code: def show_per_batch_transform(
      self,
      batch: Sequence,
      running_stage: RunningStage,
      limit_nb_samples: int = None,
      figsize: Tuple[int, int] = (6.4, 4.8),
  ) -> None:
      self.per_batch_transform_called = True
  
imports: from pathlib import Path
  from typing import Any, List, Sequence, Tuple
  import numpy
  import pytest
  import torch
  from flash.core.data.base_viz import BaseVisualization
  from flash.core.data.io.input import DataKeys
  from flash.core.data.utils import _CALLBACK_FUNCS
  from flash.core.utilities.imports import _PIL_AVAILABLE, _TOPIC_IMAGE_AVAILABLE
  from flash.core.utilities.stages import RunningStage
  from flash.image import ImageClassificationData
  from pytorch_lightning import seed_everything
  from torch import Tensor
label_desc: Use image node_id 5 for calling the CustomBaseVisualization obj's underlying member method code with example usage: obj.show_per_batch_transform(batch, running_stage, limit_nb_samples, figsize) without return types