A PyTorch Implementation of ViT (Vision Transformer)

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Deep Learning ViT_PyTorch
Overview

ViT - Vision Transformer

This is an implementation of ViT - Vision Transformer by Google Research Team through the paper "An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale"

Please install PyTorch with CUDA support following this link

ViT Architecture

Architecture of Vision Transformer

Configs

You can config the network by yourself through the config.txt file

128     #batch_size
500     #epoch
0.001   #learning_rate
0.0001  #gamma
224     #img_size
16 	#patch_size
100	#num_class
768	#d_model
12	#n_head
12      #n_layers
3072    #d_mlp
3	#channels
0.	#dropout
cls	#pool

Training

Currently, you can only train this model on CIFAR-100 with the following commands:

> git clone https://github.com/quanmario0311/ViT_PyTorch.git
> cd ViT_PyTorch
> pip3 install -r requirements.txt
> python3 train.py

Suppport for other dataset and custom datasets will be updated later

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