      def initialize(self, log=False):
          """ Initialize pynvml """
          if not self.initialized:
              if K.backend() == "plaidml.keras.backend":
                  if self.logger:
                      self.logger.debug("plaidML Detected. Using plaidMLStats")
                      loglevel = self.logger.getEffectiveLevel()
                  self.plaid = plaidlib(loglevel=loglevel, log=log)
              elif IS_MACOS:
 
</s> remove                 self.plaid = plaidlib(log=log)
 </s> add                     loglevel = self.logger.getEffectiveLevel()
                self.plaid = plaidlib(loglevel=loglevel, log=log) </s> remove         numeric_level = getattr(logging, loglevel.upper(), None)
 </s> add         if isinstance(loglevel, int):
            numeric_level = loglevel
        else:
            numeric_level = getattr(logging, loglevel.upper(), None) </s> remove             from lib.plaidml_tools import setup_plaidml
            setup_plaidml(arguments.loglevel)
 </s> add             plaidml_found = self.setup_amd(arguments.loglevel)
            if not plaidml_found:
                safe_shutdown()
                exit(1)
                loglevel = "INFO"
      def initialize(self, log=False):
          """ Initialize pynvml """
          if not self.initialized:
              if K.backend() == "plaidml.keras.backend":
                loglevel = "INFO"
                  if self.logger:
                      self.logger.debug("plaidML Detected. Using plaidMLStats")
                      loglevel = self.logger.getEffectiveLevel()
                  self.plaid = plaidlib(loglevel=loglevel, log=log)
              elif IS_MACOS:
keep keep keep add keep keep keep keep keep
 PlaidML Updates

- Add fan-amd details to Cli
- Update Extract Parallel Processing rules for plaidML
- Handle missing plaidML lib on amd flag
- Pass through correct loglevel from GPUStats to plaidml_tools 
lib/gpu_stats.py