          Parameters
          ----------
          data: dict
              The incoming tensorflow event data in dictionary form per step
          timestamps: tuple
              The raw timestamps for for the latest live query, including any partial reads
          loss: tuple
              The raw loss for for the latest live query, including any partial reads
          is_live: bool
              ``True`` if the data to be cached is from a live training session otherwise ``False``.
  
          Returns
          -------
 
</s> remove         data: dict
 </s> add         data[int, :class:`EventData`] </s> remove         labels: list
 </s> add         labels: list[str] </s> remove         dict
            The `session_id` (s) as key, the values are a dictionary containing the requested
            metric information for each session returned
 </s> add         dict or ``None``
            The `session_id`(s) as key, the values are a dictionary containing the requested
            metric information for each session returned. ``None`` if no data is stored for the
            given session_id </s> remove         data: dict
 </s> add         data: dict[int, :class:`EventData`] </s> remove         loss = list(loss)
        timestamps = list(timestamps)
 </s> add         timestamps, loss = zip(*[(data[idx].timestamp, data[idx].loss)
                               for idx in sorted(data)])
          Parameters
          ----------
          data: dict
              The incoming tensorflow event data in dictionary form per step




          is_live: bool
              ``True`` if the data to be cached is from a live training session otherwise ``False``.
  
          Returns
          -------
keep keep keep keep replace replace replace replace keep keep keep keep keep
 Bugfixes
  - plugin.train.unbalanced - decoder b
  - gui.stats - crash when log folder deleted
  - setup.py - install gcc=12.1.0 on linux (scipy dep)
  - setup.py - don't test ROCm unless valid
  - typofix - cli_args extract singleprocess help
typing
  - lib.gui.analysis.event_reader
  - lib.gpu_stats.directml - make platform specific
unit tests
  - lib.gui.analysis.event_reader 
lib/gui/analysis/event_reader.py