title: How to make WGAN train with RGB images instead of grayscale?
body: <p>I'm trying to implement WGAN-GP from this code </p>
  
  <p><a href="https://github.com/eriklindernoren/Keras-GAN/blob/master/wgan_gp/wgan_gp.py" rel="nofollow noreferrer">https://github.com/eriklindernoren/Keras-GAN/blob/master/wgan_gp/wgan_gp.py</a></p>
  
  <p>Instead of the default mnist dataset, I'd like to use my own dataset of images that are larger (384x384) and RGB rather than black and white.
  I tried changing the number of channels from 1 to 3 to take the colour channels into accoutn but I'm still running into the error below when training.
  Still new to this and I'm unsure of any other modifications I'd need to make my code run.</p>
  
  <p>When I use train()</p>
  
  <pre><code>ValueError: Error when checking input: expected input_28 to have 4 dimensions, but got array with shape (32, 384, 384, 1, 3)
  </code></pre>