code: def show_image_relevance(
      image_relevance: torch.Tensor,
      img_tensor: torch.Tensor,
      orig_image: Image,
  ):
      """
      Show the image relevance heatmap.
      Args:
          image_relevance (`torch.Tensor`):
              Image relevance.
          img_tensor (`torch.Tensor`):
              Transformed image tensor.
          orig_image (`Image`):
              Original input image.
      """
      if not is_matplotlib_available():
          models_log.warning("Matplotlib is not available.")
      from towhee.utils.matplotlib_utils import matplotlib
      import matplotlib.pylab as plt  # pylint: disable=import-outside-toplevel
  
      _, axs = plt.subplots(1, 2)
      axs[0].imshow(orig_image)
      axs[0].axis("off")
      vis = _reshape_attr_and_get_heatmap(image_relevance, img_tensor)
      axs[1].imshow(vis)
      axs[1].axis("off")
      plt.show()
  
file_path: towhee/towhee/models/visualization/clip_visualization.py
imports: from typing import List, Tuple, Callable
  from torchvision.transforms import Compose, Resize, CenterCrop, ToTensor, Normalize
  from torch import nn
  from towhee.utils.pil_utils import PILImage
  from towhee.models.visualization.transformer_visualization import _reshape_attr_and_get_heatmap
  from towhee.models import clip
  from towhee.models.clip import SimpleTokenizer
  from towhee.trainer.utils.file_utils import is_captum_available, is_matplotlib_available
  from towhee.utils.log import models_log
  import torch
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: show_image_relevance(image_relevance, img_tensor, orig_image) without return types