Open malzantot opened 7 years ago
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 ?