code: def from_dlpack(dlpack):
      
      handle = NDArrayHandle()
      dlpack = ctypes.py_object(dlpack)
      assert ctypes.pythonapi.PyCapsule_IsValid(dlpack, _c_str_dltensor), ValueError(
          'Invalid DLPack Tensor. DLTensor capsules can be consumed only once.')
      dlpack_handle = ctypes.c_void_p(ctypes.pythonapi.PyCapsule_GetPointer(dlpack, _c_str_dltensor))
      check_call(_LIB.MXNDArrayFromDLPack(dlpack_handle, ctypes.byref(handle)))
      # Rename PyCapsule (DLPack)
      ctypes.pythonapi.PyCapsule_SetName(dlpack, _c_str_used_dltensor)
      # delete the deleter of the old dlpack
      ctypes.pythonapi.PyCapsule_SetDestructor(dlpack, None)
      return NDArray(handle=handle)
docs: Returns a NDArray backed by a dlpack tensor.
  
      Parameters
      ----------
      dlpack: PyCapsule (the pointer of DLManagedTensor)
          input data
  
      Returns
      -------
      NDArray
          a NDArray backed by a dlpack tensor
  
      Examples
      --------
      >>> x = mx.nd.ones((2,3))
      >>> y = mx.nd.to_dlpack_for_read(x)
      >>> type(y)
      <class 'PyCapsule'>
      >>> z = mx.nd.from_dlpack(y)
      >>> type(z)
      <class 'mxnet.ndarray.ndarray.NDArray'>
      >>> z
      [[ 1.  1.  1.]
       [ 1.  1.  1.]]
      <NDArray 2x3 @cpu(0)>
  
      >>> w = mx.nd.to_dlpack_for_write(x)
      >>> type(w)
      <class 'PyCapsule'>
      >>> u = mx.nd.from_dlpack(w)
      >>> u += 1
      >>> x
      [[2. 2. 2.]
       [2. 2. 2.]]
      <NDArray 2x3 @cpu(0)>