code: def test_standardize_and_clip_mono_channel_tensor():
      default_min = 0.0
      default_max = 1.0
  
      input_ = torch.randint(
          low=-1000, high=1000, size=(1, 224, 224)
      ).float()
      normalized = standardize_and_clip(input_)
  
      assert normalized.shape == input_.shape
      assert normalized.min().item() >= default_min
      assert normalized.max().item() <= default_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 17 for calling a global function with example usage: test_standardize_and_clip_mono_channel_tensor() without return types