              retval = (hasattr(sys, "real_prefix") or
                        (hasattr(sys, "base_prefix") and sys.base_prefix != sys.prefix))
          else:
              prefix = os.path.dirname(sys.prefix)
              retval = (os.path.basename(prefix) == "envs")
          return retval
  
      def _process_arguments(self) -> None:
          """ Process any cli arguments and dummy in cli arguments if calling from updater. """
          args = [arg for arg in sys.argv]  # pylint:disable=unnecessary-comprehension
 
</s> remove             if get_backend() != "amd":
                retval = tf.image.resize(inputs, (size, size), method=self.interpolation)
            else:
                raise NotImplementedError
 </s> add             retval = tf.image.resize(inputs, (size, size), method=self.interpolation) </s> remove         retval = dict(a=encoder(inputs[0]), b=encoder(inputs[1]))
 </s> add         retval = {"a": encoder(inputs[0]), "b": encoder(inputs[1])} </s> remove             retval = dict(a=GBlock("a", input_shapes, self.config)()(inputs["a"]),
                          b=GBlock("b", input_shapes, self.config)()(inputs["b"]))
 </s> add             retval = {"a": GBlock("a", input_shapes, self.config)()(inputs["a"]),
                      "b": GBlock("b", input_shapes, self.config)()(inputs["b"])} </s> remove         if get_backend() == "amd":
            batch, height, width, depth = input_tensor.shape.dims
            new_height = height // self.scale
            new_width = width // self.scale
            reshaped = K.reshape(input_tensor,
                                 (batch, new_height, self.scale, new_width, self.scale, depth))
            retval = K.reshape(K.permute_dimensions(reshaped, [0, 1, 3, 2, 4, 5]),
                               (batch, new_height, new_width, -1))
        else:
            retval = tf.nn.space_to_depth(input_tensor, block_size=self.scale, data_format="NHWC")
 </s> add         retval = tf.nn.space_to_depth(input_tensor, block_size=self.scale, data_format="NHWC") </s> remove         retval = np.stack([cast(np.ndarray, feed_face.face)[..., :3]
 </s> add         retval = np.stack([T.cast(np.ndarray, feed_face.face)[..., :3]
            retval = os.path.basename(prefix) == "envs"
              retval = (hasattr(sys, "real_prefix") or
                        (hasattr(sys, "base_prefix") and sys.base_prefix != sys.prefix))
          else:
              prefix = os.path.dirname(sys.prefix)
            retval = os.path.basename(prefix) == "envs"
          return retval
  
      def _process_arguments(self) -> None:
          """ Process any cli arguments and dummy in cli arguments if calling from updater. """
          args = [arg for arg in sys.argv]  # pylint:disable=unnecessary-comprehension
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 
setup.py