evoxbench 1.0.1

A benchmark for NAS algorithms

Neural Architecture Search as Multiobjective Optimization Benchmarks: Problem Formulation and Performance Assessment [arXiv]

Preparation Steps

1. Download the following two requried files:

   • database.zip file from Google Drive or Baidu云盘（提取码：mhgs）

   • data.zip file from Google Drive

     or Baidu云盘（提取码：lfib）

2. pip install evoxbench to install the benchmark.

3. Configure the benchmark via the following steps:

    from evoxbench.database.init import config

    config("Path to databae", "Path to data")
    # For example
    # If you have the following structure
    # /home/Downloads/
    # └─ database/
    # |  |  __init__.py
    # |  |  db.sqlite3
    # |  |  ...
    # |  
    # └─ data/
    #    └─ darts/
    #    └─ mnv3/
    #    └─ ...
    # Then you should do:
    # config("/home/Downloads/database", "/home/Downloads/data")

Database

Visit this webpage for more information: https://github.com/liuxukun2000/evoxdatabase

Acknowledgement

Codes are developed upon: NAS-Bench-101 , NAS-Bench-201, NAS-Bench-301 , NATS-Bench , Once for All , AutoFormer, Django , pymoo