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Randomized reordering of tensors across GPUs with a corresponding restoration mechanism.
Distinct from Batch Processing: Specific to the shuffling of ML tensors across distributed hardware, not general batch processing.
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Lightly is a self-supervised learning framework and computer vision data curation tool designed to manage large image datasets and train models on unlabeled data. It functions as a PyTorch vision library and dataset management SDK, providing tools to convert raw images into high-dimensional vectors for similarity search, visualization, and feature extraction. The project implements a variety of self-supervised architectures, including MoCo, SimCLR, VICReg, Barlow Twins, and masked image modeling. It distinguishes itself by combining these learning frameworks with active learning capabilities,
Randomly reorders tensors in a batch across GPUs with a mechanism to restore the original order.