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Thanks for the example. I tried running it using Keras v1.1.1 , However the code generates an an inconsistent shape of the generator output. The output I get is [None, 400, 28, 1] instead of [None, 1, 28, 28] Therefore, it fails to stack the two models together.
Problem happens with both Theano and Tensorflow backends. any hints ?
The text was updated successfully, but these errors were encountered:
Seems like the issues comes from the Keras Convolution2D which requires to specify which dimension of input image stands for the depth.
Problem solved by adding the following , dim_ordering='th' to the Convolution2D and Sampling2D layers.
Apparently the problem is still there. Although it could successfully stack the two models after I added the dim_ordering flag. It now fails when I try to run the generative model.
It gives me the following error message ValueError: CorrMM images and kernel must have the same stack size
Hi,
Thanks for the example. I tried running it using Keras v1.1.1 , However the code generates an an inconsistent shape of the generator output. The output I get is [None, 400, 28, 1] instead of [None, 1, 28, 28] Therefore, it fails to stack the two models together.
Problem happens with both Theano and Tensorflow backends. any hints ?
The text was updated successfully, but these errors were encountered: