class_docstr: Derive a specific sub-class of a VAE for a CNN sentence model. 
class_docstr_tok: ["Derive","a","specific","sub-class","of","a","VAE","for","a","CNN","sentence","model","."]
code: def reconstruct(self, data, runPath, epoch):
      recon = super(CUB_Image, self).reconstruct(data[:8])
      comp = torch.cat([data[:8], recon])
      save_image(
          comp.data.cpu(), "{}/recon_{:03d}.png".format(runPath, epoch)
      )
  
imports: import torch
  import torch.distributions
  import torch.nn
  import torch.nn.functional
  import torch.utils.data
  from numpy import sqrt
  from torchvision import datasets, transforms
  from torchvision.utils import make_grid, save_image
  from utils import Constants
  from vis import plot_embeddings, plot_kls_df
  from .vae import VAE
label_desc: Use image node_id 5 for calling the CUB_Image obj's underlying member method code with example usage: obj.reconstruct(data, runPath, epoch) without return types