Comments (12)
There is now a branch "th14" which the test cases pass with pytorch 1.4. Not yet tested with any real experiments though.
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it seems that ignoring "ctx._backend = type2backend[input.type()]" works fine, could we just ignore it in the new version of Pytorch. BTW, what are we doing by using "ctx._backend = type2backend[input.type()]"? Thanks. @suhangpro @vkothapally
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Ignoring this import (as in #14 (comment)) seems to be working for the forward pass but raises errors in backprop.
Using the new branch (#14 (comment)) solved the issue.Sorry to bother you, but i don't know what the new branch(14th) is.
Is that a new package or something? Could you please post the link for me? Thank you so much!
Sure, no problem.
you can find branch th14 here
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I had the same issue. @suhangpro Do you have plans to make it compatible with PyTorch 1.4.0?
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@pfeatherstone Sorry for the delay. Yes, we definitely plan to bring compatibility to 1.4. Will take a look soon (in the next few days or perhaps a week).
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@suhangpro Just curious to know if you got a chance to look into this issue
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Thanks a lot for the quick update @suhangpro
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@Katou2 Thanks for sharing the observation. That line was originally used in some custom layer examples for exposing low-level functions. If it runs without errors then I think you're right you've found an even easier fix!
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Ignoring this import (as in #14 (comment)) seems to be working for the forward pass but raises errors in backprop.
Using the new branch (#14 (comment)) solved the issue.
from pacnet.
Ignoring this import (as in #14 (comment)) seems to be working for the forward pass but raises errors in backprop.
Using the new branch (#14 (comment)) solved the issue.
Sorry to bother you, but i don't know what the new branch(14th) is.
Is that a new package or something? Could you please post the link for me? Thank you so much!
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@suhangpro What is the main change of your new branch th14 to solve the problem of type2backend’s missing, can you briefly talk about it? Thanks
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@EricPengShuai You can check the changes here. backend is no longer exposed and so we changed the implementation to just use the higher level fold
function.
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