CycleGAN-TensorFlow
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tensorflow error raised when calculating "error_fake"
Hi, I try training on my own dataset (for images which are not square) but when TF tries to calculate the discriminator "error_fake" for some reason I get that the input and the weights belong to different graphs and thus I get the following error:
"%s must be from the same graph as %s." % (item, original_item)) ValueError: Tensor("Placeholder_1:0", shape=(1, 300, 640, 3), dtype=float32) must be from the same graph as Tensor("D_Y/C64/weights:0", shape=(4, 4, 3, 64), dtype=float32_ref).
it's weird to me since it's very similar to calculating the "error_real" (same D) only here D works on fake_y and not on y.
any idea on where this is coming from? thanks
Are all the images the same size?
yes. all 300X640X3. both A and B. moreover, it always happens on the first image (which is different every time)
Thanks for reporting! At the moment, my implementation can't work with images which are not square. The size of fake images are specified as in https://github.com/vanhuyz/CycleGAN-TensorFlow/blob/master/model.py#L58-L61. This should be fixed in future work.
Hi, I made all the necessary changes to be able to work with images which are not square. I now have image_size_h, and image_size_w parameters. good news - apparently I was not working with the latest version, so I took the latest, re-implemented my changes, and now it runs ok!. So either the issue was solved in the latest version or I made a mistake in the first time with the "image_size" changes. Either way, now I cross my fingers for good results :)
thanks