code: def create_random_image(file_path, shape):
      img = np.random.random_sample(shape)
      img = (255.0 / img.max() * (img - img.min())).astype(np.uint8)
      res = torch.tensor(img).to(torch.float) / 255
      img = np.transpose(img, (1, 2, 0))
      img = Image.fromarray(img)
      img.save(file_path)
      return res
  
imports: import numpy
  import pytest
  import torch
  from PIL import Image
  from torchvision import transforms
  from neuralcompression.data import Kodak
label_desc: Use image node_id 1 for calling a global function with example usage: create_random_image(file_path, shape) and returns: res