class_docstr: Writes `Event` protocol buffers to an event file via the graph.
  
  The `EventFileWriterV2` class is backed by the summary file writer in the v2
  summary API (currently in tf.contrib.summary), so it uses a shared summary
  writer resource and graph ops to write events.
  
  As with the original EventFileWriter, this class will asynchronously write
  Event protocol buffers to the backing file. The Event file is encoded using
  the tfrecord format, which is similar to RecordIO.
class_docstr_tok: ["Writes","`","Event","`","protocol","buffers","to","an","event","file","via","the","graph",".","The","`","EventFileWriterV2","`","class","is","backed","by","the","summary","file","writer","in","the","v2","summary","API","(","currently","in","tf.contrib.summary",")",",","so","it","uses","a","shared","summary","writer","resource","and","graph","ops","to","write","events",".","As","with","the","original","EventFileWriter",",","this","class","will","asynchronously","write","Event","protocol","buffers","to","the","backing","file",".","The","Event","file","is","encoded","using","the","tfrecord","format",",","which","is","similar","to","RecordIO","."]
docstr: Returns the directory where event file will be written.
docstr_tok: ["Returns","the","directory","where","event","file","will","be","written","."]
code: def get_logdir(self):
      """Returns the directory where event file will be written."""
      return self._logdir
  
file_path: tensorflow/tensorflow/python/summary/writer/event_file_writer_v2.py
imports: from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import summary_ops_v2
  from tensorflow.python.platform import gfile
label_desc: Use image node_id 2 for calling the EventFileWriterV2 obj's underlying member method code with example usage: obj.get_logdir() and returns: self