Will the Convolutor be a GAN - Generative Adversarial Network

My CNN Condor has been coming on leaps and bounds trained on MINST data performs admireably only after 205 iterations of training.

Fig 1 These are the Minst images after successive discriminating filters with preloaded weights.

However I cannot get it to perform as a GAN - Generative Adversarial Network.

I have created purpose built functions that assemble the GAN's elements -

Generator - A series of RGB Convolution layers in the literature they are of varying size and donot have a Pool layer or an MLP layer.

Discriminator - Well this is just the CNN pretrained with its preloaded weights which takes as its input the output of the generator - and feeds back the error.

I have tested it with an MLP layer and without but I have yet to vary the size of each layer.

What I get with training is simply an image that looks like an untuned TV with the contrast on high. Its dark mush but it may yet deliver some results after I vary the

size of the layers and perhaps play around with their transfer functions.

Interestingly the MLP included produces the same result even after training.

Random Code -> MLP1 -> Layer 1...3 -> Output Image 100x100

->Input to CNN -> MLP2 Generate Error -> Feedback Error to MLP1 and Layer 1..3

Nice try.