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hellock avatar hellock commented on August 19, 2024 1

#35

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hellock avatar hellock commented on August 19, 2024 1

OK PyTorch is fixing lots of api inconsistencies, thanks for the notice.

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MatthewD1993 avatar MatthewD1993 commented on August 19, 2024

Could someone also explain what is the benefits of using the static method in new Pytorch version and what is ctx?

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adriansahlman avatar adriansahlman commented on August 19, 2024

Hey! Im also interested in running this on python 3+ and pytorch 0.3

At the moment I dont have enough free time to fiddle with it myself so im going to keep an eye on this issue.

I dont know what the benefit of using the static method is as that is the only one I have used.

As for ctx, that is the context. The context you recieve in the forward pass of a function is the same context object that you recieve for the backward pass. You can for example save tensors in the forward pass that you are going to need in your backward pass in the ctx variable.

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lfz avatar lfz commented on August 19, 2024

Hi, I meet a simiar problem in another package, May I ask which line in the commit #35 solve this problem? Thank you! @hellock

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hellock avatar hellock commented on August 19, 2024

Hi @lfz ,
ChannelNorm_cuda_forward and ChannelNorm_cuda_backward should accept Tensor instead of Variable as arguments.

So the problem is solved by changing to

channelnorm.ChannelNorm_cuda_backward(input1, output, grad_output.data,
                                      grad_input1.data, ctx.norm_deg)

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lfz avatar lfz commented on August 19, 2024

does it influence the final output, I mean, the input is now a tensor, so is its output changed to a tensor too?

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hellock avatar hellock commented on August 19, 2024

The final output of backward function such as grad_input1 should be a Variable. You can refer to #35 for details.

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lfz avatar lfz commented on August 19, 2024

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fitsumreda avatar fitsumreda commented on August 19, 2024

we've added a python3 branch https://github.com/NVIDIA/flownet2-pytorch/tree/python36

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