Vision Transformer in PyTorch

In this video I implement the Vision Transformer from scratch. It is very much a clone of the implementation provided in https://github.com/rwightman/pytorch-image-models. I focus solely on the architecture and inference and do not talk about training. I discuss all the relevant concepts that the Vision Transformer is using e.g. patch embedding, attention mechanism, layer normalization and many others.

My implementation: https://github.com/jankrepl/mildlyoverfitted/tree/master/github_adventures/vision_transformer
timm implementation: https://github.com/rwightman/pytorch-image-models
lucidrains implementation: https://github.com/lucidrains/vit-pytorch

00:00​​​ Intro
01:20​​​ Architecture overview
02:53​​ Patch embedding module
06:39 Attention module
07:22 Dropout overview
08:11​​​ Attention continued 1
10:50 Linear overview
12:10 Attention continued 2
14:35 Multilayer perceptron
16:07 Block module
17:02 LayerNorm overview
19:31 Block continued
20:44 Vision transformer
24:52 Verification
28:01 Cat forward pass
29:10 Outro

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Twitter: https://twitter.com/moverfitted

Credits logo animation
Title: Conjungation · Author: Uncle Milk · Source: https://soundcloud.com/unclemilk​ · License: https://creativecommons.org/licenses/...​ · Download (9MB): https://auboutdufil.com/?id=600

Видео Vision Transformer in PyTorch канала mildlyoverfitted