class_docstr: Node class for the tfssa graph.
  
  name: The name of the node (str)
  op: The operation represented by the node (str)
  datatype: The type of the node. (type)
  value: The value of the node if available
  inputs: The list of nodes which are inputs to this node (list[str])
  control_inputs: The list of nodes which have to be executed before this node (list[str])
  attr: The attributes of the node
  outputs: The list of nodes which consume the result of this node (list[str])
  control_outputs: The list of nodes which have to be executed after this node (list[str])
code: def _copy_impl(self, dest):
      dest.name = self.name
      dest.op = self.op
      dest.datatype = self.datatype
      dest.value = copy.deepcopy(self.value)
      dest.inputs = self.inputs[:]
      dest.control_inputs = self.control_inputs[:]
      dest.outputs = self.outputs[:]
      dest.control_outputs = self.control_outputs[:]
      dest.attr = {k: copy.deepcopy(v) for k, v in self.attr.items()}
      return dest
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import copy
  import logging
  from coremltools.converters.mil.mil import types
  from .basic_graph_ops import check_connections, const_determined_nodes
  from .dot_visitor import DotVisitor
  from .naming_utils import escape_fn_name
label_desc: Use image node_id 3 for calling the ParsedNode obj's underlying member method code with example usage: obj._copy_impl(dest) and returns: dest