DepthConcat.py 文件源码

def updateOutput(self, input):
        outs = []
        for i in range(len(self.modules)):
            currentOutput = self.modules[i].updateOutput(input)
            outs.append(currentOutput)
            if i == 0:
                size = list(currentOutput.size())
            else:
                size[self.dimension] += currentOutput.size(self.dimension)
                for dim in range(len(self.outputSize)):
                    if dim != self.dimension:
                        # take the maximum size (shouldn't change anything for batch dim)
                        size[dim] = max(size[dim], currentOutput.size(dim))

        self.outputSize = torch.Size(size)
        self.output.resize_(self.outputSize).zero_()  # zero for padding

        offset = 0
        for i, module in enumerate(self.modules):
            currentOutput = outs[i]
            outputWindow = self.windowNarrow(self.output, currentOutput, offset)
            outputWindow.copy_(currentOutput)
            offset = offset + currentOutput.size(self.dimension)

        return self.output