Using Self-Supervised Pretext Tasks for Active Learning - Official Pytorch Implementation

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Deep LearningPT4AL
Overview

Using Self-Supervised Pretext Tasks for Active Learning - Official Pytorch Implementation

Experiment Setting:

  • CIFAR10 (downloaded and saved in ./DATA
  • Rotation prediction for pretext task

Prerequisites:

Python >= 3.7

CUDA = 11.0

PyTorch = 1.7.1

numpy >= 1.16.0

Running the Code

To train the rotation predition task on the unlabeled set:

python rotation.py

To extract pretext task losses and create batches:

python make_batches.py

To evaluate on active learning task:

python main.py
Owner
John Seon Keun Yi
MSCS Georgia Tech
John Seon Keun Yi
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