Models can be trained with RandAugment for the dataset of interest with no need for a separate proxy task. By only tuning two hyperparameters(N, M), you can achieve competitive performances as AutoAugments. Install $ pip install git+https://github.com/ildoonet/pytorch-randaugment ...
Models can be trained with RandAugment for the dataset of interest with no need for a separate proxy task. By only tuning two hyperparameters(N, M), you can achieve competitive performances as AutoAugments. Install $ pip install git+https://github.com/ildoonet/pytorch-randaugment ...
If I return aug only instead of aug.transforms.insert(0, RandAugment(4, 3)), there is no error. Error TypeError Traceback (most recent call last) <timed exec> in <module> D:\Datasets\Image dataset\Xray\SIAMESE-classifier\src\cross_vals.py in kfoldcv(model, data, epochs, n_splits,...