Hello, in the code of architecture search, ie DART/searchs/search.py, I found that the difference between the training data and the validation data is whether there is random cropping, is that right?
49 # get dataset and meta info50 input_size, input_channels, n_classes, train_data = dataset.get_train_dataset(cfg.root, cfg.dataset)51 val_data = dataset.get_dataset_without_crop(cfg.root, cfg.dataset)
I am also studying the application of NAS in recognition tasks recently, but I am confused about how to set training data and validation data because I found that the conventional setting seems to be unable to be applied to the NAS. Can you tell me your understanding of this? Thanks a lot!!!
Hello, in the code of architecture search, ie
DART/searchs/search.py, I found that the difference between the training data and the validation data is whether there is random cropping, is that right?49 # get dataset and meta info50 input_size, input_channels, n_classes, train_data = dataset.get_train_dataset(cfg.root, cfg.dataset)51 val_data = dataset.get_dataset_without_crop(cfg.root, cfg.dataset)I am also studying the application of NAS in recognition tasks recently, but I am confused about how to set training data and validation data because I found that the conventional setting seems to be unable to be applied to the NAS. Can you tell me your understanding of this? Thanks a lot!!!