0ViL SSKrSSKrSSKJrJrJr SSKrSSKJr S\R4Sjr S\R4Sjr S\R4Sjr S\SS4S jrS\R4S jrS\R4S jrS\R4S jrS\\4S jrS S\S\S\\S\\S\\S\S\\\44Sjjr"SS5r"SS5rS!S\\\4S\\\S\\\\S444SjjrS"S\S\S\S\4Sjjrg)#N)AnyOptionalUnion)_get_device_indexreturncp[RS:Xa6[R"S[R R SS35nO[R"S5nURUlURUl URUl URUlURUlU$)Nwin32 amdhip64_r.dllzlibamdhip64.so)sysplatformctypesCDLLtorchversionhiphipGetErrorStringcuGetErrorStringhipModuleLoadDatacuModuleLoadDatahipModuleGetFunctioncuModuleGetFunctionhipModuleLaunchKernelcuLaunchKernelhipFuncSetAttributecuFuncSetAttribute)libs VD:\a\ltx-desktop-ci\ltx-desktop-ci\python-embed\Lib\site-packages\torch\cuda\_utils.py_get_hip_runtime_libraryr s ||wkkIemm&7&7&:%;4@Akk*+00C00C!66C22C 44C Jc[RS:Xa[R"S5$[R"S5$)Nr z nvcuda.dllz libcuda.so.1)r r rrr r_get_cuda_libraryr#s, ||w{{<(({{>**r ch[RR(a [5$[ 5$N)rrrrr#r"r r_get_gpu_runtime_libraryr& s! }}')) ""r resultcUS:Xag[R"5n[5nURU[R"U55 UR bUR R 5OSn[SU35e)NrUnknown CUDA error CUDA error: )rc_char_pr&rbyrefvaluedecode RuntimeError)r'err_strlibcuda error_messages r _check_cudar3(sn {ooG&(G VV\\'%:;")--"; AU m_5 66r cz[RS:XafSRS[RR SS[RR S/5n[ R"SUS35nO[ R"S5nURUl URUl URUl URUlUR UlUR$UlUR(UlUR,UlUR0UlUR4UlU$) Nr 0rhiprtcr z libhiprtc.so)r r joinrrrrrhiprtcGetErrorStringnvrtcGetErrorStringhiprtcCreateProgramnvrtcCreateProgramhiprtcDestroyProgramnvrtcDestroyProgramhiprtcCompileProgramnvrtcCompileProgramhiprtcGetCodeSizenvrtcGetPTXSize hiprtcGetCode nvrtcGetPTXhiprtcGetProgramLogSizenvrtcGetProgramLogSizehiprtcGetProgramLognvrtcGetProgramLoghiprtcAddNameExpressionnvrtcAddNameExpressionhiprtcGetLoweredNamenvrtcGetLoweredName) version_strrs r_get_hiprtc_libraryrO4s ||wggsEMM$5$5a$8#u}}?P?PQR?STU kkF;-t45kk.)"66C 44C!66C!66C//C''CO!$!UT:war[R"5nTRU[R"U55 URbURR 5OSn[ SU35eg)Nr)r*)rr+r;r,r-r.r/)r'r0r2 NVRTC_SUCCESSlibnvrtcs r check_nvrtc#_nvrtc_compile..check_nvrtcso ] "oo'G  ( (g1F G==, $$&)  m_=> > #r utf-8z--offload-arch=z--gpu-architecture=sm_) include_pathsrTz-Iz12.8zPCH requires CUDA 12.8+z--pchz.cuzKernel compilation failed: r5)& torch.cudar\rSencoderTget_device_propertiescurrent_devicerr gcnArchNamemajorminorappendr`rsstrreralenrr+c_void_pr=r,rKrAc_size_trGcreate_string_bufferr-rIr/r.rCrErMr?raw) rfrgrhrirjrkrrp source_bytespropsoptionsrscuda_include_paths cuda_path directoryoptionnvrtc_compatible_flagsrc num_options options_arrayprog c_kernel_namereslog_sizelogptx_sizeptxc_mangled_name mangled_name ptx_bytesrnros @@r_nvrtc_compiler}s0$%HM ?C ?D ? ?!''0L! 001J1J1LM ==  $)$5$5#6 $)KK= !> G }});(<=DDFG/0B/CDKKMN8&v.' I;'..01(*I NNR {+224 5+5==%%&&0K2KK0  LG$"F NN6==1 2#;< NN5KL5KTDKK(5KLMg,K__{2W=M ?? D## LL  m3  & & (      &&w/M//mDE  & &t[- HC m??$''fll8.DE))(..9##D#.9#)):J:J:L9MNOO H((v||H/EFG  % %hnn 5C$$T3/0__&N$$T=&,,~:VW'%++224     d!34 !==,,#))I l ""sMs R:cL\rSrSrS\R SS4SjrS\SS4SjrS r g) _CudaModuleimodulerNcXl0Ulgr%)_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&rrzNo kernel named 'z' in this module) rtorch.cuda._utilsr&rr~r3rr,rrurr/AttributeError)rrr&r1funckernelerrs 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__rr~rr|r__static_attributes__r"r rrrs/3v343VV Vr rc \rSrSrSrS\R S\R SS4SjrSS\\ \ \ 4S \\ \ \ 4S \ \ S \ S \ \ SS4 S jjr S\ SS4SjrSrg)ri.zL Represents a compiled CUDA kernel that can be called with PyTorch tensors. rrrNc*XlX lSUlg)Nr)rr_max_shared_mem_bytes)rrrs rr_CudaKernel.__init__3s  %&"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$"U 5n U R[R"U 55 GMb['S[)U 535e [R[+U 5-"5n[-U 5H,up[R."U [R5X'M. UcSSKnURR35nUS:aSUR4S:XdX@R4:a4UR4S:XaSOSUR4S3n[7S US US 35e[9UR;UR<USUS US USUS US UUR>US5 5 g)a Call the compiled CUDA kernel Args: grid (tuple): Grid dimensions (grid_x, grid_y, grid_z) block (tuple): Block dimensions (block_x, block_y, block_z) args (list): List of arguments to pass to the kernel. PyTorch tensor arguments will be automatically converted to pointers. shared_mem (int): Shared memory size in bytes stream (torch.cuda.Stream): CUDA stream to use. If None, uses current stream. rNz?All tensor arguments must be CUDA tensors or pinned CPU tensorszUnsupported argument type: znot configuredzonly z bytes configuredzKernel requires z' bytes of shared memory (>= 48KB), but ze. Call kernel.set_shared_memory_config(shared_mem) after compilation and before launching the kernel.r7) rrT_utilsr& isinstanceTensoris_cudais_cpu is_pinned ValueErrorrr~data_ptrr{r,rSc_intfloatc_double TypeErrortyper} enumeratecastrtcurrent_streamrr/r3rr_as_parameter_)rrrrrrrr1processed_argsc_argsargptrrr c_args_arrayiconfigured_msgs r__call___CudaKernel.__call__8sT& **##<<>D13C#||,,{{CJJ3==??$Yooclln5%%c* fll3/0C%% S) fll512C''!??3/ fll845"=d3i[ IJJ+0#f+58 'FA$kk#v?LO( > ZZ..0F  "  & &! +z!!/ 01GG 783  & & ;   &6"r )rrr)rrrrNrN)rrrr__doc__rr~rtuplerSrlistrrrrr"r rrr.s'V__'foo'$'&/&/# $ _ CcM"_ S#s]#_ tn _  _  _  _ B(6(6(6r rr 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. If None, will return a module object with __getattr__. Returns: object: If kernel_names is None, returns a module object with __getattr__ to access kernels. If kernel_names is provided, returns a dict mapping kernel names to _CudaKernel objects. rNrr)rtr&rr|rurr~rTrr3rr,rrr) rrrr1rrkernelsrrs r_cuda_load_modulers '(G#sjj!__ F ZZ & & (F G,,V\\&-A3GH  6""G   ' ' T"FKK,@  $D1  N! s &0D D+deviceoptional allow_cpuc[U[5(aU$[U[5(a[R"U5n[U[R5(aDU(aUR S;a[ SU35eOUR S:wa[ SU35e[RR5(d5[U[RR5(a UR$[XU5$)aGet the device index from :attr:`device`, which can be a torch.device object, a Python integer, or ``None``. If :attr:`device` is a torch.device object, returns the device index if it is a CUDA device. Note that for a CUDA device without a specified index, i.e., ``torch.device('cuda')``, this will return the current default CUDA device if :attr:`optional` is ``True``. If :attr:`allow_cpu` is ``True``, CPU devices will be accepted and ``-1`` will be returned in this case. 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``. )rTcpuz(Expected a cuda or cpu device, but got: rTz!Expected a cuda device, but got: ) rrSr|rrrrjit is_scriptingrTidx_torch_get_device_index)rrrs rrrs &# &#f%&%,,'' {{/1 #KF8!TUU2 [[F "@IJ J 99 ! ! # # fejj// 0 0::  "6Y ??r )NNNFr%)FF)rr typingrrrr torch._utilsrrrrr#r&rSr3rOrZr\rr|reboolrbytesrrrdictrr"r rrs '' F &++ +6;;+#&++# 7 7 7V[[*6FKK6&$fkk$tCy6)-(,#' P#P#P#! P# ~ P# 4. P#  P# 5#:P#fVV