      from lib.multithreading import terminate_processes
      queue_manager.terminate_queues()
      terminate_processes()
      logger.debug("Cleanup complete. Shutting down queue manager and exiting")
      queue_manager._log_queue.put(None)  # pylint:disable=protected-access
      while not queue_manager._log_queue.empty():  # pylint:disable=protected-access
          continue
      queue_manager.manager.shutdown()
      exit(1 if got_error else 0)
  
  
  class FaceswapError(Exception):
      """ Faceswap Error for handling specific errors with useful information """
 
</s> remove     terminate_processes()
 </s> add  </s> remove     from lib.multithreading import terminate_processes
 </s> add  </s> remove         """ Return the number of passes the extractor needs to make """
        retval = 1 if self.is_parallel else 2
 </s> add         """ int: Returns the total number of passes the extractor needs to make.

        This is calculated on several factors (vram available, plugin choice,
        :attr:`multiprocess` etc.). It is useful for iterating over the pipeline
        and handling accordingly.

        Example
        -------
        >>> for phase in extractor.passes:
        >>>     if phase == 1:
        >>>         extractor.input_queue.put({"filename": "path/to/image/file",
        >>>                                    "image": np.array(image)})
        >>>     else:
        >>>         extractor.input_queue.put({"filename": "path/to/image/file",
        >>>                                    "image": np.array(image),
        >>>                                    "detected_faces": [<DetectedFace objects]})
        """
        retval = 1 if self._is_parallel else 2 </s> remove from lib.multithreading import MultiThread
 </s> add from lib.model.session import KSession </s> remove # Must import tensorflow inside the spawned process
# for Windows machines
tf = None  # pylint: disable = invalid-name


def import_tensorflow():
    """ Import tensorflow from inside spawned process """
    global tf  # pylint: disable = invalid-name,global-statement
    import tensorflow as tflow
    tf = tflow


 </s> add 
      from lib.multithreading import terminate_processes
      queue_manager.terminate_queues()
      terminate_processes()
      logger.debug("Cleanup complete. Shutting down queue manager and exiting")




      exit(1 if got_error else 0)
  
  
  class FaceswapError(Exception):
      """ Faceswap Error for handling specific errors with useful information """
keep keep keep keep replace replace replace replace keep keep keep keep keep
 De-Multiprocess Extract (#871)

* requirements.txt: - Pin opencv to 4.1.1 (fixes cv2-dnn error)

* lib.face_detect.DetectedFace: change LandmarksXY to landmarks_xy. Add left, right, top, bottom attributes

* lib.model.session: Session manager for loading models into different graphs (for Nvidia + CPU)

* plugins.extract._base: New parent class for all extract plugins

* plugins.extract.pipeline. Remove MultiProcessing. Dynamically limit batchsize for Nvidia cards. Remove loglevel input

* S3FD + FAN plugins. Standardise to Keras version for all backends

* Standardize all extract plugins to new threaded codebase

* Documentation. Start implementing Numpy style docstrings for Sphinx Documentation

* Remove s3fd_amd. Change convert OTF to expect DetectedFace object

* faces_detect - clean up and documentation

* Remove PoolProcess

* Migrate manual tool to new extract workflow

* Remove AMD specific extractor code from cli and plugins

* Sort tool to new extract workflow

* Remove multiprocessing from project

* Remove multiprocessing queues from QueueManager

* Remove multiprocessing support from logger

* Move face_filter to new extraction pipeline

* Alignments landmarksXY > landmarks_xy and legacy handling

* Intercept get_backend for sphinx doc build

# Add Sphinx documentation 
lib/utils.py