                                                                   optimizer="adam",
                                                                   mixed_precision=False)
          for key, val in _CONFIG.items():
              if key not in self._config.keys():
                  setting: "ConfigValueType" = legacy_defaults.get(key, val)
                  logger.info("Adding new config item to state file: '%s': '%s'", key, setting)
                  self._config[key] = setting
          self._update_changed_config_items(config_changeable_items)
          logger.debug("Replacing config. Old config: %s", _CONFIG)
          _CONFIG = self._config
 
</s> remove         legacy_defaults: Dict[str, Union[str, int, bool]] = dict(centering="legacy",
                                                                 mask_loss_function="mse",
                                                                 l2_reg_term=100,
                                                                 optimizer="adam",
                                                                 mixed_precision=False)
 </s> add         legacy_defaults: T.Dict[str, T.Union[str, int, bool]] = {"centering": "legacy",
                                                                 "mask_loss_function": "mse",
                                                                 "l2_reg_term": 100,
                                                                 "optimizer": "adam",
                                                                 "mixed_precision": False} </s> remove     def __init__(self, input_shape: Tuple[int, ...], config: dict) -> None:
 </s> add     def __init__(self, input_shape: T.Tuple[int, ...], config: dict) -> None: </s> remove     def _compile_preview(self, predictions: Dict[str, np.ndarray]) -> np.ndarray:
 </s> add     def _compile_preview(self, predictions: T.Dict[str, np.ndarray]) -> np.ndarray: </s> remove                  layer_indicies: Optional[Tuple[int, int]] = None) -> None:
 </s> add                  layer_indicies: T.Optional[T.Tuple[int, int]] = None) -> None: </s> remove         retval: Dict[Literal["a", "b"], Generator[BatchType, None, None]] = {}
 </s> add         retval: T.Dict[Literal["a", "b"], T.Generator[BatchType, None, None]] = {}
                setting: ConfigValueType = legacy_defaults.get(key, val)
                                                                   optimizer="adam",
                                                                   mixed_precision=False)
          for key, val in _CONFIG.items():
              if key not in self._config.keys():
                setting: ConfigValueType = legacy_defaults.get(key, val)
                  logger.info("Adding new config item to state file: '%s': '%s'", key, setting)
                  self._config[key] = setting
          self._update_changed_config_items(config_changeable_items)
          logger.debug("Replacing config. Old config: %s", _CONFIG)
          _CONFIG = self._config
keep keep keep keep 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/model/_base/model.py