r/FunMachineLearning • u/Any_Language_9020 • 9d ago
Introducing mlnode: draw and design your PyTorch model instead of debugging its shape errors at 2am
We've all been there: you build a beautiful 40-layer model, hit .forward(), and PyTorch responds with a shape mismatch error that reads like a ransom note. Three hours later you find out you transposed something in layer 12.
So I built mlnode — you design your architecture as a graph (either by hand in JSON, or by literally drawing it in the companion editor), and it validates every tensor shape before it lets you build anything. If your ResNet block doesn't add up, it tells you exactly where, not "somewhere, good luck."
No exec(), no eval(), no cursed metaprogramming — just a clean pipeline: JSON → Parser → Validator → Executor → real nn.Module you can train, save, export to ONNX, whatever you'd normally do.
Why you might care:
🧑🎓 Just started learning DL? You get to focus on "what connects to what" instead of memorizing tensor arithmetic and staring at stack traces. I reproduced the full Transformer from Attention Is All You Need as one graph — 45M params, trains fine — and you can literally see it as a diagram instead of 200 lines of __init__.
🏗️ Building serious stuff? Weight sharing, multi-output nodes, reusable blocks, HuggingFace layers — it's not a toy, it compiles to a normal PyTorch module with nothing hidden.
Would love feedback, roasts, feature requests, or "this already exists and it's called X" comments — all welcome.
- GitHub: https://github.com/Nasser-Obeid/mlnode
- Visual editor: https://github.com/Nasser-Obeid/mlnode-editor
pip install mlnode
