Tools for Optuna, MLflow and the integration of both.

Related tags

Machine Learningpythonmachine-learningloggingtransformershyperparameter-optimizationhyperparametermlflowoptuna
Overview

HPOflow - Sphinx DOC

DOC MIT License Contributor Covenant Python Version pypi
pytest status Static Code Checks status Build & Deploy Doc GitHub issues

Tools for Optuna, MLflow and the integration of both.

Detailed documentation with examples can be found here: Sphinx DOC

Table of Contents

Maintainers

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

The main components are:

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

To install all optional dependencies use:

$ pip install hpoflow[optional]

Support and Feedback

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

Reporting Security Vulnerabilities

This project is built with security and data privacy in mind to ensure your data is safe. We are grateful for security researchers and users reporting a vulnerability to us, first. To ensure that your request is handled in a timely manner and non-disclosure of vulnerabilities can be assured, please follow the below guideline.

Please do not report security vulnerabilities directly on GitHub. GitHub Issues can be publicly seen and therefore would result in a direct disclosure.

Please address questions about data privacy, security concepts, and other media requests to the [email protected] mailbox.

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.

Code of Conduct

This project has adopted the Contributor Covenant as our code of conduct. Please see the details in our Contributor Covenant Code of Conduct. All contributors must abide by the code of conduct.

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.

Comments
  • review README.md and CONTRIBUTING.md

    review README.md and CONTRIBUTING.md

    Review README.md and CONTRIBUTING.md

    • is there something missing? maybe compare with optuna and transformers
    • spelling
    • idiomatic english
    • consistency
    • correctness
    • links ok?
    • ...

    PS: The real documentation is still missing and a know issue.

    opened by PhilipMay 12
  • add typing in optuna_transformers

    add typing in optuna_transformers

    @twolffpiggott can you please tell me the type of this?

    https://github.com/telekom/HPOflow/blob/e2b0943218af419a79ce95e60b67c9a4c2477349/hpoflow/optuna_transformers.py#L47

    opened by PhilipMay 6
  • add `transformers.py`

    add `transformers.py`

    @twolffpiggott should we add this here or to an other project we open source?

    https://github.com/PhilipMay/mltb/blob/master/mltb/integration/transformers.py

    enhancement 
    opened by PhilipMay 6
  • Create Sphinx documentation page

    Create Sphinx documentation page

    • [x] setup
    • [x] make GH action
    • [x] setup page
    • [x] change styling to telekom style
    • switch to MD
    • [x] add more content
    • [x] link from README to page
    • [x] link from pypi to GH page
    • [x] add impressum
    • [x] remove strange mouse over image effect
    • add version info
    documentation 
    opened by PhilipMay 4
  • Problems with direct `_imports.check()` call

    Problems with direct `_imports.check()` call

    When the __init__.py imports OMLflowCallback the optuna_transformers.py script is executed. That executes the _imports.check() call which then throws an exception if transformers or mlflow is not installed. But that should be avoided.

    See here: https://github.com/telekom/HPOflow/blob/d1cce5cbc2a84634d1484a053286000dda05b681/hpoflow/optuna_transformers.py#L11-L17

    The solution would be to put the _imports.check() call into the constructor. But that is not possible because OMLflowCallback inherits from transformers.

    The only solution I have is to put OMLflowCallback into an factory function that creates an OMLflowCallback and does the _imports.check() in there.

    @twolffpiggott what do you think?

    bug 
    opened by PhilipMay 3
  • Flake8 ignore list for Black compatibility

    Flake8 ignore list for Black compatibility

    Flake8 raises a warning for "E203" when it encounters a Black decision to insert whitespace before : in slicing syntax.

    Black's behaviour is more correct here, so my suggestion is to add "E203" to the flake8 config ignore list.

    i.e. in setup.cfg:

    [flake8]
...
extend-ignore = E203
    opened by twolffpiggott 3
  • Simple Example?

    Simple Example?

    I don't understand how to use this package. Could you provide a basic example? I don't understand the import_structure and how it relates to importing the modules? Thanks

    opened by jmrichardson 2
  • WIP prefix in contrib file

    WIP prefix in contrib file

    Should this

    Create Work In Progress [WIP] pull requests only if you need clarification or an explicit review before you can continue your work item.

    be more like this

    Add a [WIP] prefix on your pull request name if you need clarification or an explicit review before you can continue your work item.

    documentation 
    opened by PhilipMay 2
Releases(0.1.4)
Owner
Telekom Open Source Software
published by Deutsche Telekom AG and partner companies
Telekom Open Source Software
GitHub Repository https://telekom.github.io/HPOflow/
A collection of machine learning examples and tutorials.

machine_learning_examples A collection of machine learning examples and tutorials.

LazyProgrammer.me 7.1k Jan 01, 2023
moDel Agnostic Language for Exploration and eXplanation

moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.

Model Oriented 1.2k Jan 04, 2023
pymc-learn: Practical Probabilistic Machine Learning in Python

pymc-learn: Practical Probabilistic Machine Learning in Python Contents: Github repo What is pymc-learn? Quick Install Quick Start Index What is pymc-

pymc-learn 196 Dec 07, 2022
Nixtla is an open-source time series forecasting library.

Nixtla Nixtla is an open-source time series forecasting library. We are helping data scientists and developers to have access to open source state-of-

Nixtla 401 Jan 08, 2023
Winning solution for the Galaxy Challenge on Kaggle

Winning solution for the Galaxy Challenge on Kaggle

Sander Dieleman 483 Jan 02, 2023
Model factory is a ML training platform to help engineers to build ML models at scale

Model Factory Machine learning today is powering many businesses today, e.g., search engine, e-commerce, news or feed recommendation. Training high qu

16 Sep 23, 2022
Classification based on Fuzzy Logic(C-Means).

CMeans_fuzzy Classification based on Fuzzy Logic(C-Means). Table of Contents About The Project Fuzzy CMeans Algorithm Built With Getting Started Insta

Armin Zolfaghari Daryani 3 Feb 08, 2022
Deep Survival Machines - Fully Parametric Survival Regression

Package: dsm Python package dsm provides an API to train the Deep Survival Machines and associated models for problems in survival analysis. The under

Carnegie Mellon University Auton Lab 10 Dec 30, 2022
Distributed Computing for AI Made Simple

Project Home Blog Documents Paper Media Coverage Join Fiber users email list Uber Open Source 997 Dec 30, 2022

Covid-polygraph - a set of Machine Learning-driven fact-checking tools

Covid-polygraph, a set of Machine Learning-driven fact-checking tools that aim to address the issue of misleading information related to COVID-19.

1 Apr 22, 2022
Dragonfly is an open source python library for scalable Bayesian optimisation.

Dragonfly is an open source python library for scalable Bayesian optimisation. Bayesian optimisation is used for optimising black-box functions whose

744 Jan 02, 2023
Python-based implementations of algorithms for learning on imbalanced data.

ND DIAL: Imbalanced Algorithms Minimalist Python-based implementations of algorithms for imbalanced learning. Includes deep and representational learn

DIAL | Notre Dame 220 Dec 13, 2022
Microsoft Machine Learning for Apache Spark

Microsoft Machine Learning for Apache Spark MMLSpark is an ecosystem of tools aimed towards expanding the distributed computing framework Apache Spark

Microsoft Azure 3.9k Dec 30, 2022
Machine-learning-dell - Repositório com as atividades desenvolvidas no curso de Machine Learning

📚 Descrição Neste curso da Dell aprofundamos nossos conhecimentos em Machine Learning. 🖥️ Aulas (Em curso) 1.1 - Python aplicado a Data Science 1.2

Claudia dos Anjos 1 Jan 05, 2022
Implementation of different ML Algorithms from scratch, written in Python 3.x

Implementation of different ML Algorithms from scratch, written in Python 3.x

Gautam J 393 Nov 29, 2022
Decision tree is the most powerful and popular tool for classification and prediction

Diabetes Prediction Using Decision Tree Introduction Decision tree is the most powerful and popular tool for classification and prediction. A Decision

Arjun U 1 Jan 23, 2022
A scikit-learn based module for multi-label et. al. classification

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

802 Jan 01, 2023
Python Automated Machine Learning library for tabular data.

Simple but powerful Automated Machine Learning library for tabular data. It uses efficient in-memory SAP HANA algorithms to automate routine Data Scie

Daniel Khromov 47 Dec 17, 2022
A Python toolbox to churn out organic alkalinity calculations with minimal brain engagement.

Organic Alkalinity Sausage Machine A Python toolbox to churn out organic alkalinity calculations with minimal brain engagement. Getting started To mak

Charles Turner 1 Feb 01, 2022
A concept I came up which ditches the idea of "layers" in a neural network.

Dynet A concept I came up which ditches the idea of "layers" in a neural network. Install Copy Dynet.py to your project. Run the example Install matpl

Anik Patel 4 Dec 05, 2021