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##---------- Prompt Gen Module -----------------------
class PromptGenBlock(nn.Module):
    def __init__(self,prompt_dim=128,prompt_len=5,prompt_size = 96,lin_dim = 192):
        super(PromptGenBlock,self).__init__()
        self.prompt_param = nn.Parameter(torch.rand(1,prompt_len,prompt_dim,prompt_size,prompt_size))
        self.linear_layer = nn.Linear(lin_dim,prompt_len)
        self.conv3x3 = nn.Conv2d(prompt_dim,prompt_dim,kernel_size=3,stride=1,padding=1,bias=False)
        

    def forward(self,x):
        B,C,H,W = x.shape
        emb = x.mean(dim=(-2,-1))
        prompt_weights = F.softmax(self.linear_layer(emb),dim=1)
        prompt_param = self.prompt_param.data.unsqueeze(0).repeat(B,1,1,1,1,1)
        prompt_param = prompt_param.data.squeeze(1)
        prompt_param = prompt_weights.unsqueeze(-1).unsqueeze(-1).unsqueeze(-1) * prompt_param
        prompt_param = torch.sum(prompt_param,dim=1)
        prompt_param = F.interpolate(prompt_param,(H,W),mode="bilinear")
        prompt_param = self.conv3x3(prompt_param)

        return prompt_param