Chunkize Warnung bei der Installation GENSIM

Question

Ich habe installiert GENSIM (durch pip) in Python. Nachdem die Installation über ich die folgende Warnung erhalten:

C: \ Python27 \ lib \ site-packages \ GENSIM \ utils.py: 855: UserWarning: erfasst Windows-; Aliasing chunkize warnings.warn chunkize_serial ("erkannt Windows-; Aliasing chunkize chunkize_serial")

Wie kann ich das beheben?

Ich bin zu importieren word2vec von gensim.models aufgrund dieser Warnung nicht in der Lage.

Ich habe die folgenden Konfigurationen: Python 2.7, Gensim-0.13.4.1, Numpy-1.11.3, Scipy-0.18.1, Muster-2.6.

Answer 1

Sie können die Nachricht mit diesem Code unterdrücken vor GENSIM importieren:

import warnings 
warnings.filterwarnings(action='ignore', category=UserWarning, module='gensim') 

import gensim 

Answer 2

ich denke, ist kein großes Problem. GENSIM nur Sie wissen lassen, dass sie Alias ​​andere Funktion chunkize führen, dass Sie bestimmte os verwenden.

Überprüfung der Code von gensim.utils

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