code: def _dict_trainable_setter(sess):
      def _set(td, raw_value, attr=None):
          if len(td) != len(raw_value):
              raise Exception("mismatch len")
          if td.keys() != raw_value.keys():
              raise Exception("mismatch keys")
          for k in td.keys():
              _trainable_setter(sess)(td[k], raw_value[k])
  
      return _set
  
imports: import tensorflow
  import numpy
  from cntk.contrib import crosstalk
label_desc: Use image node_id 4 for calling a global function with example usage: _dict_trainable_setter(sess) and returns: _set