code: def test_vs_numpy_mkl(backend_tests_mkl, custom_args):
      test_idx, f, flag, dim = custom_args
  
      # backend
      be = NervanaObject.be
      dtype = be.default_dtype
  
      # tensors
      tensors = gen_backend_tensors(
          [np, be], [dim] * 5, [flag] * 5, dtype=dtype
      )
  
      # compare function value and gradient
      numpy_func_val = call_func(f, np, tensors[0])
      backend_func_val = call_func(f, be, tensors[1])
  
      assert tensors_allclose(
          numpy_func_val, backend_func_val, rtol=1e-2, atol=1e-2
      )
  
file_path: neon/tests/test_backend_compound_optree.py
imports: import itertools
  import numpy
  import os
  import pytest
  import subprocess
  from neon import NervanaObject
  from utils import call_func, gen_backend_tensors, tensors_allclose
label_desc: Use image node_id 2 for calling a global function with example usage: test_vs_numpy_mkl(backend_tests_mkl, custom_args) without return types