Auto-PyTorch

Linux · Self-hosted

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Freedom report

Two barsScore 6.4

Free tierA free tier is on its own pricing page
Open codeNo open-source code on record
Runs widely1 of 6 device platforms
DocumentedPlans, terms and facts published

Auto-PyTorch is ranked #6 of 28 in AutoML software on Freedom251. It runs on Linux, Self-hosted. There is a free plan.

Auto-PyTorch plans and pricing

All plans

Auto-PyTorch Free 3-clause BSD license automl.github.io · 3 Oct 2026

Compared on AutoML software

Free plan: Yes
Feature engineering: Yes
Automated model selection: Yes
Workflow interface: code
Hosting model: self_hosted

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The record

What it does: Auto-PyTorch is an automated machine-learning toolkit based on PyTorch that helps users automate algorithm selection and hyperparameter tuning.
Optimization methods: It uses Bayesian optimization, meta-learning, and ensemble construction to search for models.
Supported tasks: The documentation describes tabular classification, tabular regression, and time-series forecasting tasks.
Data preparation: For tabular tasks, its preprocessing includes imputation, categorical encoding, scaling, and feature preprocessing, with corresponding hyperparameters tuned during search.
Ensembling: It builds ensembles by selecting among models based on their predictions for a validation set, and users can configure ensemble size and candidate limits.
Resource controls: Users can set a memory limit for estimators and a total wall-time limit for model search.
Parallel processing: It supports parallel Bayesian optimization using Dask.distributed, and parallel workers need access to a shared file system for training data and models.
Integration: The documented ecosystem includes PyTorch, scikit-learn transformers, Dask.distributed, and threadpoolctl.
Installation: The installation documentation specifies Linux, Python 3.7 or later, a C++11-capable compiler, and SWIG 3.0.*, and also documents a Docker image.
Forecasting dependencies: Time-series forecasting requires additional dependencies beyond the base installation.
License: The documentation states that Auto-PyTorch is licensed under the 3-clause BSD license.
Support and contribution: The project invites bug reports, documentation improvements, and feature contributions through its GitHub issue tracker.
Maker: The GitHub project says Auto-PyTorch is developed by the AutoML Groups of the University of Freiburg and Hannover.
Purpose: Auto-PyTorch is an automated machine learning toolkit based on PyTorch that automates algorithm selection and hyperparameter tuning.
Price from: Free

Where it ranks on Freedom251

Best AutoML Software in 2026#6 of 28

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Sources

automl.github.io/Auto-PyTorch/master/· checked 3 Oct 2026
automl.github.io/Auto-PyTorch/master/manual.html· checked 3 Oct 2026
automl.github.io/Auto-PyTorch/master/installation.html· checked 3 Oct 2026
github.com/automl/Auto-PyTorch· checked 3 Oct 2026