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Switching to eval mode after 100k iterations #14

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amirbar opened this issue Aug 4, 2019 · 0 comments

amirbar commented Aug 4, 2019

Thanks for sharing the code and for the great work on this.

While looking at the training code, I've came across the following line: https://github.com/google/sg2im/blob/master/scripts/train.py#L510

It seems in this line you switch the model to eval mode (although existence of batchnorm/dropout layers) and create a new optimizer instance.

I'm wondering what is the justifications for this or whether you have found this to be useful for particular reason?

Thanks you so much for your time.

Best,
Amir

amirbar closed this as completed

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