          learning_rate: float
              The selected learning rate to use
          autoclip: bool
              ``True`` if AutoClip should be enabled otherwise ``False``
  
          Notes
          -----
          Clip-norm is ballooning VRAM usage, which is not expected behavior and may be a bug in
          Keras/Tensorflow.
  
          PlaidML has a bug regarding the clip-norm parameter See:
          https://github.com/plaidml/plaidml/issues/228. We workaround by simply not adding this
          parameter for AMD backend users.
          """
          lr_key = "lr" if get_backend() == "amd" else "learning_rate"
          self._kwargs[lr_key] = learning_rate
  
          if not autoclip:
 
</s> remove         lr_key = "lr" if get_backend() == "amd" else "learning_rate"
        self._kwargs[lr_key] = learning_rate

 </s> add         self._kwargs["learning_rate"] = learning_rate </s> remove         Windows + AMD + Python 3.8:
        Add CONDA_DLL_SEARCH_MODIFICATION_ENABLE=1 environment variable to get around a bug which
        prevents SciPy from loading in this config: https://github.com/scipy/scipy/issues/14002

 </s> add  </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         self._mixed_precision = self.config["mixed_precision"] and get_backend() != "amd"
 </s> add         self._mixed_precision = self.config["mixed_precision"] </s> remove     which should work on both TF and Plaid.
 </s> add     which should work on TF.
          learning_rate: float
              The selected learning rate to use
          autoclip: bool
              ``True`` if AutoClip should be enabled otherwise ``False``









          """
          lr_key = "lr" if get_backend() == "amd" else "learning_rate"
          self._kwargs[lr_key] = learning_rate
  
          if not autoclip:
keep keep keep keep replace replace replace replace replace replace 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