code: def update(self, docs=None, split=0, lfs=None, parallelism=None, progress_bar=True):
          
          if lfs is None:
              raise ValueError("Please provide a list of lists of labeling functions.")
  
          if len(lfs) != len(self.candidate_classes):
              raise ValueError("Please provide LFs for each candidate class.")
  
          self.apply(
              docs=docs,
              split=split,
              lfs=lfs,
              train=True,
              clear=False,
              parallelism=parallelism,
              progress_bar=progress_bar,
          )
docs: Update the labels of the specified candidates based on the provided LFs.
  
          :param docs: If provided, apply the updated LFs to all the candidates
              in these documents.
          :param split: If docs is None, apply the updated LFs to the candidates
              in this particular split.
          :param lfs: A list of lists of labeling functions to update. Each list
              should correspond with the candidate_classes used to initialize the
              Labeler.
          :param parallelism: How many threads to use for extraction. This will
              override the parallelism value used to initialize the Labeler if
              it is provided.
          :type parallelism: int
          :param progress_bar: Whether or not to display a progress bar. The
              progress bar is measured per document.
          :type progress_bar: bool