              The inputs to the model for each side A and B
          model_targets: list
              The targets for the model for each side A and B
          """
          model_inputs: T.List[T.List[np.ndarray]] = []
          model_targets: T.List[T.List[np.ndarray]] = []
          for side in ("a", "b"):
              side_feed, side_targets = next(self._feeds[side])
              if self._model.config["learn_mask"]:  # Add the face mask as it's own target
                  side_targets += [side_targets[-1][..., 3][..., None]]
              logger.trace("side: %s, input_shapes: %s, target_shapes: %s",  # type: ignore
 
</s> remove             side = cast(Literal["a", "b"], side)
 </s> add             side = T.cast(T.Literal["a", "b"], side) </s> remove             side = cast(Literal["a", "b"], side)
 </s> add             side = T.cast(T.Literal["a", "b"], side) </s> remove         preds: T.Dict[str, np.ndarray] = {}
 </s> add         preds: dict[str, np.ndarray] = {} </s> remove         for side in get_args(Literal["a", "b"]):
 </s> add         for side in T.get_args(T.Literal["a", "b"]): </s> remove                  side: Literal["a", "b", "both"],
                 input_shapes: T.Union[list, tuple],
 </s> add                  side: T.Literal["a", "b", "both"],
                 input_shapes: list | tuple,
        model_inputs: list[list[np.ndarray]] = []
        model_targets: list[list[np.ndarray]] = []
              The inputs to the model for each side A and B
          model_targets: list
              The targets for the model for each side A and B
          """
        model_inputs: list[list[np.ndarray]] = []
        model_targets: list[list[np.ndarray]] = []
        model_inputs: list[list[np.ndarray]] = []
        model_targets: list[list[np.ndarray]] = []
          for side in ("a", "b"):
              side_feed, side_targets = next(self._feeds[side])
              if self._model.config["learn_mask"]:  # Add the face mask as it's own target
                  side_targets += [side_targets[-1][..., 3][..., None]]
              logger.trace("side: %s, input_shapes: %s, target_shapes: %s",  # type: ignore
keep keep keep keep replace 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 
plugins/train/trainer/_base.py