class_docstr: Internal class for `parallel_map`, arguments match the constructor's.
class_docstr_tok: ["Internal","class","for","`","parallel_map","`",",","arguments","match","the","constructor","'s","."]
docstr: Notifies the main thread of the finished job, bumping the number of
  jobs it should requeue. Updates the progress bar based on the returned
  chunk length.
  
  Arguments
  ---------
  future: concurrent.futures.Future
      A future holding a processed chunk (of type `list`).
docstr_tok: ["Notifies","the","main","thread","of","the","finished","job",",","bumping","the","number","of","jobs","it","should","requeue",".","Updates","the","progress","bar","based","on","the","returned","chunk","length",".","Arguments","--","--","--","--","-","future",":","concurrent.futures.Future","A","future","holding","a","processed","chunk","(","of","type","`","list","`",")","."]
code: def _bump_processed_count(self, future):
      """Notifies the main thread of the finished job, bumping the number of
      jobs it should requeue. Updates the progress bar based on the returned
      chunk length.
  
      Arguments
      ---------
      future: concurrent.futures.Future
          A future holding a processed chunk (of type `list`).
      """
      if future.cancelled():
          # the scheduler wants us to stop or something else happened, give up
          return
  
      future_exception = future.exception()
  
      # wake up dispatcher thread to refill the queue
      with self.cv:
          if future_exception is not None:
              # signal to the main thread that it should raise
              self.remote_exception = future_exception
  
          self.just_finished_count += 1
          self.cv.notify()
  
      if future_exception is None:
          # update progress bar with the length of the output as the progress
          # bar is over element count, not chunk count.
          if self.pbar is not None:
              self.pbar.update(len(future.result()))
  
file_path: speechbrain/speechbrain/utils/parallel.py
imports: import itertools
  import multiprocessing
  from collections import deque
  from concurrent.futures import Executor, ProcessPoolExecutor
  from threading import Condition
  from typing import Any, Callable, Iterable, Optional
  from tqdm.auto import tqdm
label_desc: Use image node_id 3 for calling the _ParallelMapper obj's underlying member method code with example usage: obj._bump_processed_count(future) without return types