class_docstr: Converts data from dataloader to a tuple of tuples with first element as
  the input tuple and second element as the target tuple.
code: def transform(self, t):
      if len(self._data) > 1:
          data = tuple(t[ii] for ii in self._data)
      else:
          data = t[self._data[0]]
  
      if len(self._target) > 1:
          target = tuple(t[ii] for ii in self._target)
      else:
          target = t[self._target[0]]
  
      return (data, target)
  
imports: from __future__ import division
  import numpy
  from neon import NervanaObject
label_desc: Use image node_id 2 for calling the Retuple obj's underlying member method code with example usage: obj.transform(t) and returns: data,  target