code: def _plot_transform(
      orig_img, imgs, with_orig=True, row_title=None, **imshow_kwargs
  ):
      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
  
      if not isinstance(imgs[0], list):
          imgs = [imgs]
      num_rows = len(imgs)
      num_cols = len(imgs[0]) + with_orig
      _, axs = plt.subplots(
          nrows=num_rows,
          ncols=num_cols,
          squeeze=False,
          figsize=(12, 12),
      )
      for row_idx, row in enumerate(imgs):
          row = [orig_img] + row if with_orig else row
          for col_idx, img in enumerate(row):
              ax = axs[row_idx, col_idx]
              ax.imshow(np.asarray(img), **imshow_kwargs)
              ax.set(
                  xticklabels=[], yticklabels=[], xticks=[], yticks=[]
              )
      if with_orig:
          axs[0, 0].set(title="Original image")
          axs[0, 0].title.set_size(8)
      if row_title is not None:
          for row_idx in range(num_rows):
              axs[row_idx, 0].set(ylabel=row_title[row_idx])
  
      plt.tight_layout()
      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 5 for calling a global function with example usage: _plot_transform(orig_img, imgs, with_orig, row_title) without return types