Comments (1)
sangwoomo
commented on June 3, 2024
Hi, first sorry for confusion in our transformation code: It is a legacy or our initial research ideas on differentiable augmentation.
The order of rotation, resized random crop (T_transform), and simclr_aug (color augmentations) are order-independent.
We are planning to refactor the code to use torchvision transformations for all augmentations some day :)
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Related Issues (20)
- Your data is 4 times bigger than Simclr. Is it fair? HOT 1
- Can you share the implementation detail for baseline?(Cross-Entropy) HOT 3
- batch size HOT 4
- The result of using the checkpoint of unlabeled ImageNet-30 HOT 3
- CSI/training/unsup/simclr_CSI.py HOT 1
- Error while running the training script. HOT 1
- GPU requirement for training ImageNet model HOT 1
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