code: def show_batch(
      batch_and_records,
      ncols: int = 1,
      figsize=None,
      **show_samples_kwargs,
  ):
      """Show a single batch from a dataloader.
      # Arguments
          show_samples_kwargs: Check the parameters from `show_samples`
      """
      batch, records = batch_and_records
  
      for tensor_image, gt_masks, record in zip(
          batch["img"][:], batch["gt_semantic_seg"], records
      ):
          image = mmseg_tensor_to_image(tensor_image)
          record.set_img(image)
  
          mask = MaskArray(gt_masks.cpu().numpy().squeeze())
          record.segmentation.set_mask_array(mask)
  
      return show_samples(
          records, ncols=ncols, figsize=figsize, **show_samples_kwargs
      )
  
imports: from icevision.utils import *
  from icevision.visualize import *
  from icevision.models.mmseg.common.utils import *
  from icevision.core import *
label_desc: Use image node_id 1 for calling a global function with example usage: show_batch(batch_and_records, ncols, figsize) and returns: show_samples