:jfdZddlZddlZddlZddlmZddlmZm Z m Z m Z m Z ddl ZddlmZddlmZddlmZddlmZmZmZmZddlmZdd lmZdd lm Z dd l!m"Z"m#Z#ejHjKd Z&ejHjKd Z'ejHjKdZ(dZ)e)Z*dZ+Gdde jXZ-dZ.Gdde j^Z0dZ1eZ2ejHjKdZ3Gdde4Z5da6dZ7da8da9dZ:dZ;dZe>Z?e"e?d Z@d!ZAe"eAd"ZBd#ZCe"eCd$ZDe#d%ZEd&ZFe"eFd'ZGe#d(ZHd)ejvZJeKejjd)dZMeJr eMre<d*ZNd+ZOe"eNd,ZPe"eOd-ZQy).a This file implements the code-generator for parallel-vectorize. ParallelUFunc is the platform independent base class for generating the thread dispatcher. This thread dispatcher launches threads that execute the generated function of UFuncCore. UFuncCore is subclassed to specialize for the input/output types. The actual workload is invoked inside the function generated by UFuncCore. UFuncCore also defines a work-stealing mechanism that allows idle threads to steal works from other threads. N)RLock) CFUNCTYPEc_intCDLLPOINTERc_uint)ir)as_dtype)typescgutilsconfigerrors) signature) _wrapper_info) ufuncbuilder)overload intrinsicdarwinlinuxwin32cFtj}|dkr td|S)z* Gets the available thread count. z(Number of threads specified must be > 0.)r NUMBA_NUM_THREADS ValueError)ts l/home/mcse/projects/srt_converter/srt-converter-venv/lib/python3.12/site-packages/numba/np/ufunc/parallel.pyget_thread_countr$s'   A1uCDD Hc $!"t|tsJtjd}tj|"tj"}|j t j}tj|}tjtjtj"tj|tj|"g} |jjd} | jd} djt|j|j } tj"| | | } | j%d}tj&|!| j(\}}}}|j+!}|j-}|j/}!"fd}t1|j(}t|j2t j4s|dz }tjtj"gd z|gd zz}t7j8| |d }tjtj|||"g}t7j8| ||j }| j;|j<t7j8!j>tjtjt jj@gd }!jC|g}!jE|"}||||fDcgc] }|| } }!jC||g| z||fDcgc] }|| c}z|gz|jG||jI|!jK| jM| | j;|tO| | j |j Scc}wcc}w)aWrap 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(j|SN)bitcast)argbuilder byte_ptr_ts r as_void_ptrz(build_gufunc_kernel..as_void_ptrssJ//rrnumba_parallel_forget_num_threads)libraryr"env)( isinstancetupler IntType PointerTypeget_value_typer intp FunctionTypeVoidTypecodegencreate_librarycreate_ir_moduleformatidr0r"Functionappend_basic_block IRBuilderargsget_python_api gil_ensure save_threadlen return_typeNoneTyper get_or_insert_functionadd_linking_libraryr/modulebitwidthcallr&restore_thread gil_releaseret_void add_ir_moduler)#r/ctxinfosig inner_ndimbyte_tbyte_ptr_ptr_tintp_t intp_ptr_tfnty wrapperlibmod kernel_namelfuncbb_entryrA dimensionsstepsdatapyapi gil_state thread_stater* array_countparallel_for_ty parallel_forinnerfunc_fnty tmp_voidptrr. num_threadsfnptrx innerargsr(r)s# @@rbuild_gufunc_kernelrn1sQ` dE "" " ZZ]F'J^^J/N    +F'J ??2;;=2>>*+E+->>&+A+->>&+A+5+7 8D--.EFJ  % %&? @C!((DHHtyyAK KKT 4E''+Hll8$G$)JJ!D*eT   w 'E  "I$$&L0chh-K coou~~ 6q oobkkm'1lQ&6&a&GIO11#2FHL__ Z<N00n15=K""4<<044  5::#6#67<O ,,3K OOK 4E:ud35AQ5I5 LLw2&0+%>?&)? @CN- PQ & i  S!""7+ %**$(( KK5@s P6P ceZdZdZy)ParallelUFuncBuilderct|j}|j}|j}|jj }t |||||}|jj|j}|jD cgc]+} tj| jj-} } | jtj|jjjd} | || fScc} w)N)_launch_threadstarget_contextrr/fndescllvm_func_namebuild_ufunc_wrapperget_pointer_to_functionr"rAnpdtypenumappendrF) selfcresrSrQrr/fnamerRptra dtypenums keepalives rbuildzParallelUFuncBuilder.builds!!NN ,, **"7C 4Hll22499=3<>>BaRXXaff%))B B)"7"7"<"<=AAB #y((Cs0DN)__name__ __module__ __qualname__rrrrrrprps)rrpc tj||||d|}t||||t|j}|S)NF)objmoder~)rrwrnrErA)r/rQrrr~ innerfuncrRs rrwrwsE00#u1:E6:>2 4D Krc*eZdZ dfd ZdZxZS)ParallelGUFuncBuildercx|i}|jtdtt| ||||||y)NT)nopython)py_funcridentitycache targetoptions writable_args)updatedictsuperr__init__)r}rrrrrr __class__s rrzParallelGUFuncBuilder.__init__sP  MT401 !  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This changes codegen and caching behavior. rc3.K|] }|D]}|ywr%rr.0termsyms r z'build_gufunc_wrapper.. s5555c3.K|] }|D]}|ywr%rrrs rrz'build_gufunc_wrapper..s7$$73#7#7r)r/rtrrrsetrErn)rr~rrrrr/rQr innerinfosym_insym_outrTrRs rrrs llG   CI11sD*I55 5F7$77GVg%&J iJ D KrceZdZdZdZdZy)_nopzA no-op contextmanager cyr%rr)r}s r __enter__z_nop.__enter__" rcyr%rr)r}rAs r__exit__z _nop.__exit__%rrN)rrr__doc__rrrrrrrrs  rrcn t5ddl}d|jvstr!|j }|j an tadddy#1swYyxYw#t$rF}d}tj|t|ztjtaYd}~yd}~wwxYw)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)rrQemsgs r_set_init_process_lockr,s, ' 4 "99;;x%113-0YY[*-1V*  4 4 4  ,    cCFlF$=$=>%)V" ,s5A%AAA%A"A%"A%% B4.??rc trd}ntrd}ntrd}n tdt |}|j }g|_t|_|}|dkr=d|z}tj|}tj|td|zy#ttf$r}td|zd}~wwxYw) zF 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. 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Reason: %sN) _IS_WINDOWS_IS_OSX _IS_LINUXrrTBB_runtime_interface_versionargtypesrrestyper NumbaWarningrr ImportErrorr) libtbb_namelibtbb version_func tbb_iface_verrproblemrs r_check_tbb_version_compatibler[s> %K +K (K78 8k";; " $ $ 5 26C CC ))#.G MM' "81<==>sBBB=*B88B=c ts tt5t5tr ddddddyd fd}t t j j}t j}t|dk(rt|hdk(std|zd}t d d<d d <g} fd }||vr@ |}|s3|d k(r|jdn|d k(rtr|jd |}n|d vrd g}|jd|dk(rn|dk(r)tr|jd |jd nU|dk(r@ts|jd tr|jd |jdnd}t||z||\}}nK|dk(r6||\}}|s9|jdtr"|jd nd}t||z|s||t!j"d|j$t!j"d|j&t!j"d|j(t!j"d|j*t!j"d|j,t/dt0|j2} | t4t7||adaddddddy#1swYxYw#1swYyxYw)Ncd}|jdr tddlm}|S|jdr ddlm}|S|jdrddlm}|Sd }t||z#t$rY|SwxYw#t$rY|SwxYw) zZ 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_backendz-_launch_threads..select_known_backends%%e,57A ''.A '' 4? 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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_OMPcd}d}t|dk(rd}t|dk(r ||dz}t|dkDr*dj|Dcgc]}| c}}|d|zz}t|zcc}w)Nz&No threading layer could be loaded. %szHINT: %srr#rz OR z One of: %s)rEjoinr)requirederrmsghintmsghintrloptions err_helperss rraise_with_hintz(_launch_threads..raise_with_hintsB%x=A%Dx=A%"[!%==Dx=1$&mmX,N[^,NOG"mg&=>D $//-Os A5rr) 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_PRIORITYrErrrr|rrll add_symbolrgrrrrrrlaunch_threads NUM_THREADS_load_threading_functionsr) rr namedbackendsr requirementsrlibname availablerrrrs @@rrsrs}s % #R# &Q #Q #R#R#  6 $F**+113A";;M &!+ &*EE 2$$C&K# Wi 4MB W ''.$++I6O q)) - MM.0@0@ A MM0#2J2J K MM2C4N4N O MM*C,>,> ? MM,c.B.B C3YtU3C4F4FGN ; ' %c * ' "OcQ #R#R#Q #Q #R#R#s-K?K3K?J)K3"K?3K< 8K??Lc ntjd|jtjd|jtjd|jt dt |jattt t |ja t t |ja tjd|jtjd|jtjd|jt tt|jat t|jat tttt#t t#t |jay)Nr.set_num_threads get_thread_idset_parallel_chunksizeget_parallel_chunksizeget_sched_size)rrr.r r rr_set_num_threadsr_get_num_threads_get_thread_idr r r r_set_parallel_chunksize_get_parallel_chunksizer_get_sched_size)rs rrrsHMM#S%8%89MM#S%8%89MM/3#4#45.yu-c.A.AB[!(y'(;(;<&Yu%c&7&78NMM*C,F,FGMM*C,F,FGMM"C$6$670i(.0030J0JL0i/0J0JK0i & & ' ' 0140B0B DOrc,ddlmdzfd}|S)Nr)rz.The number of threads must be between 1 and %sc0|kDs|dkr ty)Nr)r)nrrs r snt_checkz gen_snt_check..snt_check<s!  AES/ !%*r)numba.core.configr)rrrs @@r gen_snt_checkr8s3 :=N NC" rctSr%)rrs r ol_snt_checkrEs rctt|ttjfs t dt |t|y)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)rsr1intryinteger TypeErrorrrrs rr r Js8. a#rzz* +LMM aLQrctt|tjsd}t j |d}|S)Nrc0t|t|yr%)rrrs rimplz ol_set_num_threads..implos! rrsr1r Integerr TypingErrorrrr$s rol_set_num_threadsr)hs8 a 'B  %% Krcltt}|dkrtdtd|d|S)aM 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=))rsr RuntimeErrorr rjs rr.r.us=,"$Ka*O[:; ; rc td}|S)Nczt}|dkr+tdttd|td|S)NrzBroken thread_id: z num_threads: z@Invalid number of threads. This likely indicates a bug in Numba.)rprintr r,r-s rr$z ol_get_num_threads..implsD&( !  &  8 /; / GH Hrrsr$s rol_get_num_threadsr3s KrcRtd}ttj|fS)Nc|j}tjtjg}tj ||d}|j |gS)Nr.rJr r7r rWrHrLcontextr(rrAr[rYfns rr9z"_iget_num_threads..codegensEnnw~~r2  + +C7H I||B##r)rsrr r6 typingctxr9s r_iget_num_threadsr<s#$ UZZ ' ))rc*ttS)zv Returns a unique ID for each thread in the range 0 (inclusive) to :func:`~.get_num_threads` (exclusive). )rsrrrrrr r s  rc td}|S)NctSr%)_iget_thread_idrrrrr$zol_get_thread_id..impls   rr1r2s rol_get_thread_idrAs! Krc>d}ttj|fS)Nc|j}tjtjg}tj ||d}|j |gS)Nr r6r7s rr9z _iget_thread_id..codegensDnnw~~r2  + +C G||B##r)rr r6r:s rr@r@s$ UZZ ' ))rNUMBA_DYLD_WORKAROUNDctt|ttjfs t d|dkr t dt|S)N)The parallel chunksize must be an integerr/chunksize must be greater than or equal to zero)rsr1rryr r!rrrs rr r sE a#rzz* +CDD1uJKK "1 %%rc*ttSr%)rsrrrrrr r s " $$rctt|tjsd}t j |d}|S)NrFc8|dkr tdt|S)NrrG)rrrs rr$z'ol_set_parallel_chunksize..impls q5NO O&q))rr%r(s rol_set_parallel_chunksizerKs8 a '9  %%* Krc td}|S)NctSr%)rrrrrr$z'ol_get_parallel_chunksize..impls &((rr1r2s rol_get_parallel_chunksizerNs) Kr)Rrossysr threadingr threadRLockctypesrrrrrnumpyryllvmlite.bindingbindingrllvmliter numba.np.numpy_supportr numba.corer r r rnumba.core.typingrnumba.np.ufunc.wrappersrrrnumba.extendingrrplatformrrrrrrrn UFuncBuilderrprw GUFuncBuilderrrrrobjectrrrrrrrrsrrrrr r)r.r3r<r rAr@environ_DYLD_WORKAROUND_SETrget_DYLD_WORKAROUND_VALr r rKrNrrrrres=  *::+55'1'/ ,, ! !( + LL # #G , ll%%g.   LH)<44)&(#L66(#\0(M << " "7 + 6 ",> >DV#rDD O  )< /  @ /   * *  - * */"**<2::>>*A1EF0&%  ! "  !"r