hpoflow 0.1.2

Tools for Optuna, MLflow and the integration of both

HPOflow - Sphinx DOC

Tools for Optuna, MLflow and the integration of both.

This project is maintained by the One Conversation team of Deutsche Telekom AG.

The main components are:

• hpoflow.OptunaMLflow:
  A wrapper to use Optuna and log to MLflow at the same time.
• hpoflow.OptunaMLflowCallback:
  Class inheriting from transformers.TrainerCallback that integrates with OptunaMLflow to send the logs to MLflow and Optuna during model training.
• hpoflow.SignificanceRepeatedTrainingPruner:
  An Optuna pruner to use statistical significance (a t-test which serves as a heuristic) to stop unpromising trials early, avoiding unnecessary repeated training during cross validation.

Installation

HPOflow is available at the Python Package Index (PyPI). It can be installed with pip:

$ pip install hpoflow

Some additional dependencies might be necessary.

To use hpoflow.optuna_mlflow.OptunaMLflow:

$ pip install mlflow GitPython

To use hpoflow.optuna_transformers.OptunaMLflowCallback:

$ pip install mlflow GitPython transformers

Support and Feedback

The following channels are available for discussions, feedback, and support requests:

• open an issue in our GitHub repository
• send an e-mail to our open source team

Contribution

Our commitment to open source means that we are enabling -in fact encouraging- all interested parties to contribute and become part of our developer community.

Contribution and feedback is encouraged and always welcome. For more information about how to contribute, as well as additional contribution information, see our Contribution Guidelines. By participating in this project, you agree to abide by its Code of Conduct at all times.

Code of Conduct

This project has adopted the Contributor Covenant in version 2.0 as our code of conduct. Please see the details in our CODE_OF_CONDUCT.md. All contributors must abide by the code of conduct.

Working Language

We decided to apply English as the primary project language.

Consequently, all content will be made available primarily in English. We also ask all interested people to use English as language to create issues, in their code (comments, documentation etc.) and when you send requests to us. The application itself and all end-user facing content will be made available in other languages as needed.

Licensing

Copyright (c) 2021 Philip May, Deutsche Telekom AG
Copyright (c) 2021 Philip May
Copyright (c) 2021 Timothy Wolff-Piggott

Licensed under the MIT License (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License by reviewing the file LICENSE in the repository.