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i my codebase to train regnetx_200m, i use this function 'random_sized_crop' in transform, while get bad result, train acc get 90%+, while val acc get 50%+ random_sized_crop(image, size=cfg.data.image_size, area_frac=0.08)
when i use torchvision method , training result is normal.
when change the code in pycls/datasets/transforms.py , functions: random_sized_crop use torchvision aspect_ratio, training result is right !!! so different result from there ???
i my codebase to train regnetx_200m, i use this function 'random_sized_crop' in transform, while get bad result, train acc get 90%+, while val acc get 50%+
random_sized_crop(image, size=cfg.data.image_size, area_frac=0.08)
when i use torchvision method , training result is normal.
anyone meet this problem ? i see the source code diff below, i think this shouldn't make so big different.
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