# Codeblock 2
class SPP(nn.Module):
    def forward(self, x):

        pooled_outputs = []      #(1)
        for grid in GRIDS:
            pooled = F.adaptive_max_pool2d(x, output_size=(grid,grid))  #(2)
            print(f'after pool\t\t: {pooled.size()}')

            pooled = torch.flatten(pooled, start_dim=1)    #(3)
            print(f'after flatten\t\t: {pooled.size()}\n')

            pooled_outputs.append(pooled)                  #(4)

        concatenated = torch.cat(pooled_outputs, dim=1)    #(5)
        print(f'after concatenate\t: {concatenated.size()}\n')

        return concatenated