code: def visualize(
      self, num_samples=1, use_transforms=False, *args, **kwargs
  ):
      image_paths = []
      random_samples = np.random.randint(0, len(self), size=num_samples)
  
      for idx in random_samples:
          image_paths.append(self.annotation_db[idx]["img"])
  
      images = self.image_db.from_path(
          image_paths, use_transforms=use_transforms
      )
      visualize_images(images["images"], *args, **kwargs)
  
imports: import copy
  import os
  import numpy
  import omegaconf
  import torch
  from mmf.common.sample import Sample
  from mmf.datasets.mmf_dataset import MMFDataset
  from mmf.utils.general import get_mmf_root
  from mmf.utils.visualize import visualize_images
  from PIL import Image
  from torchvision import transforms
label_desc: Use image node_id 5 for calling the HatefulMemesImageDataset obj's underlying member method code with example usage: obj.visualize(num_samples, use_transforms) without return types