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Progressive Growing of GANs for Improved Quality, Stability, and Variation

Results 11 progressive_growing_of_gans issues
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**The problem** In Python when comparing to non-singleton values, it advised to use the operator '==' instead of 'is'. By doing otherwise, we may fall into the a code pitfall...

![screenshot from 2018-08-24 23-09-35](https://user-images.githubusercontent.com/29811853/44614460-e1fa4680-a7f2-11e8-8e97-3d41932081a9.png) I have received an assert error when I try to create the tfrecord. Could you help? I could provide more details.

thank you for your work, i try to get the celeba-hq dataset (with h5tool.py), but only get 30000 img files. i find that the given image_list.txt in the given google...

Listing TensorFlow dependency as ```tensorflow-gpu>=1.6.0``` gives compatibility errors as TensorFlow 2 was released, with major changes.

Add method for reversing GAN to get latent representation for images. This can help with future utilisation of the generator network. Also this pr removes some trailing space.

…images without breaking loop to function create_with_images.

Non-functional changes to run with Python 3. Incremental printing looks uglier in python 3 unfortunately (`print 'foo', => print('foo',end=' ')`), but the result should be the same.

I think it is a bug. We should configure training set before creating TrainingSchedule.