class_docstr: Represents a debugger-decorated graph.
docstr: Reconstruct non-debug GraphDef.
  
  Non-debug GraphDef means the original GraphDef without the Copy* and Debug
  nodes inserted by the debugger.
docstr_tok: ["Reconstruct","non-debug","GraphDef",".","Non-debug","GraphDef","means","the","original","GraphDef","without","the","Copy","*","and","Debug","nodes","inserted","by","the","debugger","."]
code: def _reconstruct_non_debug_graph_def(self):
      """Reconstruct non-debug GraphDef.
  
      Non-debug GraphDef means the original GraphDef without the Copy* and Debug
      nodes inserted by the debugger.
      """
      if self._non_debug_graph_def:
          return
  
      self._non_debug_graph_def = graph_pb2.GraphDef()
      for node in self._debug_graph_def.node:
          if is_copy_node(node.name) or is_debug_node(node.name):
              continue
  
          new_node = self._non_debug_graph_def.node.add()
          new_node.CopyFrom(node)
  
          # Redo the list of inputs, because in _debug_graph_def, the list can
          # consist of Copy* and Debug* nodes inserted by the debugger. Those will
          # be replaced with the original inputs here.
          del new_node.input[:]
          for inp in self._node_inputs[node.name]:
              new_node.input.append(inp)
          for ctrl_inp in self._node_ctrl_inputs[node.name]:
              new_node.input.append("^" + ctrl_inp)
  
imports: from tensorflow.core.framework import graph_pb2
  from tensorflow.python.framework import op_def_registry
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 9 for calling the DebugGraph obj's underlying member method code with example usage: obj._reconstruct_non_debug_graph_def() without return types