code: def show(imgs):
      if not isinstance(imgs, list):
          imgs = [imgs]
      fig, axs = plt.subplots(ncols=len(imgs), squeeze=False)
      for i, img in enumerate(imgs):
          img = img.detach()
          img = F.to_pil_image(img)
          axs[0, i].imshow(np.asarray(img))
          axs[0, i].set(
              xticklabels=[], yticklabels=[], xticks=[], yticks=[]
          )
  
file_path: vision/gallery/others/plot_visualization_utils.py
imports: import torch
  import numpy
  import matplotlib.pyplot
  import torchvision.transforms.functional
  from torchvision.utils import make_grid
  from torchvision.io import read_image
  from pathlib import Path
  from torchvision.utils import draw_bounding_boxes
  from torchvision.models.detection import fasterrcnn_resnet50_fpn, FasterRCNN_ResNet50_FPN_Weights
  from torchvision.models.segmentation import fcn_resnet50, FCN_ResNet50_Weights
  from torchvision.utils import draw_segmentation_masks
  from torchvision.models.detection import maskrcnn_resnet50_fpn, MaskRCNN_ResNet50_FPN_Weights
  from torchvision.models.detection import keypointrcnn_resnet50_fpn, KeypointRCNN_ResNet50_FPN_Weights
  from torchvision.io import read_image
  from torchvision.utils import draw_keypoints
label_desc: Use image node_id 1 for calling a global function with example usage: show(imgs) without return types