class_docstr: Represents a debugger-decorated graph.
code: def __init__(self, debug_graph_def, device_name=None):
      self._debug_graph_def = debug_graph_def
      self._non_debug_graph_def = None
  
      self._node_attributes = {}
      self._node_inputs = {}
      self._node_reversed_ref_inputs = {}
      self._node_ctrl_inputs = {}
      self._node_recipients = {}
      self._node_ctrl_recipients = {}
      self._node_devices = {}
      self._node_op_types = {}
      self._copy_send_nodes = []
      self._ref_args = {}
  
      self._device_name = device_name
      if not self._device_name:
          self._device_name = _infer_device_name(debug_graph_def)
  
      for node in debug_graph_def.node:
          self._process_debug_graph_node(node)
  
      self._prune_non_control_edges_of_debug_ops()
      self._prune_control_edges_of_debug_ops()
      self._prune_nodes_from_input_and_recipient_maps(
          self._get_copy_nodes()
      )
  
      self._populate_recipient_maps()
  
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 1 to create a new DebugGraph object from inherited base classes: object with example: obj = DebugGraph(debug_graph_def, device_name)