class_docstr: Writes protocol buffers to event files to be consumed by TensorBoard.
  
  The `FileWriter` class provides a mechanism to create an event file in a
  given directory and add summaries and events to it. The class updates the
  file contents asynchronously. This allows a training program to call methods
  to add data to the file directly from the training loop, without slowing down
  training.
class_docstr_tok: ["Writes","protocol","buffers","to","event","files","to","be","consumed","by","TensorBoard",".","The","`","FileWriter","`","class","provides","a","mechanism","to","create","an","event","file","in","a","given","directory","and","add","summaries","and","events","to","it",".","The","class","updates","the","file","contents","asynchronously",".","This","allows","a","training","program","to","call","methods","to","add","data","to","the","file","directly","from","the","training","loop",",","without","slowing","down","training","."]
docstr: Add a `Graph` and step stats protocol buffer to the event file.
  
  Args:
    graph_profile: A `Graph` and step stats protocol buffer.
    walltime: float. Optional walltime to override the default (current)
      walltime (from time.time()) seconds after epoch
docstr_tok: ["Add","a","`","Graph","`","and","step","stats","protocol","buffer","to","the","event","file",".","Args",":","graph_profile",":","A","`","Graph","`","and","step","stats","protocol","buffer",".","walltime",":","float",".","Optional","walltime","to","override","the","default","(","current",")","walltime","(","from","time.time","(",")",")","seconds","after","epoch"]
code: def add_graph(self, graph_profile, walltime=None):
      """Add a `Graph` and step stats protocol buffer to the event file.
  
      Args:
        graph_profile: A `Graph` and step stats protocol buffer.
        walltime: float. Optional walltime to override the default (current)
          walltime (from time.time()) seconds after epoch
      """
      graph = graph_profile[0]
      stepstats = graph_profile[1]
      event = event_pb2.Event(graph_def=graph.SerializeToString())
      self.add_event(event, None, walltime)
  
      trm = event_pb2.TaggedRunMetadata(
          tag="step1", run_metadata=stepstats.SerializeToString()
      )
      event = event_pb2.Event(tagged_run_metadata=trm)
      self.add_event(event, None, walltime)
  
imports: import os
  import time
  from typing import List, Optional, Union, TYPE_CHECKING
  import torch
  from tensorboard.compat import tf
  from tensorboard.compat.proto import event_pb2
  from tensorboard.compat.proto.event_pb2 import Event, SessionLog
  from tensorboard.plugins.projector.projector_config_pb2 import ProjectorConfig
  from tensorboard.summary.writer.event_file_writer import EventFileWriter
  from ._convert_np import make_np
  from ._embedding import get_embedding_info, make_mat, make_sprite, make_tsv, write_pbtxt
  from ._onnx_graph import load_onnx_graph
  from ._pytorch_graph import graph
  from ._utils import figure_to_image
  from .summary import audio, custom_scalars, histogram, histogram_raw, hparams, image, image_boxes, mesh, pr_curve, pr_curve_raw, scalar, tensor_proto, text, video
label_desc: Use image node_id 5 for calling the FileWriter obj's underlying member method code with example usage: obj.add_graph(graph_profile, walltime) without return types