                           layer["name"], config["dtype"], policy)
              config["dtype"] = policy
  
      def get_mixed_precision_layers(self,
                                     build_func: Callable[[List[keras.layers.Layer]],
                                                          keras.models.Model],
                                     inputs: List[keras.layers.Layer]) -> List[str]:
          """ Get and store the mixed precision layers from a full precision enabled model.
  
          Parameters
          ----------
          build_func: Callable
 
</s> remove     def _get_mixed_precision_layers(self, layers: List[dict]) -> List[str]:
 </s> add     def _get_mixed_precision_layers(self, layers: T.List[dict]) -> T.List[str]: </s> remove     def add_mixed_precision_layers(self, layers: List[str]) -> None:
 </s> add     def add_mixed_precision_layers(self, layers: T.List[str]) -> None: </s> remove         if get_backend() == "amd":
            logger.debug("No action to perform for 'mixed_precision' on backend '%s': "
                         "use_mixed_precision: %s)", get_backend(), use_mixed_precision)
            return False

 </s> add  </s> remove             optimizer: keras.optimizers.Optimizer) -> mixedprecision.LossScaleOptimizer:
 </s> add             optimizer: tf.keras.optimizers.Optimizer) -> mixedprecision.LossScaleOptimizer: </s> remove         if get_backend() == "amd":
            logger.debug("Mixed Precision not supported for AMD. Returning empty list")
            return []
 </s> add 
                                   build_func: T.Callable[[T.List[tf.keras.layers.Layer]],
                                                          tf.keras.models.Model],
                                   inputs: T.List[tf.keras.layers.Layer]) -> T.List[str]:
                           layer["name"], config["dtype"], policy)
              config["dtype"] = policy
  
      def get_mixed_precision_layers(self,
                                   build_func: T.Callable[[T.List[tf.keras.layers.Layer]],
                                                          tf.keras.models.Model],
                                   inputs: T.List[tf.keras.layers.Layer]) -> T.List[str]:
                                   build_func: T.Callable[[T.List[tf.keras.layers.Layer]],
                                                          tf.keras.models.Model],
                                   inputs: T.List[tf.keras.layers.Layer]) -> T.List[str]:
                                   build_func: T.Callable[[T.List[tf.keras.layers.Layer]],
                                                          tf.keras.models.Model],
                                   inputs: T.List[tf.keras.layers.Layer]) -> T.List[str]:
          """ Get and store the mixed precision layers from a full precision enabled model.
  
          Parameters
          ----------
          build_func: Callable
keep keep keep keep replace 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/model/_base/settings.py