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Installation

We provide installation instructions for ImageNet classification experiments here.

Dependency Setup

Create an new conda virtual environment

conda create -n moganet python=3.8 -y
conda activate moganet

Install Pytorch>=1.8.0, torchvision>=0.9.0 following official instructions. For example:

pip install torch==1.10.0+cu111 torchvision==0.11.0+cu111 torchaudio==0.10.0 -f https://download.pytorch.org/whl/torch_stable.html

Clone this repo and install required packages. You can install apex-amp if you want to use fp16 with Pytorch<=1.6.0.

git clone https://github.com/Westlake-AI/MogaNet
pip install timm fvcore

The results in this repository are produced with torch==1.10.0+cu111 torchvision==0.11.0+cu111 timm==0.6.12, and we adopt amp fp16 for fast training.

Dataset Preparation

Download the ImageNet-1K classification dataset (train and val) and structure the data as follows. You can extract ImageNet with this script.

│imagenet/
├──train/
│  ├── n01440764
│  │   ├── n01440764_10026.JPEG
│  │   ├── n01440764_10027.JPEG
│  │   ├── ......
│  ├── ......
├──val/
│  ├── n01440764
│  │   ├── ILSVRC2012_val_00000293.JPEG
│  │   ├── ILSVRC2012_val_00002138.JPEG
│  │   ├── ......
│  ├── ......