ó ‡ˆ\c@södZddlZddlZddlZddlZddlZddlZddlZddlm Z m Z e r‚ej Z n ej Z de fd„ƒYZde fd„ƒYZd e fd „ƒYZd efd „ƒYZd ed„ZdS(sb Fast cryptographic hash of Python objects, with a special case for fast hashing of numpy arrays. iÿÿÿÿNi(t_bytes_or_unicodet PY3_OR_LATERt_ConsistentSetcBseZdZd„ZRS(sa Class used to ensure the hash of Sets is preserved whatever the order of its items. cCsMyt|ƒ|_Wn3ttjfk rHtd„|Dƒƒ|_nXdS(Ncss|]}t|ƒVqdS(N(thash(t.0te((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pys *s(tsortedt _sequencet TypeErrortdecimaltInvalidOperation(tselft set_sequence((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pyt__init__s(t__name__t __module__t__doc__R (((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pyRst_MyHashcBseZdZd„ZRS(s7 Class used to hash objects that won't normally pickle cGs ||_dS(N(targs(R R((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pyR 0s(RRRR (((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pyR-stHashercBsÁeZdZdd„Zed„Zd„Zd„Zd e j d„Z e j jƒZ e e eeƒls     cCs^y tj|tt|ƒƒƒWn7tk rYtj|ttd„|DƒƒƒƒnXdS(Ncss'|]\}}t|ƒ|fVqdS(N(R(Rtktv((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pys —s(Rt_batch_setitemstiterRR(R titems((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pyRHŒs   cCstj|t|ƒƒdS(N(RR3R(R t set_items((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pytsave_setšsN(RRRR tTrueRR3R7R1tstructR9R>RtdispatchtcopyR-tlentobjectRR!RHRLtset(((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pyR4s    t NumpyHashercBs&eZdZded„Zd„ZRS(s7 Special case the hasher for when numpy is loaded. RcCs\||_tj|d|ƒddl}||_t|dƒrO|j|_n t|_dS(s Parameters ---------- hash_name: string The hash algorithm to be used coerce_mmap: boolean Make no difference between np.memmap and np.ndarray objects. R iÿÿÿÿNt getbuffer( t coerce_mmapRR tnumpytnpR/RUt _getbuffert memoryview(R R RVRX((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pyR ¥s   cCsEt||jjƒrû|jj rû|jdkr@|jƒ}n9|jjrU|}n$|jj rm|j }n |jƒ}|j j |j |j|jjƒƒƒ|jrÎt||jjƒrÎ|jj}n |j}|d|j|j|jff}n6t||jjƒr1|j}|d|jff}ntj||ƒdS(s¨ Subclass the save method, to hash ndarray subclass, rather than pickling them. Off course, this is a total abuse of the Pickler class. tHASHEDN((R*RXtndarraytdtypet hasobjecttshapetflattentflagst c_contiguoust f_contiguoustTRR$RYtviewtuint8RVtmemmapR2tstridestdescrRR3(R R&tobj_c_contiguoustklass((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pyR3¹s$"       $ (RRRtFalseR R3(((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pyRT¡sRcCsCdtjkr'td|d|ƒ}ntd|ƒ}|j|ƒS(sl Quick calculation of a hash to identify uniquely Python objects containing numpy arrays. Parameters ----------- hash_name: 'md5' or 'sha1' Hashing algorithm used. sha1 is supposedly safer, but md5 is faster. coerce_mmap: boolean Make no difference between np.memmap and np.ndarray RWR RV(R<R@RTRR(R&R RVthasher((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pyRös (RRRR<R+RNRR t_compatRRt_PicklerRRRRRRRTRlR(((s?lib/python2.7/site-packages/sklearn/externals/joblib/hashing.pyts          mU