class_docstr: ## Configurations
class_docstr_tok: ["#","#","Configurations"]
docstr: ### Generate images
  
  This generate images using the generator
docstr_tok: ["#","#","#","Generate","images","This","generate","images","using","the","generator"]
code: def generate_images(self, batch_size: int):
      """
      ### Generate images
  
      This generate images using the generator
      """
  
      # Get $w$
      w = self.get_w(batch_size)
      # Get noise
      noise = self.get_noise(batch_size)
  
      # Generate images
      images = self.generator(w, noise)
  
      # Return images and $w$
      return images, w
  
imports: import math
  from pathlib import Path
  from typing import Iterator, Tuple
  import torch
  import torch.utils.data
  import torchvision
  from PIL import Image
  from labml import tracker, lab, monit, experiment
  from labml.configs import BaseConfigs
  from labml_helpers.device import DeviceConfigs
  from labml_helpers.train_valid import ModeState, hook_model_outputs
  from labml_nn.gan.stylegan import Discriminator, Generator, MappingNetwork, GradientPenalty, PathLengthPenalty
  from labml_nn.gan.wasserstein import DiscriminatorLoss, GeneratorLoss
  from labml_nn.utils import cycle_dataloader
label_desc: Use image node_id 4 for calling the Configs obj's underlying member method code with example usage: obj.generate_images(batch_size) and returns: images,  w