mxnet implement for Conditional Wasserstein GAN

You only need to change the is_wgan flag to test wgan or dcgan results. change is_mlp to test mlp result.

generate result after 30 epochs.

wgan:

dcgan:

mlp wgan:

note:

• because we want to try mlp result, so I flatten the input image to a vector, then append condition one-hot vector to the vector. If you only want to try Convolution ops, you will not need to add condition in this way
• wgan seems not better than dcgan, maybe something wrong. If you know what happen, please let me know.
• you can learn a lot about how to construct data iterator, how to backward without output layer

Code borrows from mxnet gan example, wgan metric from WGAN