class_docstr: Base class for debug event data monitors.
class_docstr_tok: ["Base","class","for","debug","event","data","monitors","."]
docstr: Monitor method for intra-graph execution events.
  
  Return values (if any) are ignored by the associated DebugDataReader.
  
  Args:
    graph_execution_trace_index: The index of the intra-graph execution
      event, as an int.
    graph_execution_trace: A GraphExecutionTrace data object, for an
      intra-graph tensor event.
docstr_tok: ["Monitor","method","for","intra-graph","execution","events",".","Return","values","(","if","any",")","are","ignored","by","the","associated","DebugDataReader",".","Args",":","graph_execution_trace_index",":","The","index","of","the","intra-graph","execution","event",",","as","an","int",".","graph_execution_trace",":","A","GraphExecutionTrace","data","object",",","for","an","intra-graph","tensor","event","."]
code: def on_graph_execution_trace(
      self, graph_execution_trace_index, graph_execution_trace
  ):
      """Monitor method for intra-graph execution events.
  
      Return values (if any) are ignored by the associated DebugDataReader.
  
      Args:
        graph_execution_trace_index: The index of the intra-graph execution
          event, as an int.
        graph_execution_trace: A GraphExecutionTrace data object, for an
          intra-graph tensor event.
      """
  
imports: import numpy
  from tensorflow.core.protobuf import debug_event_pb2
label_desc: Use image node_id 3 for calling the BaseMonitor obj's underlying member method code with example usage: obj.on_graph_execution_trace(graph_execution_trace_index, graph_execution_trace) without return types