Image's SBOM.

Software license agreement

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python

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