Self-Classifier: Self-Supervised Classification Network
self-classifier
Official PyTorch implementation and pretrained models of the paper Self-Supervised Classification Network. Self-Classifier is a self-supervised end-to-end classification neural network. It learns labels and representations simultaneously in a single-stage end-to-end manner.
Self-Classifier architecture. Two augmented views of the same image are processed by a shared network. The cross-entropy of the two views is minimized to promote same class prediction while avoiding degenerate solutions by asserting a uniform prior. The resulting model learns representations and class labels in a single-stage end-to-end unsupervised manner. CNN: Convolutional Neural Network; FC: Fully Connected.
Setup
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Install Conda environment:
conda env create -f ./environment.yml -
Install Apex with CUDA extension:
export TORCH_CUDA_ARCH_LIST="7.0" # see https://en.wikipedia.org/wiki/CUDA#GPUs_supported pip install git+git://github.com/NVIDIA/[email protected] --install-option="--cuda_ext"