Unofficial PyTorch implementation of TokenLearner by Google AI

Overview

tokenlearner-pytorch

Unofficial PyTorch implementation of TokenLearner by Ryoo et al. from Google AI (abs, pdf)

Installation

You can install TokenLearner via pip:

pip install tokenlearner-pytorch

Usage

You can access the TokenLearner class from the tokenlearner_pytorch package. You can use this layer with a Vision Transformer, MLPMixer, or Video Vision Transformer as done in the paper.

import torch
from tokenlearner_pytorch import TokenLearner

tklr = TokenLearner(S=8)
x = torch.rand(512, 32, 32, 3)
y = tklr(x) # [512, 8, 3]

You can also use TokenLearner and TokenFuser together with Multi-head Self-Attention as done in the paper:

import torch
import torch.nn as nn
from tokenlearner_pytorch import TokenLearner, TokenFuser

mhsa = nn.MultiheadAttention(3, 1)
tklr = TokenLearner(S=8)
tkfr = TokenFuser(H=32, W=32, C=3, S=8)

x = torch.rand(512, 32, 32, 3) # a batch of images

y = tklr(x)
y = y.view(8, 512, 3)
y, _ = mhsa(y, y, y) # ignore attn weights
y = y.view(512, 8, 3)

out = tkfr(y, x) # [512, 32, 23, 3]

TODO

  • Add support for temporal dimension T
  • Implement TokenFuser with ViT
  • Implement TokenFuser with ViViT

Contributions

If I've made any errors or you have any suggestions, feel free to raise an Issue or PR. All contributions welcome!!

License

MIT

Owner
Rishabh Anand
CS undergrad + ML Research @ NUS • Open-source Jedi • Writer
Rishabh Anand
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