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github.com/rentruewang/aioway @v0.0.11 sqlite

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README
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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.

Core symbols most depended-on inside this repo

type
called by 47
noxfile.py
parse
called by 26
src/aioway/spaces/attrs/attrs.py
append
called by 21
src/aioway/_utils/types.py
items
called by 14
src/aioway/_utils/types.py
sum
called by 13
src/aioway/_costs.py
torch_fake_mode
called by 13
src/aioway/_utils/tensors/fake.py
fake_fn
called by 13
src/aioway/modes/tracking/modes.py
keys
called by 12
src/aioway/_utils/types.py

Shape

Method 556
Function 384
Class 265
Route 1

Languages

Python100%

Modules by API surface

src/aioway/_utils/types.py41 symbols
src/aioway/modes/aten/binary.py34 symbols
src/aioway/_core/tensors.py31 symbols
src/aioway/modes/tracking/modes.py30 symbols
noxfile.py30 symbols
src/aioway/torch/nn/ufuncs.py27 symbols
src/aioway/_core/iters.py27 symbols
src/aioway/modes/tracking/hists.py26 symbols
src/aioway/spaces/attrs/attrs.py25 symbols
src/aioway/modes/tensors.py24 symbols
src/aioway/torch/nn/sliding.py22 symbols
src/aioway/indices.py21 symbols

Dependencies from manifests, versioned

av17 · 1×
numpy2 · 1×
pandas3 · 1×
pillow12 · 1×
rich14 · 1×
tensordict0.11 · 1×
tokenizers0.22 · 1×
torchvision0.25 · 1×
transformers5 · 1×

For agents

$ claude mcp add aioway \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact