+ :i+^Rt^RIt^RIt^RIt^RIt^RIHtHtHtH t H t H t H t ^RI t ^RIHt^RIHtHtHt^RIHtHtHt^RIHtHt]P6!]4t^t^t^t ^t!^t"]t#]t$RPK4t&]'!]&4F!wt(t)]*!]PV],])](4K# Rt,R t-R t.] P^!4t0!R R ]14t2!R R]14t3R&t4R'R(R)R(R*R+R,R+R-R+R.R+R/R0R1R2R3R2R4R2R5R2R6R2/ t5Rt6Rt7Rt8Rt9Rt:!RR]14t;RtRt?Rt@RtARtBRtCRtDRtER tFR!tG]P!R"4tIR#tJR$tKR%tLR#)7z( This is a direct translation of nvvm.h N)c_void_pc_intPOINTERc_char_pc_size_tbyrefc_char)ir) NvvmErrorNvvmSupportError NvvmWarning) get_libdeviceopen_libdevice open_cudalib)cgutilsconfiga NVVM_SUCCESS NVVM_ERROR_OUT_OF_MEMORY NVVM_ERROR_PROGRAM_CREATION_FAILURE NVVM_ERROR_IR_VERSION_MISMATCH NVVM_ERROR_INVALID_INPUT NVVM_ERROR_INVALID_PROGRAM NVVM_ERROR_INVALID_IR NVVM_ERROR_INVALID_OPTION NVVM_ERROR_NO_MODULE_IN_PROGRAM NVVM_ERROR_COMPILATION ze-p:64:64:64-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:64-f32:32:32-f64:64:64-v16:16:16-v32:32:32-v64:64:64-v128:128:128-n16:32:64ze-p:64:64:64-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:64-i128:128:128-f32:32:32-f64:64:64-v16:16:16-v32:32:32-v64:64:64-v128:128:128-n16:32:64c@\4R# \dR#i;i)z Return if libNVVM is available TF)NVVMr U/var/www/html/photoedit/myenv/lib/python3.14/site-packages/numba/cuda/cudadrv/nvvm.py is_availabler<s%  s  ca]tRt^KtoRtR]]!]4]!]43R]]!]43R]]!]43R]]] ] ] 3R]]] ] ] 3R]]]]!] 43R]]]!] 43R ]]] 3R ]]]!] 43R ]]] 3R ]]!]4]!]4]!]4]!]43R ]]]]!] 43/ t Rt Rt Rt]R4t]R4tRtRtRRltRtVtR#)rzProcess-wide singleton. nvvmVersionnvvmCreateProgramnvvmDestroyProgramnvvmAddModuleToProgramnvvmLazyAddModuleToProgramnvvmCompileProgramnvvmGetCompiledResultSizenvvmGetCompiledResultnvvmGetProgramLogSizenvvmGetProgramLog nvvmIRVersionnvvmVerifyProgramNc\;_uu_4VPf\PV4;Vnp\ R4VnTPP4FCwrE\TP T4pT^,Tn TR,Tn \YT4KE RRR4VP# \ d pRTnRp\Y2,4hRp?ii;i +'giTP#;i)Nnvvmz;libNVVM cannot be found. Do `conda install cudatoolkit`: %s:NN) _nvvm_lock_NVVM__INSTANCEobject__new__rdriverOSErrorr _PROTOTYPESitemsgetattrrestypeargtypessetattr)clsinsteerrmsgnameprotofuncs& rr+ NVVM.__new__s Z~~%(.s(;;7".v"6DK$(#3#3#9#9#;KD"4;;5D#(8DL$)"IDMD- $<$~~7%)CN2F*6:66 7 Z$~~s/+C-C A!C- C* C%%C**C-- D cVP4pV^,VnV^,VnV^,VnV^,Vn\ 4VnR#)N)get_ir_version_majorIR_minorIR _majorDbg _minorDbgget_supported_ccs_supported_ccs)self ir_versionss& r__init__ NVVM.__init__sG))+ #A #A $Q$Q/1rcTVPVP3R8d\#\#)r')r')r?r@_datalayout_original_datalayout_i128rEs&r data_layoutNVVM.data_layouts# MM4== )F 2' '# #rcVP#N)rDrMs&r supported_ccsNVVM.supported_ccss"""rc\4p\4pVP\V4\V44pVPVR4VPVP3#)zFailed to get version.)rrr check_errorvalue)rEmajorminorerrs& r get_versionNVVM.get_versionsNuU|U5\: 67{{EKK''rcB\4p\4p\4p\4pVP\V4\V4\V4\V44pVPVR4VPVPVPVP3#)zFailed to get IR version.)rr#rrUrV)rEmajorIRminorIRmajorDbgminorDbgrYs& rr>NVVM.get_ir_versionsx''77  ww!&x%/C 9:}}gmmX^^X^^KKrcV'dE\V\V,4pV'd$\V4\P!^4R#VhR#)r'N)r RESULT_CODE_NAMESprintsysexit)rEerrormsgrfexcs&&&& rrUNVVM.check_errors6 C!25!9:Cc   r)rAr?rBr@rD)F)__name__ __module__ __qualname____firstlineno____doc__ nvvm_resultrr nvvm_programrrr.r)r+rGpropertyrNrRrZr>rU__static_attributes____classdictcell__ __classdict__s@rrrKs`  WU^WU^D k7<+@A {GL,AB ! x8#E % x8'E  ugh.?A $ wx'8&: +|X!F +|WX=N!O k<B +wu~wu~!%.'%.: k<%h/1c3KlJ*2$$ ##(LrrcJa]tRt^toRtRtRtRtRtRt Rt Rt Vt R #) CompilationUnitc\4Vn\4VnVPP \ VP44pVPP VR4R#)zFailed to create CUN)rr,rq_handlerrrU)rErYs& rrGCompilationUnit.__init__sFf #~ kk++E$,,,?@ %:;rc\4pVP\VP44pVP VRRR7R#)zFailed to destroy CUT)rfN)rrrrzrU)rEr,rYs& r__del__CompilationUnit.__del__s8''dll(;<3 6TBrc VPPVPV\V4R4pVPP VR4R#)z Add a module level NVVM IR to a compilation unit. - The buffer should contain an NVVM module IR either in the bitcode representation (LLVM3.0) or in the text representation. 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For documentation on NVVM compilation options, see the CUDA Toolkit Documentation: https://docs.nvidia.com/cuda/libnvvm-api/index.html#_CPPv418nvvmCompileProgram11nvvmProgramiPPKc cVPRR4pVfRV 2#\V\4'd \V4pRV RV 2#)_-=)replace isinstanceboolint)kvs&&rstringify_option1CompilationUnit.compile..stringify_optionsJ #s#Ay1#w!T""Fqc1#; rutf8zFailed to verify zFailed to compile z&Failed to get size of compiled result.zFailed to get compiled result.)category:NNN)r/rrencoder,r$rz _try_errorrrrrrrVr get_loglogwarningswarnr ) rEoptionsrrrxc_optsrYreslen output_buffers &, rcompileCompilationUnit.compilesz( 7>mmoFoda#A)oFS\)6=-?6=.6ahhv6F-G6=-?@kk++DLL#g,O 12kk,,T\\3w<P 23kk33DLL%-P EF&,,.1 kk// mL =><<> 888 MM$(([ 9Q7G-?s G(#G.cfVPPW: RVP4: 24R#) N)r,rUr)rErYrhs&&&rrCompilationUnit._try_error%s! dlln%EFrc\4pVPPVP\ V44pVPP VR4VP ^8dz\VP ,!4pVPPVPV4pVPP VR4VP PR4#R#)z#Failed to get compilation log size.zFailed to get compilation log.r) rr,r!rzrrUrVrr"decode)rErrYlogbufs& rrCompilationUnit.get_log(skk// eFmL %JK <=%d.%d))rrRr enumerate)myccrRrhirs& rfind_closest_archrwsF((M Qs##=) :I YAv+.2i9&s++%U++*  rc\P'd\PpRV,#\W34pRV,#)z1Matches with the closest architecture option z compute_%d%d)r FORCE_CUDA_CCr)rWrXarchs&& rget_arch_optionrsA## D  !%0 D  raNMissing libdevice file. Please ensure you have a CUDA Toolkit 11.2 or higher. For CUDA 12, ``cuda-nvcc`` and ``cuda-nvrtc`` are required: $ conda install -c conda-forge cuda-nvcc cuda-nvrtc "cuda-version>=12.0" For CUDA 11, ``cudatoolkit`` is required: $ conda install -c conda-forge cudatoolkit "cuda-version>=11.2,<12.0" c0a]tRtRtoRtRtRtRtVtR#) LibDeviceiNcVPf+\4f\\4h\ 4VnVPVnR#rQ)_cache_r RuntimeErrorMISSING_LIBDEVICE_FILE_MSGrbcrMs&rrGLibDevice.__init__s5 << &"#=>>)+DL,,rcVP#rQ)rrMs&rget LibDevice.gets wwr)rr) rkrlrmrnrrGrrsrtrus@rrrsGrrz %cas_success = cmpxchg volatile {Ti}* %iptr, {Ti} %old, {Ti} %new monotonic monotonic %cas = extractvalue {{ {Ti}, i1 }} %cas_success, 0 a define internal {T} @___numba_atomic_{T}_{FUNC}({T}* %ptr, {T} %val) alwaysinline {{ entry: %iptr = bitcast {T}* %ptr to {Ti}* %old2 = load volatile {Ti}, {Ti}* %iptr br label %attempt attempt: %old = phi {Ti} [ %old2, %entry ], [ %cas, %attempt ] %dold = bitcast {Ti} %old to {T} %dnew = {OP} {T} %dold, %val %new = bitcast {T} %dnew to {Ti} {CAS} %repeat = icmp ne {Ti} %cas, %old br i1 %repeat, label %attempt, label %done done: %result = bitcast {Ti} %old to {T} ret {T} %result }} a define internal {T} @___numba_atomic_{Tu}_inc({T}* %iptr, {T} %val) alwaysinline {{ entry: %old2 = load volatile {T}, {T}* %iptr br label %attempt attempt: %old = phi {T} [ %old2, %entry ], [ %cas, %attempt ] %bndchk = icmp ult {T} %old, %val %inc = add {T} %old, 1 %new = select i1 %bndchk, {T} %inc, {T} 0 {CAS} %repeat = icmp ne {T} %cas, %old br i1 %repeat, label %attempt, label %done done: ret {T} %old }} a define internal {T} @___numba_atomic_{Tu}_dec({T}* %iptr, {T} %val) alwaysinline {{ entry: %old2 = load volatile {T}, {T}* %iptr br label %attempt attempt: %old = phi {T} [ %old2, %entry ], [ %cas, %attempt ] %dec = add {T} %old, -1 %bndchk = icmp ult {T} %dec, %val %new = select i1 %bndchk, {T} %dec, {T} %val {CAS} %repeat = icmp ne {T} %cas, %old br i1 %repeat, label %attempt, label %done done: ret {T} %old }} a define internal {T} @___numba_atomic_{T}_{NAN}{FUNC}({T}* %ptr, {T} %val) alwaysinline {{ entry: %ptrval = load volatile {T}, {T}* %ptr ; Return early when: ; - For nanmin / nanmax when val is a NaN ; - For min / max when val or ptr is a NaN %early_return = fcmp uno {T} %val, %{PTR_OR_VAL}val br i1 %early_return, label %done, label %lt_check lt_check: %dold = phi {T} [ %ptrval, %entry ], [ %dcas, %attempt ] ; Continue attempts if dold less or greater than val (depending on whether min or max) ; or if dold is NaN (for nanmin / nanmax) %cmp = fcmp {OP} {T} %dold, %val br i1 %cmp, label %attempt, label %done attempt: ; Attempt to swap in the value %old = bitcast {T} %dold to {Ti} %iptr = bitcast {T}* %ptr to {Ti}* %new = bitcast {T} %val to {Ti} {CAS} %dcas = bitcast {Ti} %cas to {T} br label %lt_check done: ret {T} %ptrval }} c.\PVR7#)Ti)cas_nvvmformatrs&rir_casr#s ??b? !!rc \\WW#\V4R7p\P!R/VB#))TrOPFUNCCASr)dictrir_numba_atomic_binary_templater)rrrrparamss&&&& rir_numba_atomic_binaryr's( AF2J ?F * 1 1 ;F ;;rc `\WW#VV\V4R7p\P!R/VB#))rrNANr PTR_OR_VALrrr)rrir_numba_atomic_minmax_templater)rrrrrrrs&&&&&& rir_numba_atomic_minmaxr,s1 A#-F + 1 1 ;F ;;rcB\PW\V4R7#)rTur)ir_numba_atomic_inc_templaterrrrs&&rir_numba_atomic_incr3 ' . .vay . IIrcB\PW\V4R7#r)ir_numba_atomic_dec_templaterrrs&&rir_numba_atomic_decr7rrcR\RRRRR73R\RRR R R73R \RRR R R73R \RR R73R\RR R73R\RRRRRRR73R\RRRRRRR73R\RRRRRRR73R\RRRRRRR73R\RRRRRRR73R\RRRRRRR73R\RRRR RRR73R!\RRRR RRR73R".pVFwr#VP W#4pK \ V4pV#)#zIdeclare double @"___numba_atomic_double_add"(double* %".1", double %".2")doublei64faddadd)rrrrzEdeclare float @"___numba_atomic_float_sub"(float* %".1", float %".2")floati32fsubsubzIdeclare double @"___numba_atomic_double_sub"(double* %".1", double %".2")z=declare i64 @"___numba_atomic_u64_inc"(i64* %".1", i64 %".2")u64rz=declare i64 @"___numba_atomic_u64_dec"(i64* %".1", i64 %".2")zEdeclare float @"___numba_atomic_float_max"(float* %".1", float %".2")rznnan oltptrmax)rrrrrrzIdeclare double @"___numba_atomic_double_max"(double* %".1", double %".2")zEdeclare float @"___numba_atomic_float_min"(float* %".1", float %".2")znnan ogtrzIdeclare double @"___numba_atomic_double_min"(double* %".1", double %".2")zHdeclare float @"___numba_atomic_float_nanmax"(float* %".1", float %".2")nanultzLdeclare double @"___numba_atomic_double_nanmax"(double* %".1", double %".2")zHdeclare float @"___numba_atomic_float_nanmin"(float* %".1", float %".2")ugtzLdeclare double @"___numba_atomic_double_nanmin"(double* %".1", double %".2"))immargr)rrrrrllvm140_to_70_ir)llvmir replacementsdeclfns& r llvm_replacer ;s T (ue L N P 'eU K M T (ue L N H u / 1 H u / 1 P 'e +0u > ? U (u"+0u > ? Q 'e +0u > ? U (u"+0u > ? T 'e5+-E ; < X (u%E+-E ; < T 'e5+-E ; < X (u%E+-E ; < G$LL!)!f %F Mrc \V\4'dV.pVPRR4'dVPRRRRRRRR/4\ 4p\ 4pVF.p\ V4pVPVPR44K0 VPVP44VP!R/VB#) fastmathFftzTfmaprec_div prec_sqrtrr) rstrpopupdaterxrr rrrrr)roptscu libdevicemods&, r compile_irrjs&# xx E"" 4 4       B I3 cjj()y}}' ::  rz"^attributes #\d+ = \{ ([\w\s]+)\ }c.pVP!4FpVPR4'dn\PV4pVP ^4P 4pRP RV44pVPVP ^4V4pVPV4K RP V4#)z$ Convert LLVM 14.0 IR for LLVM 7.0. z attributes # c36"TFqR8wgK VxK R#5i) willreturnNr).0as& r #llvm140_to_70_ir..sC1l1BQQs r) splitlines startswithre_attributes_defmatchgroupsplitjoinrappend)r buflinemattrss& rrrs C  ??> * *!''-AGGAJ$$&EHHCCCE<< E2D 4  99S>rchVPp\P!VR4p\P!\P!^ 4^4pVP WV34p\ P!VR4pVPV4\P!^4P4p\P!V^4pVPV4p\P!WR4p RV n RV n\P!Wx.4V nVP P#R4R#)aD Mark a function as a CUDA kernel. Kernels have the following requirements: - Metadata that marks them as a kernel. - Addition to the @llvm.used list, so that they will not be discarded. - The noinline attribute is not permitted, because this causes NVVM to emit a warning, which counts as failing IR verification. Presently it is assumed that there is one kernel per module, which holds for Numba-jitted functions. If this changes in future or this function is to be used externally, this function may need modification to add to the @llvm.used list rather than creating it. kernelznvvm.annotationsz llvm.used appendingz llvm.metadatanoinlineN)moduler MetaDataStringConstantIntType add_metadatarget_or_insert_named_metadatar as_pointer ArrayTypebitcastGlobalVariablelinkagesection initializer attributesdiscard) functionr1mdstrmdvaluemdnmdptrtyusedtyfnptr llvm_useds & rset_cuda_kernelrIs__F   fh /Ekk"**R.!,G   hw7 8B  . .v7I JCGGBK JJqM $ $ &E \\% #F   U #E!!&+>I#I'IKK8I  +rc\P!^ 4p\4P4Uu.uF q!!V4NK ppVP V4pVP RV4R#uupi)zAdd NVVM IR version to moduleznvvmir.versionN)r r4rr>r5add_named_metadata)rrrrFmd_vers& radd_ir_versionrMs\ **R.C#'6#8#8#:;#:a3q6#:K;   k *F+V4rls ;;==&   8 $    EG ' (DAq CKK !1a( ) ;7 ^^  {6{|kfk\              <2D!    #, ( (#@"< <JJ,^.JJDE$$,N5r