code: def image_loader(image_name):
      image = Image.open(image_name)
      # fake batch dimension required to fit network's input dimensions
      image = loader(image).unsqueeze(0)
      return image.to(device, torch.float)
  
imports: from __future__ import print_function
  import os
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from PIL import Image
  import matplotlib.pyplot
  import torchvision.transforms
  import torchvision.models
  import copy
  from clearml import Task
label_desc: Use image node_id 1 for calling a global function with example usage: image_loader(image_name) and returns: image