              List of :class:`numpy.ndarray` of predictions received from the model
          """
          logger.debug("Getting Predictions")
          preds = {}
          standard = self._model.model.predict([feed_a, feed_b])
          swapped = self._model.model.predict([feed_b, feed_a])
  
          if self._model.config["learn_mask"] and get_backend() == "amd":
              # Ravel results for plaidml
              split = len(standard) // 2
              standard = [standard[:split], standard[split:]]
 
</s> remove         self._model = None
        logger.trace("Initialized: %s", self.__class__.__name__,)
 </s> add         self._model: Optional[Model] = None
        logger.trace("Initialized: %s", self.__class__.__name__,)  # type:ignore </s> remove     def _setup_amd(cls, arguments):
 </s> add     def _setup_amd(cls, arguments: "argparse.Namespace") -> bool: </s> remove     assert ((_BACKEND == "cpu" and keras.__version__ in ("2.4.0", "2.6.0", "2.7.0", "2.8.0")) or
 </s> add     assert ((_BACKEND == "cpu" and keras.__version__ in ("2.7.0", "2.8.0", "2.9.0")) or
        standard = self._model.model.predict([feed_a, feed_b], verbose=0)
        swapped = self._model.model.predict([feed_b, feed_a], verbose=0)
              List of :class:`numpy.ndarray` of predictions received from the model
          """
          logger.debug("Getting Predictions")
          preds = {}
        standard = self._model.model.predict([feed_a, feed_b], verbose=0)
        swapped = self._model.model.predict([feed_b, feed_a], verbose=0)
        standard = self._model.model.predict([feed_a, feed_b], verbose=0)
        swapped = self._model.model.predict([feed_b, feed_a], verbose=0)
  
          if self._model.config["learn_mask"] and get_backend() == "amd":
              # Ravel results for plaidml
              split = len(standard) // 2
              standard = [standard[:split], standard[split:]]
keep keep keep keep replace replace keep keep keep keep keep
 Update TF to 2.9
    - Update TF to 2.7 to 2.9
    - Bump dependencies
    - Remove decode from pynvml calls
    - force keras predict functions to non-verbose
    - update tests
    - update Tensorboard logging
    - Update docs 
plugins/train/trainer/_base.py