google-research/morph-net
Fast & Simple Resource-Constrained Learning of Deep Network Structure
This helps deep learning practitioners optimize their neural networks to be smaller, faster, or use less memory without significantly impacting accuracy. You provide an existing convolutional neural network and a target, like reducing FLOPs or model size. The system outputs a modified network architecture that meets your resource constraints. It's for anyone deploying deep learning models in environments with strict computational or memory limits.
1,033 stars.
Use this if you have an existing deep neural network that is too large or slow for your deployment environment and you need to reduce its resource consumption.
Not ideal if you are looking to change the fundamental layer topology of your neural network or explore entirely new architectures from scratch.
Stars
1,033
Forks
152
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 09, 2026
Commits (30d)
0
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