    def forward(self, inputs):
        """forward function"""
        att_outputs = [self.InvRes(inputs[0])]
        for x, encoder in zip(inputs, self.mhca_blks):
            # [B, C, hh, ww] -> [B, N, C]
            _, _, hh, ww = x.shape
            x = x.flatten(2).transpose(1, 2)
            att_outputs.append(encoder(x, size=(hh, ww)))

        out_concat = torch.cat(att_outputs, dim=1)
        out = self.aggregate(out_concat)

        return out
forward function
towhee/models/mpvit/mpvit.py