2d21747abdbf1968a9d565a4090d5d6297ade71a,encoding/functions/syncbn.py,_sum_square,forward,#Any#Any#,25

Before Change

        ctx.save_for_backward(input)
        C = input.size(1)
        with torch.cuda.device_of(input):
            xsum = input.new().resize_(C).zero_()
            xsquare = input.new().resize_(C).zero_()
        if isinstance(input, torch.cuda.FloatTensor):
            with torch.cuda.device_of(input):
                encoding_lib.Encoding_Float_sum_square_Forward(

After Change

    @staticmethod
    def forward(ctx, input):
        ctx.save_for_backward(input)
        if input.is_cuda:
            xsum, xsqusum = lib.gpu.sumsquare_forward(input)
        else:
            raise NotImplemented
        return xsum, xsqusum

    @staticmethod
    def backward(ctx, gradSum, gradSquare):

Instances