Skip to content

Latest commit

 

History

History
14 lines (8 loc) · 759 Bytes

README.md

File metadata and controls

14 lines (8 loc) · 759 Bytes

FastDeepNAS

Git repository for code used to produce the results reported in our paper "Fast Deep Neural Architecture Search for Wearable Activity Recognition by Early Prediction of Converged Performance (https://dl.acm.org/doi/10.1145/3460421.3478813)

To run the code in the notebooks or main.py, first install the requirements using pip:

pip install -r requirements.txt

then, you will also need to install the custom OpenAI gym environment gym_nas_pt as follows:

pip install -e ./gym_nas_pt_env

both of these commands should be run from the root of the cloned repo.

The directories MLP* and Baseline* contain notebooks to replicate the NAS runs reported in the paper, as well as the intermediate results from our experiments.