          -------
          :class:`numpy.ndarry`
              A compiled preview image ready for display or saving
          """
          figures: T.Dict[Literal["a", "b"], np.ndarray] = {}
          headers: T.Dict[Literal["a", "b"], np.ndarray] = {}
  
          for side, samples in self.images.items():
              other_side = "a" if side == "b" else "b"
              preds = [predictions[f"{side}_{side}"],
                       predictions[f"{other_side}_{side}"]]
 
</s> remove         feeds: T.Dict[Literal["a", "b"], np.ndarray] = {}
        for idx, side in enumerate(get_args(Literal["a", "b"])):
 </s> add         feeds: dict[T.Literal["a", "b"], np.ndarray] = {}
        for idx, side in enumerate(T.get_args(T.Literal["a", "b"])): </s> remove         batchsizes: T.List[int] = []
        feed: T.Dict[Literal["a", "b"], np.ndarray] = {}
        samples: T.Dict[Literal["a", "b"], np.ndarray] = {}
        masks: T.Dict[Literal["a", "b"], np.ndarray] = {}
 </s> add         batchsizes: list[int] = []
        feed: dict[T.Literal["a", "b"], np.ndarray] = {}
        samples: dict[T.Literal["a", "b"], np.ndarray] = {}
        masks: dict[T.Literal["a", "b"], np.ndarray] = {} </s> remove         iterator = T.cast(T.Dict[Literal["a", "b"], T.Generator[BatchType, None, None]],
 </s> add         iterator = T.cast(dict[T.Literal["a", "b"], "Generator[BatchType, None, None]"], </s> remove         lm_side: Literal["a", "b"] = "a" if self._side == "b" else "b"
 </s> add         lm_side: T.Literal["a", "b"] = "a" if self._side == "b" else "b" </s> remove                        feed: T.Dict[Literal["a", "b"], np.ndarray],
                       samples: T.Dict[Literal["a", "b"], np.ndarray],
                       masks: T.Dict[Literal["a", "b"], np.ndarray]
                       ) -> T.Dict[Literal["a", "b"], T.List[np.ndarray]]:
 </s> add                        feed: dict[T.Literal["a", "b"], np.ndarray],
                       samples: dict[T.Literal["a", "b"], np.ndarray],
                       masks: dict[T.Literal["a", "b"], np.ndarray]
                       ) -> dict[T.Literal["a", "b"], list[np.ndarray]]:
        figures: dict[T.Literal["a", "b"], np.ndarray] = {}
        headers: dict[T.Literal["a", "b"], np.ndarray] = {}
          -------
          :class:`numpy.ndarry`
              A compiled preview image ready for display or saving
          """
        figures: dict[T.Literal["a", "b"], np.ndarray] = {}
        headers: dict[T.Literal["a", "b"], np.ndarray] = {}
        figures: dict[T.Literal["a", "b"], np.ndarray] = {}
        headers: dict[T.Literal["a", "b"], np.ndarray] = {}
  
          for side, samples in self.images.items():
              other_side = "a" if side == "b" else "b"
              preds = [predictions[f"{side}_{side}"],
                       predictions[f"{other_side}_{side}"]]
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