          logger.debug("initialize %s: (args: %s, kwargs: %s)",
                       self.__class__.__name__, args, kwargs)
          logger.info("Initializing %s (%s)...", self.name, self._plugin_type.title())
          self.queue_size = 1
          self._add_queues(kwargs["in_queue"], kwargs["out_queue"], ["predict", "post"])
          self._compile_threads()
          try:
              self.init_model()
          except tf_errors.UnknownError as err:
              if "failed to get convolution algorithm" in str(err).lower():
 
</s> remove             import tensorflow as tf
 </s> add             import tensorflow as tf  # pylint:disable=import-outside-toplevel </s> remove             # Ensure tensorflow doesn't pin all threads to one core when using tf-mkl
 </s> add             # Ensure tensorflow doesn't pin all threads to one core when using Math Kernel Library </s> remove         plugin = getattr(self, "_{}".format(phase))
 </s> add         plugin_type, idx = self._get_plugin_type_and_index(phase)
        plugin = getattr(self, "_{}".format(plugin_type))
        plugin = plugin[idx] if idx is not None else plugin </s> remove         logger.info("sample filename: %s, base filename: %s", sample_filename, basename)
 </s> add         logger.debug("sample filename: %s, base filename: %s", sample_filename, basename)
        name = self.name.replace(" ", "_").lower()
        self._add_queues(kwargs["in_queue"],
                         kwargs["out_queue"],
                         ["predict_{}".format(name), "post_{}".format(name)])
          logger.debug("initialize %s: (args: %s, kwargs: %s)",
                       self.__class__.__name__, args, kwargs)
          logger.info("Initializing %s (%s)...", self.name, self._plugin_type.title())
          self.queue_size = 1
        name = self.name.replace(" ", "_").lower()
        self._add_queues(kwargs["in_queue"],
                         kwargs["out_queue"],
                         ["predict_{}".format(name), "post_{}".format(name)])
          self._compile_threads()
          try:
              self.init_model()
          except tf_errors.UnknownError as err:
              if "failed to get convolution algorithm" in str(err).lower():
keep keep keep keep replace keep keep keep keep keep
 Extraction - Auto generate Components and Extended Masks 
plugins/extract/_base.py