class_docstr: MKLTensor, special for MKL Backend
class_docstr_tok: ["MKLTensor",",","special","for","MKL","Backend"]
code: def __init__(
      self,
      backend,
      shape=None,
      dtype=np.float32,
      ary=None,
      name=None,
      persist_values=True,
      base=None,
  ):
      super(MKLTensor, self).__init__(
          backend, shape, dtype, ary, name, persist_values, base
      )
  
      # add 4 address for cpu layout and buffer, mkl layout and buffer
      self.primitive = np.zeros((4), dtype=np.uint64)
      if ary is not None:
          self.primitive[1] = self._tensor.ctypes.data
      self.shape5D = None
  
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 1 to create a new MKLTensor object from inherited base classes: CPUTensor with example: obj = MKLTensor(backend, shape, dtype, ary, name, persist_values, base)