sxhxliang/DLGraph
model graph to code
This tool helps deep learning practitioners design neural network models visually and then automatically generates the corresponding PyTorch code. You can visually arrange layers and connections on a canvas, and the output is ready-to-use PyTorch code for your model. It's designed for machine learning engineers, researchers, and students who build and experiment with deep learning architectures.
No commits in the last 6 months.
Use this if you prefer to design and prototype deep learning models through a drag-and-drop interface rather than writing all the PyTorch code by hand.
Not ideal if you need to implement highly custom operations or prefer to have full manual control over every line of your neural network code.
Stars
9
Forks
—
Language
JavaScript
License
—
Category
Last pushed
May 04, 2019
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/sxhxliang/DLGraph"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
pyg-team/pytorch_geometric
Graph Neural Network Library for PyTorch
a-r-j/graphein
Protein Graph Library
raamana/graynet
Subject-wise networks from structural MRI, both vertex- and voxel-wise features (thickness, GM...
pykale/pykale
Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for...
dmlc/dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.