Machine Learning

An all MLP (Multi-layer Perceptron) architecture for computer vision tasks

MLP-Mixer-CIFAR10

This repository implements MLP-Mixer as proposed in MLP-Mixer: An all-MLP Architecture for Vision. The paper introduces an all MLP (Multi-layer Perceptron) architecture for computer vision tasks. Yannic Kilcher walks through the architecture in this video.

Experiments reported in this repository are on CIFAR-10.

What’s included?

  • Distributed training with mixed-precision.
  • Visualization of the token-mixing MLP weights.
  • A TensorBoard callback to keep track of the learned linear projections of the image patches.

Notebooks

Note: These notebooks are runnable on Colab. If you don’t have access to a tensor-core GPU, please disable the mixed-precision block while running the code.

Results

MLP-Mixer achieves competitive results. The figure below summarizes top-1 accuracies on CIFAR-10 test set with respect to varying MLP blocks.