Hello！I read your code recently，i have same questions. First, if xy_pos_emb_shaped=None, get the tensor is same as input.But in your paper say"Position embeddings are added to the blocks to retain positional information, meaning that the position embedding spaces for the column and row are 1∗N ∗C and N ∗1∗C. "How can i add the position information?Second,different training setting with other models in yaml files,(1024, 2048)?Is this an unfair setting?
Hello！I read your code recently，i have same questions. First, if xy_pos_emb_shaped=None, get the tensor is same as input.But in your paper say"Position embeddings are added to the blocks to retain positional information, meaning that the position embedding spaces for the column and row are 1∗N ∗C and N ∗1∗C. "How can i add the position information?Second,different training setting with other models in yaml files,(1024, 2048)?Is this an unfair setting?