parameters: (self,
                 path,
                 size_guidance=DEFAULT_SIZE_GUIDANCE,
                 compression_bps=NORMAL_HISTOGRAM_BPS,
                 purge_orphaned_data=True)
docstring: Construct the `EventAccumulator`.
  
      Args:
        path: A file path to a directory containing tf events files, or a single
          tf events file. The accumulator will load events from this path.
        size_guidance: Information on how much data the EventAccumulator should
          store in memory. The DEFAULT_SIZE_GUIDANCE tries not to store too much
          so as to avoid OOMing the client. The size_guidance should be a map
          from a `tagType` string to an integer representing the number of
          items to keep per tag for items of that `tagType`. If the size is 0,
          all events are stored.
        compression_bps: Information on how the `EventAccumulator` should compress
          histogram data for the `CompressedHistograms` tag (for details see
          `ProcessCompressedHistogram`).
        purge_orphaned_data: Whether to discard any events that were "orphaned" by
          a TensorFlow restart.
docstring_summary: Construct the `EventAccumulator`.
docstring_tokens: Construct the EventAccumulator .
function: def __init__(self,
                 path,
                 size_guidance=DEFAULT_SIZE_GUIDANCE,
                 compression_bps=NORMAL_HISTOGRAM_BPS,
                 purge_orphaned_data=True):
      """Construct the `EventAccumulator`.
  
      Args:
        path: A file path to a directory containing tf events files, or a single
          tf events file. The accumulator will load events from this path.
        size_guidance: Information on how much data the EventAccumulator should
          store in memory. The DEFAULT_SIZE_GUIDANCE tries not to store too much
          so as to avoid OOMing the client. The size_guidance should be a map
          from a `tagType` string to an integer representing the number of
          items to keep per tag for items of that `tagType`. If the size is 0,
          all events are stored.
        compression_bps: Information on how the `EventAccumulator` should compress
          histogram data for the `CompressedHistograms` tag (for details see
          `ProcessCompressedHistogram`).
        purge_orphaned_data: Whether to discard any events that were "orphaned" by
          a TensorFlow restart.
      """
      sizes = {}
      for key in DEFAULT_SIZE_GUIDANCE:
        if key in size_guidance:
          sizes[key] = size_guidance[key]
        else:
          sizes[key] = DEFAULT_SIZE_GUIDANCE[key]
  
      self._first_event_timestamp = None
      self._scalars = reservoir.Reservoir(size=sizes[SCALARS])
      self._graph = None
      self._tagged_metadata = {}
      self._histograms = reservoir.Reservoir(size=sizes[HISTOGRAMS])
      self._compressed_histograms = reservoir.Reservoir(
          size=sizes[COMPRESSED_HISTOGRAMS])
      self._images = reservoir.Reservoir(size=sizes[IMAGES])
      self._audio = reservoir.Reservoir(size=sizes[AUDIO])
  
      self._generator_mutex = threading.Lock()
      self._generator = _GeneratorFromPath(path)
  
      self._compression_bps = compression_bps
      self.purge_orphaned_data = purge_orphaned_data
  
      self.most_recent_step = -1
      self.most_recent_wall_time = -1
      self.file_version = None
  
      # The attributes that get built up by the accumulator
      self.accumulated_attrs = ('_scalars', '_histograms',
                                '_compressed_histograms', '_images', '_audio')
function_tokens: def __init__ ( self , path , size_guidance = DEFAULT_SIZE_GUIDANCE , compression_bps = NORMAL_HISTOGRAM_BPS , purge_orphaned_data = True ) : sizes = { } for key in DEFAULT_SIZE_GUIDANCE : if key in size_guidance : sizes [ key ] = size_guidance [ key ] else : sizes [ key ] = DEFAULT_SIZE_GUIDANCE [ key ] self . _first_event_timestamp = None self . _scalars = reservoir . Reservoir ( size = sizes [ SCALARS ] ) self . _graph = None self . _tagged_metadata = { } self . _histograms = reservoir . Reservoir ( size = sizes [ HISTOGRAMS ] ) self . _compressed_histograms = reservoir . Reservoir ( size = sizes [ COMPRESSED_HISTOGRAMS ] ) self . _images = reservoir . Reservoir ( size = sizes [ IMAGES ] ) self . _audio = reservoir . Reservoir ( size = sizes [ AUDIO ] ) self . _generator_mutex = threading . Lock ( ) self . _generator = _GeneratorFromPath ( path ) self . _compression_bps = compression_bps self . purge_orphaned_data = purge_orphaned_data self . most_recent_step = - 1 self . most_recent_wall_time = - 1 self . file_version = None # The attributes that get built up by the accumulator self . accumulated_attrs = ( '_scalars' , '_histograms' , '_compressed_histograms' , '_images' , '_audio' )