Question about the attention block.

[SongYupei]

Thanks for sharing the code of the paper. I have a question about the code in line 234-237. https://github.com/DSaurus/DeepMultiCap/blob/4e93adfbdd60520d4edaa8bd8e461fe41d01c489/lib/model/DMCNet.py#L234 `` geo_feature = torch.cat(geo_feature, dim=0) print('attention input shape:{0}'.format(geo_feature.shape))

[4, 1, 4, 320, 5000]

if self.opt.coarse_part: geo_feature = self.attention(geo_feature, self.feature_fusion) # [1, 1, 4, 320, 5000] print('attention output shape:{0}'.format(geo_feature.shape)) `` the shape[0] of geo_feature is become from 4 to1, but geo_feature.shape[0] is level number, it is not the viewr number become one. Any one can help me understand the probelem?