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simclr is a reimplementation of "A Simple Framework for Contrastive Learning of Visual Representations" link

Example of minimum working command that launches a 2-gpu training with cifar10

python -m torch.distributed.launch --use_env --nproc_per_node=2 egg/zoo/simclr/train.py --batch_size=64 --dataset_name="cifar10" --dataset_dir="./cifar10" --image_size=32

In sweeps there's a configuration that tries to reproduce the setup of the paper with a batch size of 2048 using 16 GPUs In can be launched calling nest nest from the root directory of EGG with:

python egg/nest/nest.py --game egg.zoo.simclr.train --sweep egg/zoo/simclr/sweeps/simclr.json --checkpoint_dir="replicate_simclr" --nodes=2 --tasks=8