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@roestigraben you can remove the optional argument activation=LeakyReLU() from the Convolution2D() layer and add an extra layer with the activations just after each convolutional layer:
I use Keras v0.3.3 and the parameter
activation=LeakyReLU()
inside the model.add(Convolution2D()) method
does not work anymore compared to v0.3.2
see bug report on URL
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