ZhfSrSSKrSSKrSSKrSSKJr SSKJrJ r J r J r J r SSK rSSKJr SSKJr SSKJr SSKJrJrJrJr SSKJr SS KJr SS KJ r SS K!J"r"J#r# \RHRKS 5r&\RHRKS 5r'\RHRKS5r(Sr)\)"5r*Sr+"SS\ RX5r-Sr."SS\ R^5r0Sr1\"5r2\RHRKS5r3"SS\45r5Sq6Sr7Sq8Sq9Sr:Sr;Sr\>"5r?\""\?5S 5r@S!rA\""\A5S"5rBS#rC\""\C5S$5rD\#S%5rES&rF\""\F5S'5rG\#S(5rHS)\R;rJ\K"\RRS)S55rM\J(a\M(a\<"5 S*rNS+rO\""\N5S,5rP\""\O5S-5rQg).a This file implements the code-generator for parallel-vectorize. ParallelUFunc is the platform independent base class for generating the thread dispatcher. This thread dispatcher launches threads that execute the generated function of UFuncCore. UFuncCore is subclassed to specialize for the input/output types. The actual workload is invoked inside the function generated by UFuncCore. UFuncCore also defines a work-stealing mechanism that allows idle threads to steal works from other threads. N)RLock) CFUNCTYPEc_intCDLLPOINTERc_uint)ir)as_dtype)typescgutilsconfigerrors) signature) _wrapper_info) ufuncbuilder)overload intrinsicdarwinlinuxwin32cH[RnUS:a [S5eU$)z" Gets the available thread count. z(Number of threads specified must be > 0.)r NUMBA_NUM_THREADS ValueError)ts f/home/gothic/public_html/Fooocus/fooocus_env/lib64/python3.13/site-packages/numba/np/ufunc/parallel.pyget_thread_countr$s'   A1uCDD Hc \^!^"[U[5(de[R"S5n[R"U5m"[R"T"5nUR [ R5n[R"U5n[R"[R"5[R"T"5[R"U5[R"U5T"/5n UR5RS5n U RS5n SR[UR5UR 5n [R""XU S9n U R%S5n[R&"U5m!U R(unnnnUR+T!5nUR-5nUR/5nU!U"4Sjn[1UR(5n[UR2[ R45(dUS- n[R"[R"5T"/S -U/S --5n[6R8"U US 5n[R"[R"5XhUT"/5n[6R8"U UUR 5nU R;UR<5 [6R8"T!R>[R"[R"[ RR@5/5S 5nT!RCU/5nT!REUT"5nUUUU4Vs/sH nU"U5PM n nT!RCUU/U -UU4Vs/sH nU"U5PM sn-U/-5 URGU5 URIU5 T!RK5 U RMU 5 U R;U5 [OXR URS 9$s snfs snf)atWrap the original CPU ufunc/gufunc with a parallel dispatcher. This function will wrap gufuncs and ufuncs something like. Args ---- ctx numba's codegen context info: (library, env, name) inner function info sig type signature of the gufunc inner_ndim inner dimension of the gufunc (this is len(sig.args) in the case of a ufunc) Returns ------- wrapper_info : (library, env, name) The info for the gufunc wrapper. Details ------- The kernel signature looks like this: void kernel(char **args, npy_intp *dimensions, npy_intp* steps, void* data) args - the input arrays + output arrays dimensions - the dimensions of the arrays steps - the step size for the array (this is like sizeof(type)) data - any additional data The parallel backend then stages multiple calls to this kernel concurrently across a number of threads. Practically, for each item of work, the backend duplicates `dimensions` and adjusts the first entry to reflect the size of the item of work, it also forms up an array of pointers into the args for offsets to read/write from/to with respect to its position in the items of work. 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NOTE: The execution backend is passed the requested thread count, but it can choose to ignore it (TBB)! parallelgufuncwrapperzparallel.gufunc.wrapperz .kernel.{}_{})namec(>TRUT5$N)bitcast)argbuilder byte_ptr_ts r as_void_ptr(build_gufunc_kernel..as_void_ptrssJ//rrnumba_parallel_forget_num_threads)libraryr"env)( isinstancetupler IntType PointerTypeget_value_typer intp FunctionTypeVoidTypecodegencreate_librarycreate_ir_moduleformatidr1r"Functionappend_basic_block IRBuilderargsget_python_api gil_ensure save_threadlen return_typeNoneTyper get_or_insert_functionadd_linking_libraryr0modulebitwidthcallr&restore_thread gil_releaseret_void add_ir_moduler)#r0ctxinfosig inner_ndimbyte_tbyte_ptr_ptr_tintp_t intp_ptr_tfnty wrapperlibmod kernel_namelfuncbb_entryrB dimensionsstepsdatapyapi gil_state thread_stater* array_countparallel_for_ty parallel_forinnerfunc_fnty tmp_voidptrr/ num_threadsfnptrx innerargsr(r)s# @@rbuild_gufunc_kernelro1s^` dE " "" " ZZ]F'J^^J/N    +F'J ??2;;=2>>*+E+->>&+A+->>&+A+5+7 8D--.EFJ  % %&? @C!((DHHtyyAK KK 4E''+Hll8$G$)JJ!D*eT   w 'E  "I$$&L0chh-K coou~~ 6 6q oobkkm'1lQ&6&a&GIO11#2FHL__ Z<N00n15=K""4<<044  5::#6#67<O ,,3K OOK 4E:ud353%&Q35 LLw2&0+%>?%>&)%>? @CN- PQ & i  S!""7+ **$(( KK5@s (P$P) c\rSrSrSrSrg)ParallelUFuncBuilderc[5 URnURnURnURR n[ XSXdU5nURRUR5nURV s/sH-n [R"U R5RPM/ n n U R[R"URR5R5 Sn XU 4$s sn f)N)_launch_threadstarget_contextrr0fndescllvm_func_namebuild_ufunc_wrapperget_pointer_to_functionr"rBnpdtypenumappendrG) selfcresrTrRrr0fnamerSptra dtypenums keepalives rbuildParallelUFuncBuilder.builds!!NN ,, **"74Hll22499=3<>>B>aRXXaff%))> B)"7"7"<"<=AAB y((Cs4DrtN)__name__ __module__ __qualname____firstlineno__r__static_attributes__rtrrrqrqs)rrqc v[R"XUUSUS9n[XXS[UR55nU$)NF)objmoder)rryrorFrB)r0rRrrr innerfuncrSs rryrys?00u1:E6:>2 4D Krc:^\rSrSrSS0S4U4SjjrSrSrU=r$)ParallelGUFuncBuilderNFrtc d>UR[SS95 [[U]UUUUUUS9 g)NT)nopython)py_funcridentitycache targetoptions writable_args)updatedictsuperr__init__)rrrrrrr __class__s rrParallelGUFuncBuilder.__init__sE T401 !  '' )rc [5 [URXRURUR SS9nUR RUR5nURn/nURRHUn[U[R5(a URnOUnUR![#U5R$5 MW XSU4$)z: Returns (dtype numbers, function ptr, EnvironmentObject) Fr is_parfors)rubuild_gufunc_wrapperrsinsoutrr0rzr"r1rrBr2r Arrayr|r~r r})rrrSrr1rrtys rrParallelGUFuncBuilder.builds $ LL$$))4:: ll22499=hh $$A!U[[))WW   Xb\-- . %s""r)rrrrrrr __classcell__)rs@rrrs48! )##rrc URnURnURn[R"XX#XES9n [ SU55n [ SU55n [ X-5n [XgXU 5n U $)zBuild gufunc wrapper for the given arguments. The *is_parfors* is a boolean indicating whether the gufunc is being built for use as a ParFors kernel. This changes codegen and caching behavior. rc36# UHoHo"v M M g7fr%rt.0termsyms r 'build_gufunc_wrapper.. s5c36# UHoHo"v M M g7fr%rtrs rrr s7$$$3#$#$r)r0rvrrrsetrFro)rrrrrrr0rRr innerinfosym_insym_outrUrSs rrrs llG   CI11sI55 5F7$77GV%&J iJ D Krc$\rSrSrSrSrSrSrg)_nopizA no-op contextmanager cgr%rt)rs r __enter___nop.__enter__  rcgr%rt)rrBs r__exit__ _nop.__exit__#rrrtN)rrrr__doc__rrrrtrrrrs  rrc[ SSKnSUR5;d [(a!UR 5nUR 5qO [5qSSS5 g!,(df  g=f![aGnSn[R"U[U5-[R5 [5qSnAgSnAff=f)NrforkaACould not obtain multiprocessing lock due to OS level error: %s A likely cause of this problem is '/dev/shm' is missing or read-only such that necessary semaphores cannot be written. *** The responsibility of ensuring multiprocessing safe access to this initialization sequence/module import is deferred to the user! *** )_backend_init_thread_lockmultiprocessingget_start_method_windows get_contextr_backend_init_process_lockrOSErrorwarningswarnstrrNumbaSystemWarning)rrRemsgs r_set_init_process_lockr*s, ' "99;;xx%113-0YY[*-1V* ' & &  ,    cCFlF$=$=>%)V" ,s5A1AA A1 A.*A1.A11 C;=B==CFc2[c [S5e[$)zE Get the name of the threading layer in use for parallel CPU targets z#Threading layer is not initialized.)_threading_layerrrtrrthreading_layerrOs>??rc[(aSnO'[(aSnO[(aSnO [S5e[ U5nUR n/Ul[UlU"5nUS:a?SU-n[R"U5n[R"U5 [SU-5eg![[4an[SU-5eSnAff=f) z> Checks that if TBB is present it is of a compatible version. z tbb12.dllzlibtbb.12.dylibz libtbb.so.12zUnknown operating systemi/zThe TBB threading layer requires TBB version 2021 update 6 or later i.e., TBB_INTERFACE_VERSION >= 12060. Found TBB_INTERFACE_VERSION = %s. The TBB threading layer is disabled.zProblem with TBB. Reason: %sN) _IS_WINDOWS_IS_OSX _IS_LINUXrrTBB_runtime_interface_versionargtypesrrestyper NumbaWarningrr ImportErrorr) libtbb_namelibtbb version_func tbb_iface_verrproblemrs r_check_tbb_version_compatiblerYs> ;%K W+K Y(K78 8k";; " $ $ 5 26C CC ))#.G MM' "81<==>sB*B--C=C  Cc^ ^ [(d [5 [ [ [(aSSS5 SSS5 gSm U 4Sjn[ [ R 5R5n[ Rn[U5S:Xa[U51Sk:Xd[SU-5eSn[5m ST S'ST S '/nU 4S jnX;aMT "U5nU(d:US :XaURS5 O"US :Xa[(aURS 5 UnGOUS ;aS /nURS5 US:XaOUS:Xa.[(aURS 5 URS 5 O_US:XaJ[(dURS 5 [(aURS 5 URS5 OSn[X-5eU"U5up6OTUS:Xa?U"U5up6U(d-URS5 [(aURS 5 OSn[X-5eU(dU"U5 [ R""SUR$5 [ R""SUR&5 [ R""SUR(5 [ R""SUR*5 [ R""SUR,5 [/S[05"UR25n U "[45 [7U5 UqSqSSS5 SSS5 g!,(df  N=f!,(df  g=f)Nc4SnURS5(a[5 SSKJn U$URS5(a SSKJn U$URS5(aSSKJn U$S n[X -5e![a U$f=f![a U$f=f) z: Loads a specific threading layer backend based on string Ntbbr)tbbpoolomp)omppool workqueue)rz/Unknown value specified for threading layer: %s) startswithrnumba.np.ufuncrrrrr)backendlibrs rselect_known_backend-_launch_threads..select_known_backends%%e,,57A ''..A '' 44? 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It must be a permutation of {'tbb', 'omp', 'workqueue'}z3Intel TBB is required, try: $ conda/pip install tbbTBBz?Intel OpenMP is required, try: $ conda/pip install intel-openmpOSX_OMPc>SnSn[U5S:XaSn[U5S:Xa UTUS-n[U5S:a-SRUVs/sHnTUPM sn5nUSU--n[UW-5es snf)Nz&No threading layer could be loaded. %szHINT: %srr#rz OR z One of: %s)rFjoinr)requirederrmsghintmsghintrmoptions err_helperss rraise_with_hint(_launch_threads..raise_with_hintsB%x=A%Dx=A%"[!%==Dx=1$&mmX,NX[^X,NOG"mg&=>D $//-OsA;rr) threadsafeforksafesaferrrrz+No threading layer available for purpose %sdefaultz7The threading layer requested '%s' is unknown to Numba.r.do_scheduling_signeddo_scheduling_unsignedallocate_scheddeallocate_schedT)rrr_is_initializedrr THREADING_LAYERlowerTHREADING_LAYER_PRIORITYrFrrrr~rrll add_symbolrhrrrrrrlaunch_threads NUM_THREADS_load_threading_functionsr) rr namedbackendsr requirementsrlibname availablerrrrs @@rruru{s % % # &' $ #  6 $F**+113A";;M &!+ &*EE 2$$C&K# Wi 4MB  ''.w$++I6O )) - MM.0@0@ A MM0#2J2J K MM2C4N4N O MM*C,>,> ? MM,c.B.B C&tU3C4F4FGN ; ' %c * ' "Oc' $ # & & $ #s.M L4MK L4#M4 M >M Mc z[R"SUR5 [R"SUR5 [R"SUR5 [ S[ 5"UR5q[[5 [ [ 5"UR5q [ [ 5"UR5q [R"SUR5 [R"SUR5 [R"SUR5 [ [[5"UR5q[ [5"UR5q[ [[[[#[ 5[#[ 55"UR5qg)Nr/set_num_threads get_thread_idset_parallel_chunksizeget_parallel_chunksizeget_sched_size)r rr/rrrr_set_num_threadsr_get_num_threads_get_thread_idrrrr_set_parallel_chunksize_get_parallel_chunksizer_get_sched_size)rs rrrs8MM#S%8%89MM#S%8%89MM/3#4#45!u-c.A.AB[!!'(;(;<u%c&7&78NMM*C,F,FGMM*C,F,FGMM"C$6$67'(.0030J0JL(/0J0JK & & ' ' 0140B0B DOrc.^^SSKJm ST-mUU4SjnU$)Nr)rz.The number of threads must be between 1 and %sc4>UT:dUS:a [T5eg)Nr)r)nrrs r snt_check gen_snt_check..snt_check:s!  AES/ !%*r)numba.core.configr)r%rrs @@r gen_snt_checkr(6s3 :=N NC" rc[$r%)r%r$s r ol_snt_checkr+Cs rc[5 [U[[R45(d [ S5e[ U5 [U5 g)a Set the number of threads to use for parallel execution. By default, all :obj:`numba.config.NUMBA_NUM_THREADS` threads are used. This functionality works by masking out threads that are not used. Therefore, the number of threads *n* must be less than or equal to :obj:`~.NUMBA_NUM_THREADS`, the total number of threads that are launched. See its documentation for more details. This function can be used inside of a jitted function. Parameters ---------- n: The number of threads. Must be between 1 and NUMBA_NUM_THREADS. See Also -------- get_num_threads, numba.config.NUMBA_NUM_THREADS, numba.config.NUMBA_DEFAULT_NUM_THREADS, :envvar:`NUMBA_NUM_THREADS` 2The number of threads specified must be an integerN)rur2intr{integer TypeErrorr%rr*s rrrHs;. a#rzz* + +LMM aLQrc[5 [U[R5(dSn[R "U5eSnU$)Nr-c0[U5 [U5 gr%)r%rr*s rimpl ol_set_num_threads..implms! rrur2r Integerr TypingErrorr$rr3s rol_set_num_threadsr9fs; a ' 'B  %% Krcr[5 [5nUS::a[S[5<SU<S35eU$)a Get the number of threads used for parallel execution. By default (if :func:`~.set_num_threads` is never called), all :obj:`numba.config.NUMBA_NUM_THREADS` threads are used. This number is less than or equal to the total number of threads that are launched, :obj:`numba.config.NUMBA_NUM_THREADS`. This function can be used inside of a jitted function. Returns ------- The number of threads. See Also -------- set_num_threads, numba.config.NUMBA_NUM_THREADS, numba.config.NUMBA_DEFAULT_NUM_THREADS, :envvar:`NUMBA_NUM_THREADS` rzLInvalid number of threads. This likely indicates a bug in Numba. (thread_id=z, num_threads=))rur RuntimeErrorrrks rr/r/ss=,"$Ka*O[:; ; rc [5 SnU$)Nc|[5nUS::a+[S[55 [SU5 [S5eU$)NrzBroken thread_id: z num_threads: z@Invalid number of threads. 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Krc>Sn[[R5U4$)NcURn[R"[R/5n[R "XES5nUR U/5$)NrrGrHs rr: _iget_thread_id..codegensBnnw~~r2  + +C G||B##r)rr r7rLs rrRrRs$ UZZ ' ))rNUMBA_DYLD_WORKAROUNDc[5 [U[[R45(d [ S5eUS:a [ S5e[U5$)N)The parallel chunksize must be an integerr/chunksize must be greater than or equal to zero)rur2r.r{r/r0rrr*s rrrsH a#rzz* + +CDD1uJKK "1 %%rc*[5 [5$r%)rur rtrrrrs " $$rc[5 [U[R5(dSn[R "U5eSnU$)NrZc:US:a [S5e[U5$)Nrr[)rrr*s rr3'ol_set_parallel_chunksize..impls q5NO O&q))rr5r8s rol_set_parallel_chunksizer`s; a ' '9  %%* Krc [5 SnU$)Nc[5$r%)r rtrrr3'ol_get_parallel_chunksize..impls &((rrBrCs rol_get_parallel_chunksizerds) Kr)Rrossysr threadingr threadRLockctypesrrrrrnumpyr{llvmlite.bindingbindingr llvmliter numba.np.numpy_supportr numba.corer r r rnumba.core.typingrnumba.np.ufunc.wrappersrrrnumba.extendingrrplatformrrrrrrro UFuncBuilderrqry GUFuncBuilderrrrrobjectrrrr rrrrurr(r%r+rr9r/rDrNrrTrRenviron_DYLD_WORKAROUND_SETr.get_DYLD_WORKAROUND_VALrrr`rdrtrrr{s=  *::+55'1'/ ,, ! !( + LL # #G , ll%%g.   LH)<44)&&#L66&#X0(M << " "7 + 6 ",> >DV#rDD O  )< /  @ /   * *  - * */"**<2::>>*A1EF0&%  ! "  !"r