                  tf.config.experimental.set_memory_growth(gpu, True)
              logger.debug("Set Tensorflow 'allow_growth' option")
  
      @classmethod
      def _set_keras_mixed_precision(cls, use_mixed_precision: bool, exclude_gpus: bool) -> bool:
          """ Enable the Keras experimental Mixed Precision API.
  
          Enables the Keras experimental Mixed Precision API if requested in the user configuration
          file.
  
 
</s> remove         logger.debug("use_mixed_precision: %s, exclude_gpus: %s",
                     use_mixed_precision, exclude_gpus)
        if not use_mixed_precision:
 </s> add         logger.debug("use_mixed_precision: %s", use_mixed_precision)
        if not use_mixed_precision and get_backend() == "amd": </s> remove         exclude_gpus: bool
            ``True`` If connected GPUs are being excluded otherwise ``False``.
 </s> add  </s> remove         logger.info("Enabling Mixed Precision Training.")
 </s> add         if not use_mixed_precision:
            policy = mixedprecision.Policy('float32')
            mixedprecision.set_global_policy(policy)
            logger.debug("Disabling mixed precision. (Compute dtype: %s, variable_dtype: %s)",
                         policy.compute_dtype, policy.variable_dtype)
            return False
    def _set_keras_mixed_precision(cls, use_mixed_precision: bool) -> bool:
                  tf.config.experimental.set_memory_growth(gpu, True)
              logger.debug("Set Tensorflow 'allow_growth' option")
  
      @classmethod
    def _set_keras_mixed_precision(cls, use_mixed_precision: bool) -> bool:
          """ Enable the Keras experimental Mixed Precision API.
  
          Enables the Keras experimental Mixed Precision API if requested in the user configuration
          file.
  
keep keep keep keep replace keep keep keep keep keep
 Enable change of precision for existing models 
plugins/train/model/_base/settings.py