code: public int layerSize(String layerName) {
          Layer l = getLayer(layerName);
          if(l == null){
              throw new IllegalArgumentException("No layer with name \"" + layerName + "\" exists");
          }
          org.deeplearning4j.nn.conf.layers.Layer conf = l.conf().getLayer();
          if (conf == null || !(conf instanceof FeedForwardLayer)) {
              return 0;
          }
          FeedForwardLayer ffl = (FeedForwardLayer) conf;
  
          // FIXME: int cast
          return (int) ffl.getNOut();
      }
docs: Return the layer size (number of units) for the specified layer.<br>
  Note that the meaning of the "layer size" can depend on the type of layer. For example:<br>
  - DenseLayer, OutputLayer, recurrent layers: number of units (nOut configuration option)<br>
  - ConvolutionLayer: the channels (number of channels)<br>
  - Subsampling layers, global pooling layers, etc: size of 0 is always returned<br>
  
  @param layerName Name of the layer to get the size of
  @return Size of the layer