# 在MaskDecoder的__init__定义
self.output_hypernetworks_mlps = nn.ModuleList([MLP(transformer_dim, transformer_dim, transformer_dim // 8, 3)for i in range(self.num_mask_tokens)]
)
# 在MaskDecoder的predict_masks添加位置编码for i in range(self.num_mask_tokens):# mask_tokens_out[:, i, :]: B,1,C# output_hypernetworks_mlps: B,1,chyper_in_list.append(self.output_hypernetworks_mlps[i](mask_tokens_out[:, i, :]))# B,n,chyper_in = torch.stack(hyper_in_list, dim=1)b, c, h, w = upscaled_embedding.shape# B,n,c × B,c,N-->B,n,h,wmasks = (hyper_in @ upscaled_embedding.view(b, c, h * w)).view(b, -1, h, w)

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