KAIST CS454, AI based Software Engineering, project originated from cgp-cnn-PyTorch
- Ubuntu 16.04.6 LTS
- Python version 3.6.2
- PyTorch version 0.4.1
- tensorflow 1.9.0
- CUDA version 10.x (Any)
- scikit-image 0.13.0
- pandas 0.20.3
exp_main.py [-h] [--gpu_ids GPU_IDS [GPU_IDS ...]]
[--population POPULATION] [--lam LAM]
[--log_folder LOG_FOLDER] [--max_gen MAX_GEN]
[--snm {normal,strong}] [--seed SEED]
[--epoch EPOCH]
optional arguments:
-h, --help show this help message and exit
--gpu_ids GPU_IDS [GPU_IDS ...], -g GPU_IDS [GPU_IDS ...]
List of GPU ids
--population POPULATION, -p POPULATION
Num. of Population (Num. of Parents)
--lam LAM, -l LAM Num. of offsprings
--log_folder LOG_FOLDER
Log folder name
--max_gen MAX_GEN, -max MAX_GEN
Num. of max evaluations
--snm {normal,strong}, -snm {normal,strong}
Strong Neutral Mutation
--seed SEED, -s SEED Numpy random seed
--epoch EPOCH, -e EPOCH
Training epoch
This repository contains the code for the following paper:
Masanori Suganuma, Shinichi Shirakawa, and Tomoharu Nagao, "A Genetic Programming Approach to Designing Convolutional Neural Network Architectures," Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '17, Best paper award), pp. 497-504 (2017) [paper] [arXiv]