Skip to main content
       _____
______ ___(_)________      _______ _____  __
_  __ `/_  /_  __ \_ | /| / /  __ `/_  / / /
/ /_/ /_  / / /_/ /_ |/ |/ // /_/ /_  /_/ /
\__,_/ /_/  \____/____/|__/ \__,_/ _\__, /
                                   /____/

An optimizing compiler for ML algorithms.

Unit Testing Pre Commit Checks Publish PyPI Apache

🛣️ AioWay

Aioway is an optimizing compiler for deep learning algorithms. It treats the machine learning models / algorithms as instructions and build the pipeline that way.

🏢 Architecture diagram

🍰 Features

Most of these features are done but not polished yet! But will be in couple of weeks.

  • ⚡ Fast. Compared to neural architecture search, the optimization can be rule based (fast).
  • 🕵️ Detects the tasks at hand, resource available, and select the best algorithms and models.
  • 🎁 The models built from aioway would be white box (explainable), due to our architecture.
  • ⚙️ Allows upgrading parts of the models. You scale up to different model size, and to different machines.
  • 🐍 Both relational algebra (SQL like) and python library interface.
  • 🔥 Extensible with custom pytorch.

⛰️ Compared with current landscape

  1. Neural architecture search: Too slow (because most need backtracking).
  2. Current autoML framework: non flexible enough, usually stuck with UI or fixed set of models (black box still).
  3. Pretrained models / LLM: Usually expensive, non explainable, less flexible.
  4. Traditional methods: They can't handle new data (multimodal).

🤔 Why aioway yada yada

In the recent years, machine learning's entry barrier higher, rather than lower. People with expert training are expensive, as they need years of experience to be good.

However, current AutoML solutions are subpar. Each one of them have clear limitations: slow, inflexible, unreliable, or unable to handle modern data.

Drawing inspriation from opitmizing compilers (especially SQLs), aioway aims to solve that.

🌟 Give us a star!

That's all for now!

If you have read this far, please consider giving me a star (⭐) or a fork (🍴).

This will keep me motivated!

Or if you have too much cash at hand: BuyMeACoffee

🗺️ Roadmap

We are most likely launching v0.1.0 before July 2026, but before that, see the pre-release tracking project for more details.

🤝 Contributing

Contributing is of course welcome. Please see the contributing guide and follow the code of conduct.

👨‍👨‍👦‍👦 Contributors

🐨 Relation to koila

Aioway builds on top of the original koila (moved to a branch). The torch team built FakeTensor which overlaps a lot with koila's functionality, so it's no longer maintained. See the rationale in the koila branch.

Conceptually, aioway works in a similar way, but instead of Tensor ops, aioway focuses on a higher level, on algorithm building.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aioway-0.1.tar.gz (171.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

aioway-0.1-py3-none-any.whl (88.9 kB view details)

Uploaded Python 3

File details

Details for the file aioway-0.1.tar.gz.

File metadata

  • Download URL: aioway-0.1.tar.gz
  • Upload date:
  • Size: 171.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: pdm/2.28.0 CPython/3.14.6 Linux/6.17.0-1020-azure

File hashes

Hashes for aioway-0.1.tar.gz
Algorithm Hash digest
SHA256 0527d2b90e63bad75ee152345a385404dad2712907e9205ac9929b2bb41fa106
MD5 deebde8ec7d7c7554b1c84e17079e1f3
BLAKE2b-256 555e69e21a33d98c338daf2788e86ab5ab43a8d52c82ab96a2814ae31fa5b3d2

See more details on using hashes here.

File details

Details for the file aioway-0.1-py3-none-any.whl.

File metadata

  • Download URL: aioway-0.1-py3-none-any.whl
  • Upload date:
  • Size: 88.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: pdm/2.28.0 CPython/3.14.6 Linux/6.17.0-1020-azure

File hashes

Hashes for aioway-0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 aa00570cac28d805f26d54559521a2f61f9e5db7048b6127be0ccac69470fff5
MD5 ff874bec340460b6931d383bc1985e69
BLAKE2b-256 a01cfd13972bdd31a6bcfec3bb7a6d1e6fd3e5e59ea76636fd7e03492841bd46

See more details on using hashes here.

Release history Release notifications | RSS feed

0.2

2 files

0.1.1

2 files

This release

0.1 This release

2 files

0.0.14

2 files

0.0.13

2 files

0.0.12

2 files

0.0.11

2 files

0.0.10

2 files

0.0.9

2 files

0.0.8

2 files

0.0.7

2 files

0.0.6.post0

2 files

0.0.6

2 files

0.0.5

2 files

0.0.4

2 files

0.0.3

2 files

0.0.2

2 files

0.0.1

2 files

0.0.0

2 files

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page