code: def call_func(f, backend, tensors):
      """
      Call and evaluate a function with corresponding tensors, returns a numpy array.
  
      Arguments:
          f (lambda): Usage f(backend, *tensors)
          backend (Backend or numpy): one of (np, NervanaGPU, NervanaCPU, NervanaMKL)
          tensors (list): list of tensors
  
      Returns:
          numpy.ndarray: the evaluated result of f
      """
      if backend == np:
          return f(backend, *tensors)
      else:
          op_tree = f(backend, *tensors)
          op_tree_val = backend.empty(op_tree.shape)
          op_tree_val[:] = op_tree
          return op_tree_val.get()
  
file_path: neon/tests/utils.py
imports: from builtins import zip
  import numpy
  import numpy.random
  from neon import logger
  from neon.backends.backend import Tensor
label_desc: Use image node_id 4 for calling a global function with example usage: call_func(f, backend, tensors) and returns: f, op_tree_val