gridgen.py 文件源码

def forward(self, input1):
        self.input1 = input1
        output = input1.new(torch.Size([input1.size(0)]) + self.grid.size()).zero_()
        self.batchgrid = input1.new(torch.Size([input1.size(0)]) + self.grid.size()).zero_()
        for i in range(input1.size(0)):
            self.batchgrid[i] = self.grid.astype(self.batchgrid[i])

        # if input1.is_cuda:
        #    self.batchgrid = self.batchgrid.cuda()
        #    output = output.cuda()

        for i in range(input1.size(0)):
            output = torch.bmm(self.batchgrid.view(-1, self.height*self.width, 3), torch.transpose(input1, 1, 2)).view(-1, self.height, self.width, 2)

        return output