SlowGuess/NeurIPS_2023_OCR huggingface dataset:
We follow previous tasks to set attention ratio  $\tau = 0.5$ . Since image classification depends less on local information, we directly set the semantic pattern number  $K = 1$ . The input images are resized to  $224 \times 224$  when fed into the pretrained DeiT-S [50] model in the data selection process.
C.3.2 Implementation of Task Model
We follow [57, 35] to use ResNet-18 [21] classification model in this task, which is implemented based on mmclassification  $^{5}$ . The model is trained for 200 epochs with batch size 128 using an SGD optimizer (momentum 0.9, weight decay 5e-4). The initial learning rate is 0.1, which decays to 0.01 after 160 epochs. We apply standard data augmentation to the training including  $32 \times 32$  size random crop from  $36 \times 36$  zero-padded images and random horizontal flip.
<sup>4</sup>https://github.com/fyu/drn
$^{5}$ https://github.com/open-mmlab/mmclassification