                             self._images[side] if images is None else images,
                             self._batch_size if batch_size is None else batch_size)
          return retval
  
      def _set_preview_feed(self) -> T.Dict[Literal["a", "b"], T.Generator[BatchType, None, None]]:
          """ Set the preview feed for this feeder.
  
          Creates a generator from :class:`lib.training_data.PreviewDataGenerator` specifically
          for previews for the feeder.
  
 
</s> remove                            images: T.Dict[Literal["a", "b"], T.List[str]],
 </s> add                            images: dict[T.Literal["a", "b"], list[str]], </s> remove                         batch_size: T.Optional[int] = None,
                        images: T.Optional[T.List[str]] = None) -> DataGenerator:
 </s> add                         batch_size: int | None = None,
                        images: list[str] | None = None) -> DataGenerator: </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                         side: Literal["a", "b"],
 </s> add                         side: T.Literal["a", "b"], </s> remove         retval: T.Optional[T.Callable[[np.ndarray],
                           T.List[bytes]]] = None if test is None else self._writer.pre_encode
 </s> add         retval: Callable[[np.ndarray],
                         list[bytes]] | None = None if test is None else self._writer.pre_encode
    def _set_preview_feed(self) -> dict[T.Literal["a", "b"], Generator[BatchType, None, None]]:
                             self._images[side] if images is None else images,
                             self._batch_size if batch_size is None else batch_size)
          return retval
  
    def _set_preview_feed(self) -> dict[T.Literal["a", "b"], Generator[BatchType, None, None]]:
          """ Set the preview feed for this feeder.
  
          Creates a generator from :class:`lib.training_data.PreviewDataGenerator` specifically
          for previews for the feeder.
  
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 
plugins/train/trainer/_base.py