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Two issues regarding the implementation #1

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hubert0527 opened this issue Dec 27, 2019 · 3 comments
Open

Two issues regarding the implementation #1

hubert0527 opened this issue Dec 27, 2019 · 3 comments

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@hubert0527
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Thanks for your interest in COCO-GAN and your effort in implementing it in Pytorch!

I took a quick look and found two issues (not sure if there is still any other) that may cause your model failed to converge:

  1. The implementation of CBN is wrong, the mean_rec and var_rec needs to be tracked for each iteration. It should work very similarly to the standard batch norm. You may refer to this:
    https://discuss.pytorch.org/t/conditional-batch-normalization/14412/2

  2. You will have to implement a GPU version for micro-patch-to-macro-patch conversion. Otherwise, there will be no gradient propagation from the discriminator for the generator adversarial training.

@shaanrockz
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Thank you for pointing out, appreciated. Will update the code.
The code was debugged and run on the cpu for implementation, I should have added this in the description, my bad. Anyways I will also add the gpu implementation of the functions soon.

@waydegilliam
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Have these issues been fixed yet?

@shaanrockz
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Have these issues been fixed yet?

Hi, sorry for late reply. I will update the codebase soon.

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