I think this is not a big problem. gensim will simply tell you that they will be an alias for different functions because you use special os.
check gensim.utils code
if os.name == 'nt': logger.info("detected Windows; aliasing chunkize to chunkize_serial") def chunkize(corpus, chunksize, maxsize=0, as_numpy=False): for chunk in chunkize_serial(corpus, chunksize, as_numpy=as_numpy): yield chunk else: def chunkize(corpus, chunksize, maxsize=0, as_numpy=False): """ Split a stream of values into smaller chunks. Each chunk is of length `chunksize`, except the last one which may be smaller. A once-only input stream (`corpus` from a generator) is ok, chunking is done efficiently via itertools. If `maxsize > 1`, don't wait idly in between successive chunk `yields`, but rather keep filling a short queue (of size at most `maxsize`) with forthcoming chunks in advance. This is realized by starting a separate process, and is meant to reduce I/O delays, which can be significant when `corpus` comes from a slow medium (like harddisk). If `maxsize==0`, don't fool around with parallelism and simply yield the chunksize via `chunkize_serial()` (no I/O optimizations). >>> for chunk in chunkize(range(10), 4): print(chunk) [0, 1, 2, 3] [4, 5, 6, 7] [8, 9] """ assert chunksize > 0 if maxsize > 0: q = multiprocessing.Queue(maxsize=maxsize) worker = InputQueue(q, corpus, chunksize, maxsize=maxsize, as_numpy=as_numpy) worker.daemon = True worker.start() while True: chunk = [q.get(block=True)] if chunk[0] is None: break yield chunk.pop() else: for chunk in chunkize_serial(corpus, chunksize, as_numpy=as_numpy): yield chunk