code: def validate_model_on_gpu():
      # A quick \ crude way of checking if model is loaded in GPU
      # Assumption is -
      # 1. GPUs on test setup are only utlizied by torchserve
      # 2. Models are successfully UNregistered between subsequent calls
      import nvgpu
  
      model_loaded = False
      for info in nvgpu.gpu_info():
          if info["mem_used"] > 0 and info["mem_used_percent"] > 0.0:
              model_loaded = True
              break
      return model_loaded
  
file_path: serve/ts_scripts/sanity_utils.py
imports: import glob
  import json
  import os
  import subprocess
  import sys
  from pathlib import Path
  import torch
  from ts_scripts import marsgen
  from ts_scripts import tsutils
  from ts_scripts import utils
  from ts_scripts.tsutils import generate_grpc_client_stubs
label_desc: Use image node_id 2 for calling a global function with example usage: validate_model_on_gpu() and returns: model_loaded