      loss: list[float]
          The loss values collected for A and B sides for the event step
      """
      timestamp: float = 0.0
      loss: List[float] = field(default_factory=list)
  
  
  class _LogFiles():
      """ Holds the filenames of the Tensorflow Event logs that require parsing.
  
 
</s> remove     def __init__(self, labels: List[str], timestamps: np.ndarray, loss: np.ndarray) -> None:
 </s> add     def __init__(self, labels: list[str], timestamps: np.ndarray, loss: np.ndarray) -> None: </s> remove         self._loss = zlib.compress(cast(bytes, loss))
        self._timestamps = zlib.compress(cast(bytes, timestamps))
 </s> add         self._loss = zlib.compress(T.cast(bytes, loss))
        self._timestamps = zlib.compress(T.cast(bytes, timestamps)) </s> remove         retval: Dict[int, Dict[str, np.ndarray]] = {}
 </s> add         retval: dict[int, dict[str, np.ndarray]] = {} </s> remove     detected_faces: List[List["DetectedFace"]] = field(default_factory=list)
    rotation_matrix: List[np.ndarray] = field(default_factory=list)
    scale: List[float] = field(default_factory=list)
    pad: List[Tuple[int, int]] = field(default_factory=list)
 </s> add     detected_faces: list[list["DetectedFace"]] = field(default_factory=list)
    rotation_matrix: list[np.ndarray] = field(default_factory=list)
    scale: list[float] = field(default_factory=list)
    pad: list[tuple[int, int]] = field(default_factory=list) </s> remove     filenames: List[str] = field(default_factory=list)
    matrix: List[np.ndarray] = field(default_factory=list)
    src: List[np.ndarray] = field(default_factory=list)
    dst: List[np.ndarray] = field(default_factory=list)
 </s> add     filenames: list[str] = field(default_factory=list)
    matrix: list[np.ndarray] = field(default_factory=list)
    src: list[np.ndarray] = field(default_factory=list)
    dst: list[np.ndarray] = field(default_factory=list)
    loss: list[float] = field(default_factory=list)
      loss: list[float]
          The loss values collected for A and B sides for the event step
      """
      timestamp: float = 0.0
    loss: list[float] = field(default_factory=list)
  
  
  class _LogFiles():
      """ Holds the filenames of the Tensorflow Event logs that require parsing.
  
keep keep keep keep replace keep keep keep keep keep
 Rebase code (#1326)

* Remove tensorflow_probability requirement

* setup.py - fix progress bars

* requirements.txt: Remove pre python 3.9 packages

* update apple requirements.txt

* update INSTALL.md

* Remove python<3.9 code

* setup.py - fix Windows Installer

* typing: python3.9 compliant

* Update pytest and readthedocs python versions

* typing fixes

* Python Version updates
  - Reduce max version to 3.10
  - Default to 3.10 in installers
  - Remove incompatible 3.11 tests

* Update dependencies

* Downgrade imageio dep for Windows

* typing: merge optional unions and fixes

* Updates
  - min python version 3.10
  - typing to python 3.10 spec
  - remove pre-tf2.10 code
  - Add conda tests

* train: re-enable optimizer saving

* Update dockerfiles

* Update setup.py
  - Apple Conda deps to setup.py
  - Better Cuda + dependency handling

* bugfix: Patch logging to prevent Autograph errors

* Update dockerfiles

* Setup.py - Setup.py - stdout to utf-8

* Add more OSes to github Actions

* suppress mac-os end to end test 
lib/gui/analysis/event_reader.py