code: def test_standardize_and_clip_with_custom_min_max():
      custom_min = 2.0
      custom_max = 3.0
  
      input_ = torch.randint(
          low=-1000, high=1000, size=(224, 224)
      ).float()
      normalized = standardize_and_clip(
          input_, min_value=custom_min, max_value=custom_max
      )
  
      assert normalized.shape == input_.shape
      assert normalized.min() >= custom_min
      assert normalized.max() <= custom_max
  
imports: import pytest
  from os import path
  from PIL import Image
  import numpy
  import torch
  from flashtorch.utils import load_image, apply_transforms, denormalize, standardize_and_clip, format_for_plotting
label_desc: Use image node_id 16 for calling a global function with example usage: test_standardize_and_clip_with_custom_min_max() without return types