Demo project for training DeiT with Mesa

For more details, please checkout our paper: Mesa: A Memory-saving Training Framework for Transformers.

Usage

1. Install Mesa from here.
2. Install timm.

   pip install timm==0.3.2

3. To train a model.

   conda activate mesa
   bash scripts/run.sh [model] [gpus]
   
   # For example, to train DeiT-Ti with Mesa on 1 GPU
   
   bash scripts/run.sh deit_tiny_patch16_224 1
   # You may need to change the `--data-path` and `--data-set` (CIFAR or IMNET) in scripts/run.sh to make sure you have the correct path to dataset.

Results on ImageNet

Model	Param (M)	FLOPs (G)	Train Memory	Top-1 (%)
DeiT-Ti	5	1.3	4,171	71.9
DeiT-Ti w/ Mesa	5	1.3	1,858	72.1
DeiT-S	22	4.6	8,459	79.8
DeiT-S w/ Mesa	22	4.6	3,840	80.0
DeiT-B	86	17.5	17,691	81.8
DeiT-B w/ Mesa	86	17.5	8,616	81.8

Acknowledgments

This repository has adopted codes from DeiT, we thank the authors for their open-sourced code.