code: def _show_grid(row_grid_list, cls_list):
      if not is_matplotlib_available():
          trainer_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(
          nrows=len(row_grid_list),
          ncols=len(row_grid_list[0]),
          squeeze=False,
          figsize=(13, 13),
      )
      for row, (row_gird, _) in enumerate(zip(row_grid_list, cls_list)):
          for col, img in enumerate(row_gird):
              show_img = img.numpy().transpose(1, 2, 0)
              axs[row, col].imshow(show_img)
              axs[row, col].set(
                  xticklabels=[], yticklabels=[], xticks=[], yticks=[]
              )
      plt.show()
  
imports: from typing import Optional, List, Any, Tuple
  from torchvision import transforms
  from torchvision.io import read_image
  from pathlib import Path
  from torch import nn
  from towhee.utils.pil_utils import PILImage
  from towhee.trainer.optimization.optimization import get_scheduler, get_warmup_steps
  from towhee.trainer.utils.trainer_utils import _construct_scheduler_from_config
  from towhee.trainer.training_config import TrainingConfig
  from towhee.trainer.utils.file_utils import is_captum_available, is_matplotlib_available
  from towhee.utils.log import trainer_log
  import torch
  import torch.nn.functional
  import numpy
  import random
  import os
  import copy
label_desc: Use image node_id 1 for calling a global function with example usage: _show_grid(row_grid_list, cls_list) without return types