class_docstr: MKL Backend
class_docstr_tok: ["MKL","Backend"]
code: def convert_data(self, tensor, layer_mkl):
      if not layer_mkl and tensor is not None:
          if type(tensor) == MKLTensor:
              self.convert(tensor)
              tensor.clean_mkl()
          elif type(tensor) is list or type(tensor) is tuple:
              for i in tensor:
                  self.convert_data(i, layer_mkl)
          elif type(tensor) is OpTreeNode or type(tensor) is np.ndarray:
              return
          else:
              assert False, "unsupported input for convert " + str(
                  type(tensor)
              )
  
imports: from __future__ import division
  from builtins import zip
  import logging
  from neon.backends import layer_mkl
  from neon.backends.util.check_mkl import get_mkl_lib
  from neon.backends.nervanacpu import CPUTensor, NervanaCPU, CustomNumpy
  import ctypes
  from cffi import FFI
  from ctypes import c_longlong, c_float, c_double, c_int
  import numpy
  from neon.backends import math_cpu
  from neon.backends.backend import OpTreeNode
  import os
  import sys
label_desc: Use image node_id 5 for calling the NervanaMKL obj's underlying member method code with example usage: obj.convert_data(tensor, layer_mkl) without return types