  
  def _get_upscale_layer(method: Literal["resize_images", "subpixel", "upscale_dny", "upscale_fast",
                                         "upscale_hybrid", "upsample2d"],
                         filters: int,
                         activation: Optional[str] = None,
                         upsamples: Optional[int] = None,
                         interpolation: Optional[str] = None) -> keras.layers.Layer:
      """ Obtain an instance of the requested upscale method.
  
      Parameters
      ----------
      method: str
 
</s> remove                  normalization: Optional[str] = None,
                 activation: Optional[str] = "leakyrelu",
 </s> add                  normalization: T.Optional[str] = None,
                 activation: T.Optional[str] = "leakyrelu", </s> remove                  activation: Optional[str] = "leakyrelu",
 </s> add                  activation: T.Optional[str] = "leakyrelu", </s> remove                  activation: Optional[str] = "leakyrelu",
 </s> add                  activation: T.Optional[str] = "leakyrelu", </s> remove                 configfile: Optional[str] = None) -> Dict[str, "ConfigValueType"]:
 </s> add                 configfile: T.Optional[str] = None) -> T.Dict[str, ConfigValueType]: </s> remove                  git_model_id: Optional[int] = None,
                 model_filename: Optional[str] = None,
                 configfile: Optional[str] = None,
 </s> add                  git_model_id: T.Optional[int] = None,
                 model_filename: T.Optional[str] = None,
                 configfile: T.Optional[str] = None,
                       activation: T.Optional[str] = None,
                       upsamples: T.Optional[int] = None,
                       interpolation: T.Optional[str] = None) -> keras.layers.Layer:
  
  def _get_upscale_layer(method: Literal["resize_images", "subpixel", "upscale_dny", "upscale_fast",
                                         "upscale_hybrid", "upsample2d"],
                         filters: int,
                       activation: T.Optional[str] = None,
                       upsamples: T.Optional[int] = None,
                       interpolation: T.Optional[str] = None) -> keras.layers.Layer:
                       activation: T.Optional[str] = None,
                       upsamples: T.Optional[int] = None,
                       interpolation: T.Optional[str] = None) -> keras.layers.Layer:
                       activation: T.Optional[str] = None,
                       upsamples: T.Optional[int] = None,
                       interpolation: T.Optional[str] = None) -> keras.layers.Layer:
      """ Obtain an instance of the requested upscale method.
  
      Parameters
      ----------
      method: str
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/phaze_a.py