U md')@sdZddlZddlZddlZddlZddlZddlZddlZejZ Gddde Z Gddde Z Gddde Z Gd d d e Zdd dZdS)zb Fast cryptographic hash of Python objects, with a special case for fast hashing of numpy arrays. Nc@seZdZdZddZdS)_ConsistentSetza Class used to ensure the hash of Sets is preserved whatever the order of its items. c CsBzt||_Wn.ttjfk r<tdd|D|_YnXdS)Ncss|]}t|VqdSNhash).0erG/home/sam/Atlas/atlas_env/lib/python3.8/site-packages/joblib/hashing.py %sz*_ConsistentSet.__init__..)sorted _sequence TypeErrordecimalInvalidOperation)selfZ set_sequencerrr __init__sz_ConsistentSet.__init__N__name__ __module__ __qualname____doc__rrrrr rsrc@seZdZdZddZdS)_MyHashz7 Class used to hash objects that won't normally pickle cGs ||_dSr)args)rrrrr r+sz_MyHash.__init__Nrrrrr r(src@seZdZdZdddZdddZdd Zd d Zd ej fd dZ e j Z e e ee<e e ee<e e ee <e e eej<ddZddZee ee<d S)HasherzW A subclass of pickler, to do cryptographic hashing, rather than pickling. md5cCs0t|_d}tj||j|dt||_dS)N)protocol)ioBytesIOstreamPicklerrhashlibnew_hash)r hash_namerrrr r4s zHasher.__init__Tc Csvz||Wn>tjk rL}z|jd||ff7_W5d}~XYnX|j}|j||rr|jSdS)Nz"PicklingError while hashing %r: %r) dumppickle PicklingErrorrrgetvaluer#update hexdigest)robjZ return_digestrdumpsrrr r=s  z Hasher.hashcCst|tjtijfr|t|dr*|jj}n|j}|j}t|tt krTt ||j}n(|dkrht ||}n|jj }t |||}t ||dS)N__func__) isinstancetypes MethodTypetypepophasattrr-r__self__r&r __class__r save)rr+ func_nameinstclsrrr r6Hs    z Hasher.savecCs"t|ttfrdSt||dSr)r.bytesstrr memoize)rr+rrr r<[szHasher.memoizeNcCst||d}|d=ztj||f|Wnltjk rtj||f|t|dd}|dkr|}|dkrn|j}tj|}t ||st |||YnXdS)N)namepackr>r__main__) dictr save_globalr&r'getattrrsysmodulesr3setattr)rr+r=r>kwargsmoduleZmy_namemodrrr rAfs    zHasher.save_globalc CsPzt|tt|Wn2tk rJt|ttdd|DYnXdS)Ncss|]\}}t||fVqdSrr)rkvrrr r sz)Hasher._batch_setitems..)r _batch_setitemsiterr r )ritemsrrr rKs zHasher._batch_setitemscCst|t|dSr)r r6r)rZ set_itemsrrr save_setszHasher.save_set)r)T)rrrrrrr6r<structr>rAr dispatchcopyr1lenobjectr&r%rKrNsetrrrr r/s      rc@s"eZdZdZd ddZddZdS) NumpyHasherz7 Special case the hasher for when numpy is loaded. rFcCs@||_tj||dddl}||_t|dr6|j|_nt|_dS)a Parameters ---------- hash_name: string The hash algorithm to be used coerce_mmap: boolean Make no difference between np.memmap and np.ndarray objects. r$rN getbuffer) coerce_mmaprrnumpynpr3rW _getbuffer memoryview)rr$rXrZrrr rs   zNumpyHasher.__init__cCst||jjr|jjs|jdkr*|}n&|jjr8|}n|jj rH|j }n|}|j | ||jj|jrt||jjr|jj}n|j}|d|j|j|jff}n6t||jjr|j dd|j t|dSt||dS)z Subclass the save method, to hash ndarray subclass, rather than pickling them. Off course, this is a total abuse of the Pickler class. rZHASHEDZ _HASHED_DTYPEzutf-8N)r.rZZndarrayZdtypeZ hasobjectshapeflattenflags c_contiguous f_contiguousTr#r)r[viewZuint8rXZmemmapr5stridesencoder&r,rr6)rr+Zobj_c_contiguousklassrrr r6s(   zNumpyHasher.saveN)rF)rrrrrr6rrrr rUs rUrFcCsHd}||krtd||dtjkr4t||d}n t|d}||S)aj 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 )rsha1zAValid options for 'hash_name' are {}. Got hash_name={!r} instead.rY)r$rXrV) ValueErrorformatrCrDrUrr)r+r$rXZvalid_hash_namesZhasherrrr rs   r)rF)rr&r!rCr/rOrr_Picklerr rSrrrrUrrrrr s kZ