cHdZddlmZddlmZddlZddlZddlZddl Z ddl m Z ddl ZddlZddlZddlZddlZddlZddlZddlmZddlZddlZddlZddlZddlZddlZddlmZddlmZddl Z ddl!Z!ddl"Z#ddl$Z%dd l&m'Z'dd l(m)Z*ej+e,Z-d Z.ej/d ej0Z1ej/d ej0Z2e3dZ4 e#j5Z6dZ7dZ8dZ9edZ:dZ;dZd`dZ?dadZ@e@ZAdbdZBeBZCdZDGd d!ZEd"ZFd#ZGGd$d%ZHd&ZId'ZJd(ZKGd)d*eEZLGd+d,eEZMGd-d.eEZNGd/d0eEZOd1ZPd2ZQde#jRfd3ZSeSZTGd4d5ejUZVejWd6ksej d7krejXd8krdcd9ZYndcd:ZYd;ZZe.fd<Z d=Z[d>Z\d?Z]ed@Z^e]dAdddCZ_dedEZ`e]dAdfdGZadgdIZbdhdJZcdidMZddjdNZedkdOZfdkdPZgdQZhdRZidZjdSZkdZldkdTZmejnfdUZodldVZpdWZqdmdXZrdndYZsdZZtd[Zud\Zvd]Zwd^ZxdS)oz"Various general utility functions.)with_statement)contextmanagerN)name2codepointwraps)deepcopy)datetime)open) __version__z(((?![\d])\w)+)z&(#?)([xX]?)(\w{1,8});aCompiled extensions are unavailable. If you've installed from a package, ask the package maintainer to include compiled extensions. If you're building Gensim from source yourself, install Cython and a C compiler, and then run `python setup.py build_ext --inplace` to retry. c>||tjurtjjjSt |t jtjfrtj|St |tjjr|Std|z)aGenerate :class:`numpy.random.RandomState` based on input seed. Parameters ---------- seed : {None, int, array_like} Seed for random state. Returns ------- :class:`numpy.random.RandomState` Random state. Raises ------ AttributeError If seed is not {None, int, array_like}. Notes ----- Method originally from `maciejkula/glove-python `_ and written by `@joshloyal `_. Nz:%r cannot be used to seed a np.random.RandomState instance) nprandommtrand_rand isinstancenumbersIntegralinteger RandomState ValueError)seeds ,lib/python3.11/site-packages/gensim/utils.pyget_random_staterAs0 &try(&y%%$)2:677+y$$T***$ -.. QTXX Y YYcfd}|S)zA decorator to place an instance-based lock around a method. Notes ----- Adapted from http://code.activestate.com/recipes/577105-synchronization-decorator-for-class-methods/. c@tfd}|S)Nc>t|}tdj|5tdj|g|Ri|}tdj|cdddS#1swxYwYdS)Nzacquiring lock %r for %szacquired lock %r for %szreleasing lock %r for %s)getattrloggerdebug__name__)selfargskwargstlockresultfunc tlocknames r _synchronizerz4synchronous.._synched.._synchronizerksD),,E LL3Y N N N   6 4=QQQd4T444V44 7DMRRR                   sABBBr)r(r*r)s` r_synchedzsynchronous.._synchedjs: t       r)r)r+s` r synchronousr-bs#      Orczt|trt|dS|d|S)a4Open a filename for reading with `smart_open`, or seek to the beginning if `input` is an already open file. Parameters ---------- input : str or file-like Filename or file-like object. Returns ------- file-like object An open file, positioned at the beginning. rbr)rstrr seek)inputs rfile_or_filenamer3ys<%E4     1  rc#Kt|}d} |VnC#t$r6d}t|tr|jt jsYnwxYw|s.t|tr|ddddSdSdS#|s-t|tr|dddwwwxYw)aProvide "with-like" behaviour without closing the file object. Parameters ---------- input : str or file-like Filename or file-like object. Yields ------- file File-like object based on input (or input if this already file-like). FTN)r3 Exceptionrr0__exit__sysexc_info)r2mgrexcs r open_filer;s  5 ! !C C + %%% \S\3<>>-J     +z%-- + LLtT * * * * * + + + +s +z%-- + LLtT * * * * + +s&B=ABAB2Cct|ts|d}tjd|}dd|D}tjd|S)uRemove letter accents from the given string. Parameters ---------- text : str Input string. Returns ------- str Unicode string without accents. Examples -------- .. sourcecode:: pycon >>> from gensim.utils import deaccent >>> deaccent("Šéf chomutovských komunistů dostal poštou bílý prášek") u'Sef chomutovskych komunistu dostal postou bily prasek' utf8NFDc3JK|]}tj|dk|VdS)MnN) unicodedatacategory).0chs r zdeaccent..s7KKB+*>r*B*Bd*JKRKKKKKKrNFC)rr0decoderB normalizejoin)textnormr's rdeaccentrMsl, dC #{{6""   - -D WWKK$KKK K KF   / //rctj} tjt_tj|||t_dS#|t_wxYw)a$Recursively copy a directory ala shutils.copytree, but hardlink files instead of copying. Parameters ---------- source : str Path to source directory dest : str Path to destination directory Warnings -------- Available on UNIX systems only. N)shutilcopy2oslinkcopytree)sourcedestrPs rcopytree_hardlinkrVsI LEw %%% u s +AAFr=strictc|p|p|}t|||}|r|}|rt|}t|S)uIteratively yield tokens as unicode strings, optionally removing accent marks and lowercasing it. Parameters ---------- text : str or bytes Input string. deacc : bool, optional Remove accentuation using :func:`~gensim.utils.deaccent`? encoding : str, optional Encoding of input string, used as parameter for :func:`~gensim.utils.to_unicode`. errors : str, optional Error handling behaviour, used as parameter for :func:`~gensim.utils.to_unicode`. lowercase : bool, optional Lowercase the input string? to_lower : bool, optional Same as `lowercase`. Convenience alias. lower : bool, optional Same as `lowercase`. Convenience alias. Yields ------ str Contiguous sequences of alphabetic characters (no digits!), using :func:`~gensim.utils.simple_tokenize` Examples -------- .. sourcecode:: pycon >>> from gensim.utils import tokenize >>> list(tokenize('Nic nemůže letět rychlostí vyšší, než 300 tisíc kilometrů za sekundu!', deacc=True)) [u'Nic', u'nemuze', u'letet', u'rychlosti', u'vyssi', u'nez', u'tisic', u'kilometru', u'za', u'sekundu'] errors) to_unicodelowerrMsimple_tokenize)rK lowercasedeaccencodingrZto_lowerr\s rtokenizerbs^D.X.I dHV 4 4 4Dzz|| ~~ 4  rc#pKt|D]}|VdS)zTokenize input test using :const:`gensim.utils.PAT_ALPHABETIC`. Parameters ---------- text : str Input text. Yields ------ str Tokens from `text`. N)PAT_ALPHABETICfinditergroup)rKmatchs rr]r]sF ((..kkmmrcJfdt|d|dD}|S)aqConvert a document into a list of lowercase tokens, ignoring tokens that are too short or too long. Uses :func:`~gensim.utils.tokenize` internally. Parameters ---------- doc : str Input document. deacc : bool, optional Remove accent marks from tokens using :func:`~gensim.utils.deaccent`? min_len : int, optional Minimum length of token (inclusive). Shorter tokens are discarded. max_len : int, optional Maximum length of token in result (inclusive). Longer tokens are discarded. Returns ------- list of str Tokens extracted from `doc`. cxg|]6}t|cxkrknn|d4|7S)_)len startswith)rDtokenmax_lenmin_lens r z%simple_preprocess..6sx c%jj$+494D4DS4I4I rTignore)r\r_rZ)rb)docr_rqrptokenss `` rsimple_preprocessrv sI,#Ct5RRRF Mrct|tr|dSt|||dS)azConvert a unicode or bytes string in the given encoding into a utf8 bytestring. Parameters ---------- text : str Input text. errors : str, optional Error handling behaviour if `text` is a bytestring. encoding : str, optional Encoding of `text` if it is a bytestring. Returns ------- str Bytestring in utf8. r=rY)rr0encode)rKrZr`s rany2utf8ry=sK&$#{{6""" tXf - - - 4 4V < <;RT^ _ _ _   5  ! ( ( 4 4 4 4 4 5 5rNctd|j|t|\}}t |}||||||d||S)aaLoad an object previously saved using :meth:`~gensim.utils.SaveLoad.save` from a file. Parameters ---------- fname : str Path to file that contains needed object. mmap : str, optional Memory-map option. If the object was saved with large arrays stored separately, you can load these arrays via mmap (shared memory) using `mmap='r'. If the file being loaded is compressed (either '.gz' or '.bz2'), then `mmap=None` **must be** set. See Also -------- :meth:`~gensim.utils.SaveLoad.save` Save object to file. Returns ------- object Object loaded from `fname`. Raises ------ AttributeError When called on an object instance instead of class (this is a class method). zloading %s object from %sloaded)fname)r infor"r_adapt_by_suffixunpickle_load_specialsr)clsrmmapcompresssubnameobjs rloadz SaveLoad.loadsx:  /uEEE$55e<<'uoo 5$'::: 666 rc d}t|dgD]}d||f}td|||t 5t||||||dddn #1swxYwYt|dgD]}td||||||r=|r|||||t j|||d}n t j|||| }t 5t|||dddn #1swxYwYt|d gD]e}td|||||t|||} |rw|r|||||t j|||d 5} | d | _ | d | _ | d| _ dddn #1swxYwYnrt j|||d | | _ t j|||d | | _ t j|||d| | _ t 5t||| dddn #1swxYwYgt|dgD]T}td|t 5t||ddddn #1swxYwYUdS)uzLoad attributes that were stored separately, and give them the same opportunity to recursively load using the :class:`~gensim.utils.SaveLoad` interface. Parameters ---------- fname : str Input file path. mmap : {None, ‘r+’, ‘r’, ‘w+’, ‘c’} Memory-map options. See `numpy.load(mmap_mode) `_. compress : bool Is the input file compressed? subname : str Attribute name. Set automatically during recursive processing. c4td|d|ddzS)NzCannot mmap compressed object z in file z. z:Use `load(fname, mmap=None)` or uncompress files manually.)IOError)rfilenames r mmap_errorz+SaveLoad._load_specials..mmap_errors/7CF33QNO r__recursive_saveloads.z-loading %s recursively from %s.* with mmap=%sN__numpyszloading %s from %s with mmap=%sval) mmap_mode__scipyssparsedataindptrindices __ignoredsz$setting ignored attribute %s to None) rrJr rignore_deprecation_warningrrrsetattrrrrr) r#rrrrrattribcfnamerrfs rrzSaveLoad._load_specialss"    d$;R@@ V VFXXufo..F KKGQWY] ^ ^ ^+-- V Vf%%44VT8WUUU V V V V V V V V V V V V V V VdJ33 + +F KK96775RXCYCY[_ ` ` ` FE$*VWWUF-C-CDDDgggeV4455e<gggeV44EEE+-- + +fc*** + + + + + + + + + + + + + + +dJ33 . .F KK96775RXCYCY[_ ` ` `ggeV4455F \E$*VWWUF-C-CDDDWWWUFH==>>2!"#F)FK$%hKFM%&y\FN222222222222222 !gggeVV&D&DPTUUU "vx(H(HTX Y Y Y !# )J)JVZ![![![+-- . .ff--- . . . . . . . . . . . . . . .dL"55 , ,F KK> G G G+-- , ,fd+++ , , , , , , , , , , , , , , , , ,sZ'B  B B ?EE! $E! 6(H**H. 1H. 6KK K L;;L? L? ct|ds|drdnd\}|fdfS)aGet compress setting and filename for numpy file compression. Parameters ---------- fname : str Input filename. Returns ------- (bool, function) First argument will be True if `fname` compressed. .gz.bz2)Tnpz)Fnpyc6d|fzS)Nr)rJ)r$suffixs rz+SaveLoad._adapt_by_suffix..>ssxxy0@'A'Ar)endswith)rrrs @rrzSaveLoad._adapt_by_suffix.sL-2NN5,A,AoU^^TZE[E[o==ao&AAAAAAric Bt|\}}||||||||} t||||D]V\} } | D]<\} } t 5t | | | dddn #1swxYwY=Wn^#|D]V\} } | D]<\} } t 5t | | | dddn #1swxYwY=WwxYwtd|dS)aSave the object to a file. Used internally by :meth:`gensim.utils.SaveLoad.save()`. Parameters ---------- fname : str Path to file. separately : list, optional Iterable of attributes than need to store distinctly. sep_limit : int, optional Limit for separation. ignore : frozenset, optional Attributes that shouldn't be store. pickle_protocol : int, optional Protocol number for pickle. Notes ----- If `separately` is None, automatically detect large numpy/scipy.sparse arrays in the object being stored, and store them into separate files. This avoids pickle memory errors and allows mmap'ing large arrays back on load efficiently. You can also set `separately` manually, in which case it must be a list of attribute names to be stored in separate files. The automatic check is not performed in this case. protocolNzsaved %s) rr_save_specialspickleitemsrrr r) r#r separately sep_limitrspickle_protocolrrrestoresrasidesrrs r _smart_savezSaveLoad._smart_save@s:%55e<<'&& :y&/8W   2 4 9 9 9 9 ( 2 2 V#)<<>>22KFC35522VS1112222222222222222 2x 2 2 V#)<<>>22KFC35522VS1112222222222222222 2  J&&&&&sAB&:BB B &/DC3 ' D3C77D:C7;Dc x i}tjjtjjf} |g}|jD]p\} } t | tjr!| j |kr| | @t | | r | j |kr| | qt5|t|zD]5} t|| r#t|| || <t!|| 6 dddn #1swxYwYg} g} |jD]o\} } t| drZ| | d|| f}| | |d|||||p ggg}}}|D]\} } t | tjr| |vr| | t(d| ||| |r3tj||| tj| tj||| tj| t | tjjtjjfr^| |vrY| | t(d| ||| |r3tj||| d| j| j| jnotj||| d | jtj||| d | jtj||| d | j| j| j| j}}}d \| _| _| _ t9| ||| | |||c| _| _| _:#|||c| _| _| _wxYwt(d| | | ||jd<||jd<||jd<| |jd<n:#t:$r-|D]\} } t=|| | wxYw| ||fgzS)aSave aside any attributes that need to be handled separately, including by recursion any attributes that are themselves :class:`~gensim.utils.SaveLoad` instances. Parameters ---------- fname : str Output filename. separately : list or None List of attributes to store separately. sep_limit : int Don't store arrays smaller than this separately. In bytes. ignore : iterable of str Attributes that shouldn't be stored at all. pickle_protocol : int Protocol number for pickle. compress : bool If True - compress output with :func:`numpy.savez_compressed`. subname : function Produced by :meth:`~gensim.utils.SaveLoad._adapt_by_suffix` Returns ------- list of (obj, {attrib: value, ...}) Settings that the caller should use to restore each object's attributes that were set aside during the default :func:`~gensim.utils.pickle`. Nrrzstoring np array '%s' to %s)rz(storing scipy.sparse array '%s' under %sr)rrrrrr)NNNrznot storing attribute %srrrr)scipyr csr_matrix csc_matrix__dict__rrrndarraysizernnzrlistrrdelattrrJextendrr rsavez_compressedascontiguousarraysaverrrrr5r)r#rrrrsrrrrsparse_matricesrrrecursive_saveloadsrrnumpysscipysignoredsrrrs rrzSaveLoad._save_specialslsS8 <2EL4KL  .J#}2244 . . c2:...38y3H.%%f----_55.#'Y:N.%%f--- ' ) ) * *$tF||3 * *4((*%,T6%:%:F6ND&))) * * * * * * * * * * * * * * * *!=..00 y yKFCs,-- y#**62225&/22 2 264FTcemov w wxxx0 ')2rHFF%||~~$ ,$ , c2:..#,63G#,MM&)))KK =vwwuV\G]G]^^^S+GGE6,B,BH\]`HaHabbbbbv 6 68LS8Q8QRRRRel&=u|?V%WXX,]ckq]q,MM&)))KK JFT[T[\aciTjTjkkk P+#GE68< >IIIvx @ @#*MMMvy A A3;OOO,/Hcj#+'&D8H5CHcj#+RsGGE6$:$:_UUUU<@&'9#*ckkD&'9#*ckQQQQKK :FCCCOOF++++(.DM* %(.DM* %*2DM, '5HDM1 2 2   %||~~ + + fc****    D&>***s9A DDD0HQ:P,Q:PAQ::7R1c>|dt|t||| tj|||td|jjdS#t$r| |||||YdSwxYw)aSave the object to a file. Parameters ---------- fname_or_handle : str or file-like Path to output file or already opened file-like object. If the object is a file handle, no special array handling will be performed, all attributes will be saved to the same file. separately : list of str or None, optional If None, automatically detect large numpy/scipy.sparse arrays in the object being stored, and store them into separate files. This prevent memory errors for large objects, and also allows `memory-mapping `_ the large arrays for efficient loading and sharing the large arrays in RAM between multiple processes. If list of str: store these attributes into separate files. The automated size check is not performed in this case. sep_limit : int, optional Don't store arrays smaller than this separately. In bytes. ignore : frozenset of str, optional Attributes that shouldn't be stored at all. pickle_protocol : int, optional Protocol number for pickle. See Also -------- :meth:`~gensim.utils.SaveLoad.load` Load object from file. saving)fname_or_handlerrrsrzsaved %s object)rN) rr0_pickledumpr rrr" TypeErrorr)r#rrrrsrs rrz SaveLoad.saves@   00: !    n L I I I I KK)4>+B C C C C C n n n   _j)V]l  m m m m m m ns.(s&"F"Fzw7"F"F"F"F"F"Fr)max)corpusmaxiddocuments r get_max_idrsO$ EHH  Hs"F"FX"F"F"FFFGGE LrcDeZdZdZdZdZdZdZdZdZ dZ d d Z d S) FakeDictzObjects of this class act as dictionaries that map integer->str(integer), for a specified range of integers <0, num_terms). This is meant to avoid allocating real dictionaries when `num_terms` is huge, which is a waste of memory. c||_dS)zf Parameters ---------- num_terms : int Number of terms. N num_terms)r#rs r__init__zFakeDict.__init__3s#rc0|jjd|jdS)Nz )rr"rr#s r__str__zFakeDict.__str__>s%)^%<%<% `str(word_id)`. Parameters ---------- corpus : iterable of iterable of (int, numeric) Collection of texts in BoW format. Returns ------ id2word : :class:`~gensim.utils.FakeDict` "Fake" mapping which maps each `word_id` -> `str(word_id)`. Warnings -------- This function is used whenever *words* need to be displayed (as opposed to just their ids) but no `word_id` -> `word` mapping was provided. The resulting mapping only covers words actually used in the corpus, up to the highest `word_id` found. r)rr)rrid2words rdict_from_corpusros(*Jv&&&Iy!!G Nrc d|jjvrd|fSn#t$rYnwxYw t|dst|dr&t |}t j|g|}nt t|}t|dkrd|fSt t|\}}t|t|}}n#t$rd|fcYSwxYwd|fS)aSCheck whether `obj` is a corpus, by peeking at its first element. Works even on streamed generators. The peeked element is put back into a object returned by this function, so always use that returned object instead of the original `obj`. Parameters ---------- obj : object An `iterable of iterable` that contains (int, numeric). Returns ------- (bool, object) Pair of (is `obj` a corpus, `obj` with peeked element restored) Examples -------- .. sourcecode:: pycon >>> from gensim.utils import is_corpus >>> corpus = [[(1, 1.0)], [(2, -0.3), (3, 0.12)]] >>> corpus_or_not, corpus = is_corpus(corpus) Warnings -------- An "empty" corpus (empty input sequence) is ambiguous, so in this case the result is forcefully defined as (False, `obj`). CorpusTnext__next__rF) rr"r5rr itertoolschainiterrmintfloat)rdoc1id1val1s r is_corpusr$s$: s}- - 9         3   #73 #;#; #99D/4&#..CCS ??D t99> 9 d$$ THHeDkkT cz 9s$ ""A8C=CC.-C.cddl} ddlm}|}||j|j}||jj|jjf| \}}n#t$r ddl }| d dd ddd}t| dd krtn7#t$r*||}YnwxYwYnwxYw|S) a}Try to obtain our external ip (from the Pyro4 nameserver's point of view) Returns ------- str IP address. Warnings -------- This tries to sidestep the issue of bogus `/etc/hosts` entries and other local misconfiguration, which often mess up hostname resolution. If all else fails, fall back to simple `socket.gethostbyname()` lookup. rN)locateNSifconfig rrr )socket Pyro4.namingr&AF_INET SOCK_DGRAMconnect_pyroUrihostport getsocknamer5commands getoutputsplitrm gethostbyname gethostname)r*r&nssr'r1r3s r get_my_ipr:seMMM@)))))) XZZ MM&.&*; < < 2;#R[%56777}}   @ @ @ @ OOO'' 3399$??BHHJJ1MabbQF6<<$$%%* "kk! " @ @ @))&*<*<*>*>??FFF @ @ Ms7A2A99 EBD  E 1D?<E>D??EEceZdZdZdZdZdS) RepeatCorpusa,Wrap a `corpus` as another corpus of length `reps`. This is achieved by repeating documents from `corpus` over and over again, until the requested length `len(result) == reps` is reached. Repetition is done on-the-fly=efficiently, via `itertools`. Examples -------- .. sourcecode:: pycon >>> from gensim.utils import RepeatCorpus >>> >>> corpus = [[(1, 2)], []] # 2 documents >>> list(RepeatCorpus(corpus, 5)) # repeat 2.5 times to get 5 documents [[(1, 2)], [], [(1, 2)], [], [(1, 2)]] c"||_||_dS)z Parameters ---------- corpus : iterable of iterable of (int, numeric) Input corpus. reps : int Number of repeats for documents from corpus. N)rreps)r#rr>s rrzRepeatCorpus.__init__s  rcdtjtj|j|jSr)rislicecyclerr>rs r__iter__zRepeatCorpus.__iter__s#  < >> from gensim.utils import RepeatCorpusNTimes >>> >>> corpus = [[(1, 0.5)], []] >>> list(RepeatCorpusNTimes(corpus, 3)) # repeat 3 times [[(1, 0.5)], [], [(1, 0.5)], [], [(1, 0.5)], []] c"||_||_dS)z Parameters ---------- corpus : iterable of iterable of (int, numeric) Input corpus. n : int Number of repeats for corpus. N)rn)r#rrGs rrzRepeatCorpusNTimes.__init__s rc#TKt|jD]}|jD]}|VdSr)r rGr)r#rlrs rrBzRepeatCorpusNTimes.__iter__!sHtv  A K     rNrCr,rrrErEs<     rrEc&eZdZdZddZdZdZdS) ClippedCorpusz5Wrap a `corpus` and return `max_doc` element from it.Nc"||_||_dS)a Parameters ---------- corpus : iterable of iterable of (int, numeric) Input corpus. max_docs : int Maximum number of documents in the wrapped corpus. Warnings -------- Any documents after `max_docs` are ignored. This effectively limits the length of the returned corpus to <= `max_docs`. Set `max_docs=None` for "no limit", effectively wrapping the entire input corpus. N)rmax_docs)r#rrLs rrzClippedCorpus.__init__)s    rc@tj|j|jSr)rr@rrLrs rrBzClippedCorpus.__iter__<s T];;;rcPt|jt|jSr)minrLrmrrs rrzClippedCorpus.__len__?s4=#dk"2"2333rrr"rrrrrBrr,rrrJrJ'sL??!!!!&<<<44444rrJc$eZdZdZdZdZdZdS) SlicedCorpusz'Wrap `corpus` and return a slice of it.c0||_||_d|_dS)an Parameters ---------- corpus : iterable of iterable of (int, numeric) Input corpus. slice_ : slice or iterable Slice for `corpus`. Notes ----- Negative slicing can only be used if the corpus is indexable, otherwise, the corpus will be iterated over. Slice can also be a np.ndarray to support fancy indexing. Calculating the size of a SlicedCorpus is expensive when using a slice as the corpus has to be iterated over once. Using a list or np.ndarray does not have this drawback, but consumes more memory. N)rslice_length)r#rrTs rrzSlicedCorpus.__init__Es&   rc"tjdr@tjjdkr#fdjjjDSt jjjjjjjj S)Nindexrc3LK|]}j|VdSr)r docbyoffset)rDr r#s rrFz(SlicedCorpus.__iter__..^s3WW1DK++A..WWWWWWr) rrrmrWrTrr@startstopsteprs`rrBzSlicedCorpus.__iter__\s 4; ( ( XS1B-C-Ca-G XWWWW 8I$+8VWWW W T[-> @PRVR]Rbcccrc|jt|jttjfrt |j|_nt|jtrO|jt |j j \}}}||z }||z||zdkz|_ntd|D|_|jS)Nrc3K|]}dVdS)rNr,)rDxs rrFz'SlicedCorpus.__len__..ks"!2!2!!2!2!2!2!2!2r) rUrrTrrrrmslicerrrWsum)r#rZendr\diffs rrzSlicedCorpus.__len__as ; 3$+bj'9:: 3!$+.. DK// 3%)[%8%8T[=N9O9O%P%P"TU{"dldTkAo> !!2!2T!2!2!222 {rNrPr,rrrRrRCsJ11.ddd     rrRcv t|S#t$rd|z}|dcYSwxYw)a:Create a unicode character from its integer value. In case `unichr` fails, render the character as an escaped `\U<8-byte hex value of intval>` string. Parameters ---------- intval : int Integer code of character Returns ------- string Unicode string of character z\U%08xzunicode-escape)chrrrH)intvalr9s r safe_unichrrgpsQ*6{{ ***  xx())))) *s $88c>d}t||S)uDecode all HTML entities in text that are encoded as hex, decimal or named entities. Adapted from `python-twitter-ircbot/html_decode.py `_. Parameters ---------- text : str Input HTML. Examples -------- .. sourcecode:: pycon >>> from gensim.utils import decode_htmlentities >>> >>> u = u'E tu vivrai nel terrore - L'aldilà (1981)' >>> print(decode_htmlentities(u).encode('UTF-8')) E tu vivrai nel terrore - L'aldilà (1981) >>> print(decode_htmlentities("l'eau")) l'eau >>> print(decode_htmlentities("foo < bar")) foo < bar c |d}|ddkrk|ddkrtt|S|ddvrtt|dSdStj|}|rt|S|S#t $r|cYSwxYw)Nr#rhr?)r_X)rfrgrn2cprr5)rgentcps rsubstitute_entityz.decode_htmlentities..substitute_entitys !++a..C{{1~~$ );;q>>R'5&s3xx000[[^^z15&s3||44455 Xc]])&r??* ;;==( ! ! !;;==  !s$A"C%3C$CCC54C5)RE_HTML_ENTITYsub)rKrqs rdecode_htmlentitiesrts*2!!!,   / 6 66rc#.Kt|} |r0fdtj|t|Dg}n0t tj|t|g}|dsdS|V)aYield elements from `iterable` in "chunksize"-ed groups. The last returned element may be smaller if the length of collection is not divisible by `chunksize`. Parameters ---------- iterable : iterable of object An iterable. chunksize : int Split iterable into chunks of this size. as_numpy : bool, optional Yield chunks as `np.ndarray` instead of lists. Yields ------ list OR np.ndarray "chunksize"-ed chunks of elements from `iterable`. Examples -------- .. sourcecode:: pycon >>> print(list(grouper(range(10), 3))) [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] Tc<g|]}tj|S))dtype)rarray)rDrtrws rrrz#chunkize_serial..s(iiiSbhs%888iiirrN)rrr@rrpop)iterable chunksizeas_numpyrwit wrapped_chunks ` rchunkize_serialrs6 hB "  IjiiiIDTUWY\]fYgYgDhDhiiijMM!)"22s9~~"F"FGGHMQ  E!!!!! "rc(eZdZdZfdZdZxZS) InputQueuezPopulate a queue of input chunks from a streamed corpus. Useful for reading and chunking corpora in the background, in a separate process, so that workers that use the queue are not starved for input chunks. ctt|||_||_||_||_||_dS)a Parameters ---------- q : multiprocessing.Queue Enqueue chunks into this queue. corpus : iterable of iterable of (int, numeric) Corpus to read and split into "chunksize"-ed groups chunksize : int Split `corpus` into chunks of this size. as_numpy : bool, optional Enqueue chunks as `numpy.ndarray` instead of lists. N)superrrqmaxsizerr{r|)r#rrr{rr|rs rrzInputQueue.__init__sH j$((***  "  rc t|j} tj||j}|jrd|Dg}nt |g}|ds|jdddS |j }n#t$rd}YnwxYwt dt|d||j|d)NTc6g|]}tj|Sr,)rasarray)rDrts rrrz"InputQueue.run.. s !C!C!Cc"*S//!C!C!Crrblock?z1prepared another chunk of %i documents (qsize=%s))rrrr@r{r|rrputqsizeNotImplementedErrorr r!rmry)r#r}chunkr~rs rrunzInputQueue.runs $+   8$R88E} ."D!CU!C!C!C D !%e  #  4t ,,,  &     LLLcR_`aRbNcNcej k k k FJJ}((**$J 7 7 7' 8s<B B%$B%)r"rrrrr __classcell__)rs@rrrsQ !!!!!*8888888rrntdarwin)rjc#K|dkr+tjdkrdnd}tjd|zt |||D]}|VdS)a<Split `corpus` into fixed-sized chunks, using :func:`~gensim.utils.chunkize_serial`. Parameters ---------- corpus : iterable of object An iterable. chunksize : int Split `corpus` into chunks of this size. maxsize : int, optional Ignored. For interface compatibility only. as_numpy : bool, optional Yield chunks as `np.ndarray` s instead of lists? Yields ------ list OR np.ndarray "chunksize"-ed chunks of elements from `corpus`. rrWindowszOSX with python3.8+z1detected %s; aliasing chunkize to chunkize_serialr|N)rQnamewarningswarnr)rr{rr|entityrs rchunkizerst( Q; X"$'T/LYY7LF MMPVV W W W$VYJJJ  EKKKK  rc#RK|dksJ|dkr}tj|}t|||||}d|_| |dg}|ddS|V8t|||D]}|VdS)aSplit `corpus` into fixed-sized chunks, using :func:`~gensim.utils.chunkize_serial`. Parameters ---------- corpus : iterable of object An iterable. chunksize : int Split `corpus` into chunks of this size. maxsize : int, optional If > 0, prepare chunks in a background process, filling a chunk queue of size at most `maxsize`. as_numpy : bool, optional Yield chunks as `np.ndarray` instead of lists? Yields ------ list OR np.ndarray "chunksize"-ed chunks of elements from `corpus`. Notes ----- 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 > 0`, 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 HDD, database or network. If `maxsize == 0`, don't fool around with parallelism and simply yield the chunksize via :func:`~gensim.utils.chunkize_serial` (no I/O optimizations). Yields ------ list of object OR np.ndarray Groups based on `iterable` r)r)rr|TrNr)multiprocessingQueuerdaemonrZrryr)rr{rr|rworkerrs rrr9sL1} Q; %g666A69gPXYYYF FM LLNNN "T**+8Eiikk!!!  " )XNNN     rctj|\}}|dr||ddz|zdz}n1|dr||ddz|zdz}n||z|z}|S)a2Append a file extension `ext` to `fname`, while keeping compressed extensions like `.bz2` or `.gz` (if any) at the end. Parameters ---------- fname : str Filename or full path. ext : str Extension to append before any compression extensions. Returns ------- str New path to file with `ext` appended. Examples -------- .. sourcecode:: pycon >>> from gensim.utils import smart_extension >>> smart_extension("my_file.pkl.gz", ".vectors") 'my_file.pkl.vectors.gz' rNr)rQpathsplitextr)rextoexts rsmart_extensionrps4'""5))KE4 }}V#SbS !C'&0 u  #SbS !C'%/ s" Lrct|d5}tj|||ddddS#1swxYwYdS)a$Pickle object `obj` to file `fname`, using smart_open so that `fname` can be on S3, HDFS, compressed etc. Parameters ---------- obj : object Any python object. fname : str Path to pickle file. protocol : int, optional Pickle protocol number. wbrN)r rr)rrrfouts rrrs eT  3d S$2222333333333333333333s 6::ct|d5}tj|dcdddS#1swxYwYdS)zLoad object from `fname`, using smart_open so that `fname` can be on S3, HDFS, compressed etc. Parameters ---------- fname : str Path to pickle file. Returns ------- object Python object loaded from `fname`. r/latin1)r`N)r rr)rrs rrrs eT  2a|A111222222222222222222s 488cXdt|DS)aReverse a dictionary mapping, i.e. `{1: 2, 3: 4}` -> `{2: 1, 4: 3}`. Parameters ---------- d : dict Input dictionary. Returns ------- dict Reversed dictionary mapping. Notes ----- When two keys map to the same value, only one of them will be kept in the result (which one is kept is arbitrary). Examples -------- .. sourcecode:: pycon >>> from gensim.utils import revdict >>> d = {1: 2, 3: 4} >>> revdict(d) {2: 1, 4: 3} ci|]\}}|| Sr,r,)rDkvs r zrevdict..s / / /VaAq / / /r)dictr)ds rrevdictrs&6 0 /tAww}} / / //rc$ttrfd}|Stjstjr!dt fd}|St tt)a^Decorator to mark functions as deprecated. Calling a decorated function will result in a warning being emitted, using warnings.warn. Adapted from https://stackoverflow.com/a/40301488/8001386. Parameters ---------- reason : str Reason of deprecation. Returns ------- function Decorated function cHdtfd}|S)Nz'Call to deprecated `{name}` ({reason}).ctjjtd|i|S)N)rreasonrhrC stacklevelrrformatr"DeprecationWarning)r$r%fmtr(rs r new_func1z0deprecated..decorator..new_func1sN JJDM&JAA/  tT,V,,,rr)r(rrrs` @r decoratorzdeprecated..decoratorsE;C 4[[ - - - - - -[ - rzCall to deprecated `{name}`.c~tjjtd|i|S)N)rrhrr)r$r%rr(s r new_func2zdeprecated..new_func2sL M  ..+     4((( (r) rr0inspectisclass isfunctionrrreprtype)rrrrr(s` @@r deprecatedrs"&#,       ,G$6v$>$>,, t ) ) ) ) )  )T&\\**+++rc#Ktj5tjdtdVddddS#1swxYwYdS)z/Contextmanager for ignoring DeprecationWarning.rs)rCN)rcatch_warningsfilterwarningsrr,rrrr s  " "3EFFFF s AA Az!Function will be removed in 4.0.0 c~||}tt|d}fd|d|DS)amDebug fnc to help inspect the top `n` most similar documents (according to a similarity index `index`), to see if they are actually related to the query. Parameters ---------- query : {list of (int, number), numpy.ndarray} vector OR BoW (list of tuples) texts : str object that can return something insightful for each document via `texts[docid]`, such as its fulltext or snippet. index : any A instance from from :mod:`gensim.similarity.docsim`. Return ------ list a list of 3-tuples (docid, doc's similarity to the query, texts[docid]) c|d S)Nrr,)items rrztoptexts..'s T!WHr)keyc,g|]\}}|||fSr,r,)rDtopid topcosinetextss rrrztoptexts..)s) N N N1A UIuU| , N N NrN)sorted enumerate)queryrrWrGsimss ` rtoptextsrsL* !X..//3H 7<<+--v/@ A AArc.d}t||D]}|t|z}td||dz |5g}|D].}||d|d<|d=||/|}|||}dS)aOMemory-friendly upload of documents to a SimServer (or Pyro SimServer proxy). Notes ----- Use this function to train or index large collections.abc -- avoid sending the entire corpus over the wire as a single Pyro in-memory object. The documents will be sent in smaller chunks, of `chunksize` documents each. rzuploading documents %i-%irNrKru)grouperrmr rrbuffer) serverdocsr{ preprocessrZrrbpchunkrts rupload_chunkedr>s Ey))  c%jj  /a@@@  F # # * 3v; 7 7H K c""""E e  rTcddl} |||||S#|jj$rt dwxYw)aGet a Pyro4 name server proxy. Parameters ---------- host : str, optional Name server hostname. port : int, optional Name server port. broadcast : bool, optional Use broadcast mechanism? (i.e. reach out to all Pyro nodes in the network) hmac_key : str, optional Private key. Raises ------ RuntimeError When Pyro name server is not found. Returns ------- :class:`Pyro4.core.Proxy` Proxy from Pyro4. rNzPyro name server not found)Pyro4r&rZ NamingError RuntimeError)r0r1 broadcasthmac_keyrs rgetNSrXsY2LLL9~~dD)X>>> < #99978889s=c"|i}|r0|dttjddddzz }ddl}t di|5}||p t |pd5}|||} ||||| t d|| | dddn #1swxYwYddddS#1swxYwYdS)zRegister an object with the Pyro name server. Start the name server if not running yet and block until the daemon is terminated. The object is registered under `name`, or `name`+ some random suffix if `random_suffix` is set. Nrrrrhz(%s registered with nameserver (URI '%s')r,) rrrrrDaemonr:registerremover r requestLoop) rr random_suffixipr1ns_confrr8ruris r pyro_daemonrxs; c&.H5566qrr:::LLL     !R \\"+ TYQ 7 7 !6//#t,,C IIdOOO KKc " " " KKBD# N N N     ! ! ! ! ! ! ! ! ! ! ! ! ! ! !!!!!!!!!!!!!!!!!!!s7'D.A2C, D,C0 0D3C0 4DD D??ctj|ffdt|DS)aCreate a random gensim BoW vector, with the feature counts following the Poisson distribution. Parameters ---------- dim : int, optional Dimension of vector. prob_nnz : float, optional Probability of each coordinate will be nonzero, will be drawn from the Poisson distribution. lam : float, optional Lambda parameter for the Poisson distribution. Returns ------- list of (int, float) Vector in BoW format. )rcg|]@}|k|ttjdzfAS))lamr)r rrpoisson)rDr rrprob_nnzs rrrz!mock_data_row..sP b b bQPSTUPVYaPa bQbi''C'003677 8 b b br)rruniformr )dimrrrs ``@r mock_data_rowrsG$ )  #  ( (C b b b b b b%** b b bbrcBfdt|DS)a}Create a random Gensim-style corpus (BoW), using :func:`~gensim.utils.mock_data_row`. Parameters ---------- n_items : int Size of corpus dim : int Dimension of vector, used for :func:`~gensim.utils.mock_data_row`. prob_nnz : float, optional Probability of each coordinate will be nonzero, will be drawn from Poisson distribution, used for :func:`~gensim.utils.mock_data_row`. lam : float, optional Parameter for Poisson distribution, used for :func:`~gensim.utils.mock_data_row`. Returns ------- list of list of (int, float) Gensim-style corpus. c4g|]}tS))rrr)r)rDrlrrrs rrrzmock_data..s( W W W1McH# > > > W W Wr)r )n_itemsrrrs ```r mock_datar s.* X W W W W Wg W W WWrc d}t|}t|D](}t|||||s|||z }||=)td|t|z ||t||S)aRemove all entries from the `vocab` dictionary with count smaller than `min_reduce`. Modifies `vocab` in place, returns the sum of all counts that were pruned. Parameters ---------- vocab : dict Input dictionary. min_reduce : int Frequency threshold for tokens in `vocab`. trim_rule : function, optional Function for trimming entities from vocab, default behaviour is `vocab[w] <= min_reduce`. Returns ------- result : int Sum of all counts that were pruned. rz:pruned out %i tokens with count <=%i (before %i, after %i))rmrkeep_vocab_itemr r)vocab min_reduce trim_ruler'old_lenws r prune_vocabrs(F%jjG %[[q%(J BB  eAh Fa KKD#e**j'3u:: Mrc|t|krdStj||d}t |||dS)aRetain `topk` most frequent words in `vocab`. If there are more words with the same frequency as `topk`-th one, they will be kept. Modifies `vocab` in place, returns nothing. Parameters ---------- vocab : dict Input dictionary. topk : int Number of words with highest frequencies to keep. trim_rule : function, optional Function for trimming entities from vocab, default behaviour is `vocab[w] <= min_count`. Nr)r)rmheapqnlargestvaluesr)rtopkr min_counts rtrim_vocab_by_freqrsU s5zztU\\^^44R8IyI666666rcn|D]\}}||vr||xx|z cc<|||< |S)a]Merge `dict1` of (word, freq1) and `dict2` of (word, freq2) into `dict1` of (word, freq1+freq2). Parameters ---------- dict1 : dict of (str, int) First dictionary. dict2 : dict of (str, int) Second dictionary. Returns ------- result : dict Merged dictionary with sum of frequencies as values. )r)dict1dict2wordfreqs r merge_countsr!sSkkmm d 5=  $KKK4 KKKKE$KK LrcN |S#t$rYdSwxYw)zGet the (approximate) queue size where available. Parameters ---------- queue : :class:`queue.Queue` Input queue. Returns ------- int Queue size, -1 if `qsize` method isn't implemented (OS X). r)rr)queues rrr s7{{}} rrs  $$rch||k}||S||||}|tkrdS|tkrdS|S)a6Should we keep `word` in the vocab or remove it? Parameters ---------- word : str Input word. count : int Number of times that word appeared in a corpus. min_count : int Discard words with frequency smaller than this. trim_rule : function, optional Custom function to decide whether to keep or discard this word. If a custom `trim_rule` is not specified, the default behaviour is simply `count >= min_count`. Returns ------- bool True if `word` should stay, False otherwise. NTF) RULE_KEEP RULE_DISCARD)rcountrr default_resrule_ress rrr$sY*9$K 9T5)44 y  4  % 5 rc td||tj|d|i|}|\}}|}|r=|d}||d}tj||}||_||S#t$r| wxYw)aRun OS command with the given arguments and return its output as a byte string. Backported from Python 2.7 with a few minor modifications. Used in word2vec/glove2word2vec tests. Behaves very similar to https://docs.python.org/2/library/subprocess.html#subprocess.check_output. Examples -------- .. sourcecode:: pycon >>> from gensim.utils import check_output >>> check_output(args=['echo', '1']) '1\n' Raises ------ KeyboardInterrupt If Ctrl+C pressed. zCOMMAND: %s %sstdoutr$Nr) r r! subprocessPopen communicatepollrCalledProcessErroroutputKeyboardInterrupt terminate) r+ popenargsr%processr1 unused_errretcodecmderrors r check_outputr:Gs( %y&999"9G&GGG$0022 ,,..  **V$$C #l1'3??E!ELK  s BB B=c|r=tjttt |n&t j|}fd|DS)aSelected `n` (possibly random) items from the dictionary `d`. Parameters ---------- d : dict Input dictionary. n : int, optional Number of items to select. use_random : bool, optional Select items randomly (without replacement), instead of by the natural dict iteration order? Returns ------- list of (object, object) Selected items from dictionary, as a list. c$g|] }||f Sr,r,)rDrrs rrrzsample_dict..s! 3 3 3cS!C&M 3 3 3r)rsamplerrOrmrr@r)rrG use_random selected_keyss` r sample_dictr@msj$?IkFM$q''3s1vvq>>:::iN^_`_e_e_g_gijNkNkM 3 3 3 3] 3 3 33rcRtj|}||jdkrtj|gS||jdkrtjdS|jd}tjj||jd|z dz|f||fS)aProduce a numpy.ndarray of windows, as from a sliding window. Parameters ---------- ndarray : numpy.ndarray Input array window_size : int Sliding window size. Returns ------- numpy.ndarray Subsequences produced by sliding a window of the given size over the `ndarray`. Since this uses striding, the individual arrays are views rather than copies of `ndarray`. Changes to one view modifies the others and the original. Examples -------- .. sourcecode:: pycon >>> from gensim.utils import strided_windows >>> strided_windows(np.arange(5), 2) array([[0, 1], [1, 2], [2, 3], [3, 4]]) >>> strided_windows(np.arange(10), 5) array([[0, 1, 2, 3, 4], [1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 6, 7], [4, 5, 6, 7, 8], [5, 6, 7, 8, 9]]) r)rrr)shapestrides) rrrBrxrrClib stride_tricks as_strided)r window_sizestrides rstrided_windowsrIsHj!!GgmA&&"x """ w}Q' '"z&!!! _Q F 6  * * a(;6:KH  + " ""rc#xKt|D]'\}}t||||D]}|r||fV |V(dS)akProduce a generator over the given texts using a sliding window of `window_size`. The windows produced are views of some subsequence of a text. To use deep copies instead, pass `copy=True`. Parameters ---------- texts : list of str List of string sentences. window_size : int Size of sliding window. copy : bool, optional Produce deep copies. ignore_below_size : bool, optional Ignore documents that are not at least `window_size` in length? include_doc_num : bool, optional Yield the text position with `texts` along with each window? N)r _iter_windows)rrGcopyignore_below_sizeinclude_doc_numdoc_numrwindows r iter_windowsrQsx('u--#Hk4ARSS  F '''''  rc#Kt||}|jddkr |s|r|n|VdSdS|D]}|r|n|VdSr)rIrBrL)rrGrLrM doc_windows doc_windows rrKrKs!(K88Kq <  8%)7(--///x 7 7 7 7 7 8 8& < rsu)(%%%%%%%%%%%%000000     000000  8 $ $. ;;5rzBB L;   Sy$$&& ZZZB..+++:000<.(!(!(!(!V$:====2 ..... LLL&ynynynynynynynynx    "2@@@@@@@@F4333l!!!HIIIII8IIIDD44444H4448*****8***Z***0/7/7/7d38rz&"&"&"&"R 1818181818(181818p7d?Os|x/OC4D4NO44444n"""J!03333"222$000<0,0,0,f  /00OOO10O4BBBB$  /001029999@!!!!.cccc,XXXX0B7777,,*      F#####L4444,-"-"-"`8<<<<+++$,   4     r