gt_mask shape is (0, x, y) while pred_mask shape is (some number, x, y), which raise assertion error for vqa and reason seg datasets

[Jefferyy-Peng]

Hi, In utils/vqa_datasets.py, at line 122. masks = torch.rand(0, *ori_size). This code create mask of shape (0, *ori_size). While in the LISAForCausalLM's model_forward function, it asserts assert ( gt_mask.shape[0] == pred_mask.shape[0]), "gt_mask.shape: {}, pred_mask.shape: {}".format(gt_mask.shape, pred_mask.shape). pred_mask have shape (some number, *ori_size) where some number depends on the offset, which raise assertion error.

Could you explain why this error raises and also what does offset represents?