Vit (vision transformer) principle and code elaboration

Course link ：ViT（Vision Transformer） Principle and code elaboration -1- Course is an introduction to - Bai Yong's online video tutorial -CSDN Programmer Institute

Transformer In many NLP( natural language processing ) The most advanced results have been achieved in the mission . ViT (Vision Transformer) yes Transformer be applied to CV（ Computer vision ） Milestone work in the field , Later, more variants have been developed , Such as Swin Transformer. 

ViT (Vision Transformer) Model published in paper An Image is Worth 16X16 Words: Transformer For Image Recognition At Scale, Use pure Transformer Image classification .ViT stay JFT-300M After pre training on the dataset , It can exceed convolutional neural network ResNet Performance of , And the training computing resources used can be less . 

This course is right ViT Principle and PyTorch The implementation code is refined , To help you master its detailed principle and specific implementation . The code implementation includes two code implementation methods , One is to adopt timm library , The other is to adopt einops/einsum.  

Principle elaboration part Include ：Transformer An overview of the architecture 、Transformer Of Encoder 、Transformer Of Decoder、ViT Architecture Overview 、ViT The model, 、ViT Performance and analysis .  

Code elaboration part Use Jupyter Notebook Yes ViT Of PyTorch Read the code line by line , Include ： install PyTorch、ViT Of timm Library implementation code interpretation 、 einops/einsum 、ViT Of einops/einsum Implement code interpretation .