class_docstr: Writes entries directly to event files in the log_dir to be consumed by TensorBoard.
  
  The `SummaryWriter` class provides a high-level API 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","entries","directly","to","event","files","in","the","log_dir","to","be","consumed","by","TensorBoard",".","The","`","SummaryWriter","`","class","provides","a","high-level","API","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 text data to summary.
  
  Args:
      tag (str): Data identifier
      text_string (str): String to save
      global_step (int): Global step value to record
      walltime (float): Optional override default walltime (time.time())
        seconds after epoch of event
  Examples::
  
      writer.add_text('lstm', 'This is an lstm', 0)
      writer.add_text('rnn', 'This is an rnn', 10)
docstr_tok: ["Add","text","data","to","summary",".","Args",":","tag","(","str",")",":","Data","identifier","text_string","(","str",")",":","String","to","save","global_step","(","int",")",":","Global","step","value","to","record","walltime","(","float",")",":","Optional","override","default","walltime","(","time.time","(",")",")","seconds","after","epoch","of","event","Examples",":",":","writer.add_text","(","'lstm","'",",","'This","is","an","lstm","'",",","0",")","writer.add_text","(","'rnn","'",",","'This","is","an","rnn","'",",","10",")"]
code: def add_text(self, tag, text_string, global_step=None, walltime=None):
      """Add text data to summary.
  
      Args:
          tag (str): Data identifier
          text_string (str): String to save
          global_step (int): Global step value to record
          walltime (float): Optional override default walltime (time.time())
            seconds after epoch of event
      Examples::
  
          writer.add_text('lstm', 'This is an lstm', 0)
          writer.add_text('rnn', 'This is an rnn', 10)
      """
      torch._C._log_api_usage_once("tensorboard.logging.add_text")
      self._get_file_writer().add_summary(
          text(tag, text_string), global_step, 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 17 for calling the SummaryWriter obj's underlying member method code with example usage: obj.add_text(tag, text_string, global_step, walltime) without return types