class_docstr: The ``TemplateVisualization`` class is a :class:`~flash.core.data.callbacks.BaseVisualization` that just prints
  the data.
  
  If you want to provide a visualization with your task, you can override these hooks.
code: def show_load_sample(
      self,
      samples: List[Any],
      running_stage: RunningStage,
      limit_nb_samples: int = None,
      figsize: Tuple[int, int] = (6.4, 4.8),
  ):
      print(samples)
  
imports: from typing import Any, Callable, Collection, Dict, List, Optional, Sequence, Tuple, Type
  import numpy
  import torch
  from flash.core.data.base_viz import BaseVisualization
  from flash.core.data.callback import BaseDataFetcher
  from flash.core.data.data_module import DataModule
  from flash.core.data.io.classification_input import ClassificationInputMixin
  from flash.core.data.io.input import DataKeys, Input
  from flash.core.data.io.input_transform import InputTransform
  from flash.core.data.utilities.classification import TargetFormatter
  from flash.core.data.utilities.samples import to_samples
  from flash.core.utilities.imports import _SKLEARN_AVAILABLE
  from flash.core.utilities.stages import RunningStage
  from flash.core.utilities.types import INPUT_TRANSFORM_TYPE
label_desc: Use image node_id 1 for calling the TemplateVisualization obj's underlying member method code with example usage: obj.show_load_sample(samples, running_stage, limit_nb_samples, figsize) without return types