          logger.debug("Setting time-lapse feed: (input_images: '%s', batch_size: %s)",
                       images, batch_size)
  
          # MyPy can't recurse into nested dicts to get the type :(
          iterator = cast(Dict[Literal["a", "b"], Generator[BatchType, None, None]],
                          self._display_feeds["timelapse"])
  
          for side in get_args(Literal["a", "b"]):
              imgs = images[side]
              logger.debug("Setting preview feed: (side: '%s', images: %s)", side, len(imgs))
  
 
</s> remove         batchsizes: List[int] = []
        feed: Dict[Literal["a", "b"], np.ndarray] = {}
        samples: Dict[Literal["a", "b"], np.ndarray] = {}
        masks: Dict[Literal["a", "b"], np.ndarray] = {}
 </s> add         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> remove         iterator = cast(Dict[Literal["a", "b"], Generator[BatchType, None, None]],
                        self._display_feeds["timelapse" if is_timelapse else "preview"])
 </s> add         iterator = T.cast(T.Dict[Literal["a", "b"], T.Generator[BatchType, None, None]],
                          self._display_feeds["timelapse" if is_timelapse else "preview"]) </s> remove         retval: Dict[Literal["a", "b"], Generator[BatchType, None, None]] = {}
 </s> add         retval: T.Dict[Literal["a", "b"], T.Generator[BatchType, None, None]] = {} </s> remove         retval: Dict[Literal["a", "b"], List[np.ndarray]] = {}
 </s> add         retval: T.Dict[Literal["a", "b"], T.List[np.ndarray]] = {} </s> remove                  model: "ModelBase",
                 images: Dict[Literal["a", "b"], List[str]],
 </s> add                  model: ModelBase,
                 images: T.Dict[Literal["a", "b"], T.List[str]],
        iterator = T.cast(T.Dict[Literal["a", "b"], T.Generator[BatchType, None, None]],
                          self._display_feeds["timelapse"])
          logger.debug("Setting time-lapse feed: (input_images: '%s', batch_size: %s)",
                       images, batch_size)
  
          # MyPy can't recurse into nested dicts to get the type :(
        iterator = T.cast(T.Dict[Literal["a", "b"], T.Generator[BatchType, None, None]],
                          self._display_feeds["timelapse"])
        iterator = T.cast(T.Dict[Literal["a", "b"], T.Generator[BatchType, None, None]],
                          self._display_feeds["timelapse"])
  
          for side in get_args(Literal["a", "b"]):
              imgs = images[side]
              logger.debug("Setting preview feed: (side: '%s', images: %s)", side, len(imgs))
  
keep keep keep keep replace replace keep keep keep keep keep
 Remove plaidML support (#1325)

* Remove PlaidML reference from readme files

* Remove AMD option from installers

* remove amd requirements and update setup.py

* remove plaidml test from CI workflow

* gpustats: remove plaidml backend

* plaid removals:
  - faceswap.py - python version check
  - setup.cfg - plaidml typing ignore
  - lib.keras_utils - All plaid code
  - lib.launcher.py - All plaidml checks and configuration

* remove tf2.2 specific code from GUI event reader

* lib.model - remove all plaidml implementations

* plugins.extract - remove plaidml code

* plugins.train remove plaidml code

* lib.convert - remove plaidml code

* tools.model: remove plaidml code

* Remove plaidML tests from unit tests

* remove plaidml_utils and docsting cleanups

* Remove plaidML refs from configs

* fix keras imports 
plugins/train/trainer/_base.py