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StyleGAN training #1446

Merged
merged 45 commits into from
Sep 17, 2020
Merged

StyleGAN training #1446

merged 45 commits into from
Sep 17, 2020

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xdeng7
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@xdeng7 xdeng7 commented Sep 16, 2020

Pull request for adding training for StyleGAN

@mli
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mli commented Sep 16, 2020

Job PR-1446-1 is done.
Docs are uploaded to http://gluon-vision-staging.s3-website-us-west-2.amazonaws.com/PR-1446/1/index.html
Code coverage of this PR: pr.svg vs. Master: master.svg

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Minor comments, otherwise LGTM. Thank you for the contribution.

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*Notes for training*
1) The original tensorflow implementation can't be 100% converted by MXNet. Two functions are missing, gradient penalty and blur. The lack of gradient penalty can cause mode collapse while training, so it is neccessary to tune the learning rate based on the number of GPUs and apply early stop. The lack of blur function results in the low image quality and this is one of the important reasons that high-resolution images can't be generted via our implementation.
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Please add links to gradient penalty and blur function in original Tensorflow implementation, so that people interested can go check it out.

Besides, generted -> generated, just a typo.


*Notes for training*
1) The original tensorflow implementation can't be 100% converted by MXNet. Two functions are missing, gradient penalty and blur. The lack of gradient penalty can cause mode collapse while training, so it is neccessary to tune the learning rate based on the number of GPUs and apply early stop. The lack of blur function results in the low image quality and this is one of the important reasons that high-resolution images can't be generted via our implementation.
2) This is an unstable version of StyleGAN. We've tested the training by using 8 GPUs and single GPU. Single GPU can be problematic. The following images are generated by a model trained with 8 GPUs.
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This is an unstable version of StyleGAN -> The training of StyleGAN is not stable at this moment due to the aforementioned reasons.

*Notes for training*
1) The original tensorflow implementation can't be 100% converted by MXNet. Two functions are missing, gradient penalty and blur. The lack of gradient penalty can cause mode collapse while training, so it is neccessary to tune the learning rate based on the number of GPUs and apply early stop. The lack of blur function results in the low image quality and this is one of the important reasons that high-resolution images can't be generted via our implementation.
2) This is an unstable version of StyleGAN. We've tested the training by using 8 GPUs and single GPU. Single GPU can be problematic. The following images are generated by a model trained with 8 GPUs.
3) It takes around 4 days with 8 GPUs to train a StyleGAN to generate 128x128 images.
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What GPU? 8 GPUs -> 8 K80 GPUs

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All minor changes have been done. Please check.

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mli commented Sep 17, 2020

Job PR-1446-2 is done.
Docs are uploaded to http://gluon-vision-staging.s3-website-us-west-2.amazonaws.com/PR-1446/2/index.html
Code coverage of this PR: pr.svg vs. Master: master.svg

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mli commented Sep 17, 2020

Job PR-1446-3 is done.
Docs are uploaded to http://gluon-vision-staging.s3-website-us-west-2.amazonaws.com/PR-1446/3/index.html
Code coverage of this PR: pr.svg vs. Master: master.svg

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mli commented Sep 17, 2020

Job PR-1446-4 is done.
Docs are uploaded to http://gluon-vision-staging.s3-website-us-west-2.amazonaws.com/PR-1446/4/index.html
Code coverage of this PR: pr.svg vs. Master: master.svg

@bryanyzhu bryanyzhu merged commit cf767a1 into dmlc:master Sep 17, 2020
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3 participants