Ei=MSSKrSSKrSSKJr SSKrSSKJr S\R4Sjr S\R4Sjr S\R4Sjr S\ SS4S jr S\R4S jrS\R4S jrS\R4S jrS\\4S jrS S\S\S\S-S\S-S\S-S\S\\\44Sjjr"SS5r"SS5rS!S\\-S\\S-S\\\S4-4SjjrS"S\S\S\S\ 4Sjjrg)#N)Any)_get_device_indexreturnc SSKn[R"[UR S5S55nURUl URUlUR UlUR$UlUR(UlU$![ [ 4ad [RS:Xa7[R"S[RRSS35nN[R"S5nNf=f)Nramdhip64win32 amdhip64_.dllzlibamdhip64.so)rocm_sdkctypesCDLLstrfind_libraries ImportError IndexErrorsysplatformtorchversionhiphipGetErrorStringcuGetErrorStringhipModuleLoadDatacuModuleLoadDatahipModuleGetFunctioncuModuleGetFunctionhipModuleLaunchKernelcuLaunchKernelhipFuncSetAttributecuFuncSetAttribute)r libs N/home/mande/repo/quber/.venv/lib/python3.13/site-packages/torch/cuda/_utils.py_get_hip_runtime_libraryr# s 0kk#h55jA!DEF00C00C!66C22C 44C J  $0 <<7 "++ %--*;*;A*>)?tDEC++./C 0s5BAD)DDc[RS:Xa[R"S5$[R"S5$)Nrz nvcuda.dllz libcuda.so.1)rrr r r"_get_cuda_libraryr'"s, ||w{{<(({{>**r&ch[RR(a [5$[ 5$N)rrrr#r'r%r&r"_get_gpu_runtime_libraryr**s! }}')) ""r&resultcUS:Xag[R"5n[5nURU[R"U55 UR bUR R 5OSn[SU35e)NrUnknown CUDA error CUDA error: )r c_char_pr*rbyrefvaluedecode RuntimeError)r+err_strlibcuda error_messages r" _check_cudar72sn {ooG&(G VV\\'%:;")--"; AU m_5 66r&cSSKn[R"[UR S5S55nURUlURUlUR"UlUR&UlUR*UlUR.UlUR2UlUR6UlUR:UlUR>Ul U$![ [ 4a [RS:XahSRS[RRSS[RRS/5n[R"SUS35nGN8[R"S5nGNQf=f) Nrhiprtcr0r z libhiprtc.so)!r r r rrrrrrjoinrrrhiprtcGetErrorStringnvrtcGetErrorStringhiprtcCreateProgramnvrtcCreateProgramhiprtcDestroyProgramnvrtcDestroyProgramhiprtcCompileProgramnvrtcCompileProgramhiprtcGetCodeSizenvrtcGetCUBINSize hiprtcGetCode nvrtcGetCUBINhiprtcGetProgramLogSizenvrtcGetProgramLogSizehiprtcGetProgramLognvrtcGetProgramLoghiprtcAddNameExpressionnvrtcAddNameExpressionhiprtcGetLoweredNamenvrtcGetLoweredName)r r! version_strs r"_get_hiprtc_libraryrS>sA .kk#h55h?BCD"66C 44C!66C!66C11C))C!$!UT:war[R"5nTRU[R"U55 URbURR 5OSn[ SU35eg)Nr-r.)r r/r?r0r1r2r3)r+r4r6 NVRTC_SUCCESSlibnvrtcs r" check_nvrtc#_nvrtc_compile..check_nvrtcso ] "oo'G  ( (g1F G==, $$&)  m_=> > #r&utf-8z--offload-arch=z--gpu-architecture=sm_) include_pathsrXz-Iz12.8zPCH requires CUDA 12.8+, got z--pchz.cuzKernel compilation failed: r:)' torch.cudar`rWencoderXget_device_propertiescurrent_devicerr gcnArchNamemajorminorappendrdrwrAssertionErrorrirelenr r/c_void_prAr0rOrEc_size_trKcreate_string_bufferr1rMr3r2rGrIrQrCraw)rjrkrlrmrnrorrt source_bytespropsoptionsrwcuda_include_paths cuda_path directoryoptionnvrtc_compatible_flagsrg num_options options_arrayprog c_kernel_namereslog_sizelog binary_sizebinaryc_mangled_name mangled_namerrrss @@r"_nvrtc_compilers0$%HM ?C ?D ? ?!''0L! 001J1J1LM ==  $)$5$5#6 $)KK= !> G }});(<=DDFG/0B/CDKKMN8&v.' 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D## LL  m3  & & (      &&w/M//mDE  & &t[- HC m??$''fll8.DE))(..9##D#.9#)):J:J:L9MNOO//#K**4k1JKL  ( ():): ;F&&tV45__&N$$T=&,,~:VW'%++224     d!34 ::| ##oMs&R,cL\rSrSrS\R SS4SjrS\SS4SjrS r g) _CudaModulei!modulerNcXl0Ulgr))_module_kernels)selfrs r"__init___CudaModule.__init__"s 02 r&name _CudaKernelc XR;aURU$SSKJn U"5n[R"5n[ UR [R"U5URURS555 [X@R5nXPRU'U$![an[SUS35UeSnAff=f)Nr)r*rvzNo kernel named 'z' in this module) rtorch.cuda._utilsr*r rr7rr0rryrr3AttributeError)rrr*r5funckernelerrs r" __getattr___CudaModule.__getattr__&s == ==& & ?*,  V ++LL& dkk'6J  !||4F"(MM$ M V #4TF:J!KLRU U VsA-B00 C:C  C)rr) __name__ __module__ __qualname____firstlineno__r rrrr__static_attributes__r%r&r"rr!s/3v343VV Vr&rc \rSrSrSrS\R S\R SS4SjrSS\\ \ \ 4S \\ \ \ 4S \ S-S \ S \ S-SS4 S jjr S\ SS4Sjr Srg)ri?zL Represents a compiled CUDA kernel that can be called with PyTorch tensors. rrrNc*XlX lSUlg)Nr)rr_max_shared_mem_bytes)rrrs r"r_CudaKernel.__init__Ds  %&"r&gridblockargs shared_memstreamcSSKnURRR5nU(d/n/n/n UGHvn [ XR 5(aU R (d1U R(aU R5(d [S5e[R"U R55n URU 5 U R[R"U 55 M[ U [5(a>[R "U 5n U R[R"U 55 GM[ U ["5(a>[R$"U 5n U R[R"U 55 GMb['S[)U 535e [R[+U 5-"5n[-U 5H,up[R."U [R5X'M. 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Call kernel.set_shared_memory_config(shared_mem) after compilation and before launching the kernel.r<) rrX_utilsr* isinstanceTensoris_cudais_cpu is_pinned ValueErrorr rdata_ptrrr0rWc_intfloatc_double TypeErrortyper enumeratecastrxcurrent_streamrr3r7rr_as_parameter_)rrrrrrrr5processed_argsc_argsargptrrr c_args_arrayiconfigured_msgs r"__call___CudaKernel.__call__IsT& **##<<>D13C#||,,{{CJJ3==??$Yooclln5%%c* fll3/0C%% S) fll512C''!??3/ fll845"=d3i[ IJJ+0#f+58 'FA$kk#v?LO( > ZZ..0F  "  & &! +z!!/ 01GG 783  & & ;   &6"r&)rrr)rrrrNrN)rrrr__doc__r rrtuplerWlistrrrrr%r&r"rr?s'V__'foo'$'&/&/ ! _ CcM"_ S#s]#_ Tk _  _ d _  _ B(6(6(6r&rptx kernel_namesc \SSKn[5n[U[5(aUR S5n[ R "5nURR5nU [UR[ R"U5U55 SSS5 U(d [U5$0nUHcn[ R "5n[UR[ R"U5XGR S555 [X5Xg'Me U$!,(df  N=f)a Loads a CUDA module from PTX code and returns a module object that can access kernels. Args: ptx (bytes or str): The PTX code to load kernel_names (list, optional): List of kernel names to extract from the module. 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If :attr:`device` is a Python integer, it is returned as is. If :attr:`device` is ``None``, this will return the current default CUDA device if :attr:`optional` is ``True``. )rXcpuz(Expected a cuda or cpu device, but got: rXz!Expected a cuda device, but got: ) rrWrrrrrjit is_scriptingrXidx_torch_get_device_index)rrrs r"rrs &# &#f%&%,,'' {{/1 #KF8!TUU2 [[F "@IJ J 99 ! ! # # fejj// 0 0::  "6Y ??r&)NNNFr))FF)r rtypingrr torch._utilsrrr r#r'r*rWr7rSr^r`rrriboolrbytesrrrdictrr%r&r"rs  F&++.+6;;+#&++# 7 7 7V[[:6FKK6&$fkk$tCy6&*%) $ O$O$O$d O$d{ O$ + O$  O$ 5#:O$dVV