§ `ƒiÇ$ãóü—ddlZddlZddlZddlZddlZddlZd„Ze¦«rdndZejee ¬¦«Z gd¢ZeD]Ze e e¦«e¦«e<ŒddlmZmZd Zejd d dejddfd „Zejfd„Zee j_ee_d„Z dd„Z dd„Zee_ee_ d„Z!d„Z"e¦«re!¦«n e"¦«ddl#m#Z#m$Z$m%Z%ddl&m'Z'ddl(m)Z)de*de)fd„Z+dS)éNcó@—tj d¦«S)NÚwin)ÚsysÚplatformÚ startswith©óúb/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/cudnn/__init__.pyÚ is_windowsr s€ÝŒ<×"Ò" 5Ñ)Ô)Ð)r z.Release._compiled_modulez._compiled_module)Úpackage)Úbackend_versionÚbackend_version_stringÚget_last_error_stringÚdestroy_handleÚnorm_forward_phaseÚreduction_modeÚ behavior_noteÚ knob_typeÚ create_handleÚcreate_kernel_cacheÚcreate_device_propertiesÚ get_streamÚnumerical_noteÚ set_streamÚbuild_plan_policyÚ data_typeÚtensor_reorderingÚ heur_modeÚpygraphÚtensorÚknobÚcudnnGraphNotSupportedErrorÚdiagonal_alignmentÚattention_implementationé)Ú _library_typeÚ_is_torch_tensorz1.18.0FÚéÿÿÿÿc óX—| ||t|¦«|||||| ¬¦ « S)ag Create a tensor. Args: dim (List[int]): The dimensions of the tensor. stride (List[int]): The strides of the tensor. data_type (cudnn.data_type): The data type of the tensor. is_virtual (bool): Flag indicating if the tensor is virtual. is_pass_by_value (bool): Flag indicating if the tensor is passed by value. ragged_offset (cudnn_tensor): The ragged offset tensor. reordering_type (cudnn.tensor_reordering): The reordering type of the tensor. name (str): The name of the tensor. Returns: cudnn_tensor: The created tensor. ) ÚdimÚstriderÚ is_virtualÚis_pass_by_valueÚ ragged_offsetÚreordering_typeÚnameÚuid)Ú_make_tensorr&) Úselfr+r,rr-r.r/r0r1r2s r Ú_tensorr54sD€ð8×ÒØØÝ Ñ*Ô*ØØ)Ø#Ø'Ø Øðñ ô ð r cóF—| t|¦«¦«S©N)Ú_set_data_typer&)r4rs r r8r8]s €ð×Ò}¨YÑ7Ô7Ñ8Ô8Ð8r có¬—t|¦«tur|St|¦«r| ¦«St |¦«Sr7)ÚtypeÚintr'Údata_ptrÚ_pybind_moduleÚ _get_data_ptr)Úinput_tensors r Ú_library_device_pointerr@hsS€åˆLÑÔSÐ Ð ØÐå ˜,Ñ 'Ô 'ð:Ø×$Ò$Ñ&Ô&Ð&õ×+Ò+¨LÑ9Ô9Ð9r cóŽ—d„| ¦«D¦«}t|¦«}| |||¦«dS)aQ Execute a cudnn graph. Args: tensor_to_device_buffer (dict(cudnn_tensor, Union[torch.Tensor, int, __dlpack__])): The dimensions of the tensor. workspace (Union[torch.Tensor, int, __dlpack__]): The name of the tensor. handle: cudnn_handle created with cudnn.create_handle() Returns: None cóŒ—i|]A\}}|®t|¦«tur|n| ¦«t|¦«“ŒBSr7©r:r;Úget_uidr@©Ú.0ÚxÚpointers r ú z_execute..‡ód€ðððÙS]ÐSTÐV]ðEFðERT!‰WŒWˆ^ˆ^ˆˆ §¢¡¤Õ.EÀgÑ.NÔ.NðERðERðERr N)Úitemsr@Ú_execute) r4Útensor_to_device_bufferÚ workspaceÚhandleÚ override_uidsÚoverride_shapesÚoverride_stridesÚuid_to_tensor_pointerÚworkspace_pointers r rLrLtsc€ð&ðØax×a~Òa~ñbAôbAðñôÐõ0° Ñ:Ô:ÐØ‡M‚MÐ'Ð):¸FÑCÔCÐCÐCÐCr c ó–—d„| ¦«D¦«}t|¦«} | || |||||¦«dS)aˆ Execute a cudnn graph. Args: tensor_to_device_buffer (dict(cudnn_tensor, Union[torch.Tensor, int, __dlpack__])): The dimensions of the tensor. workspace (Union[torch.Tensor, int, __dlpack__]): The name of the tensor. index(int): Location of execution plan to use. handle: cudnn_handle created with cudnn.create_handle() Returns: None cóŒ—i|]A\}}|®t|¦«tur|n| ¦«t|¦«“ŒBSr7rCrEs r rIz*_execute_plan_at_index..¤rJr N)rKr@Ú_execute_plan_at_index) r4rMrNÚindexrOrPrQrRrSrTs r rWrWs|€ð*ðØax×a~Òa~ñbAôbAðñôÐõ0° Ñ:Ô:ÐØ×ÒØØØ ØØØØñôðððr cóþ—tjtj t jd¦«d¦«¦«}|rTt |¦«dksJdt |¦«›d¦«‚tj |d¦«}ntj d¦«}tj |jtj¦«j }t |¦«dS)NÚpurelibznvidia/cudnn/bin/cudnn64_9.dllr%úFound z% libcudnn.dll.x in nvidia-cudnn-cuXX.rz cudnn64_9.dll)ÚglobÚosÚpathÚjoinÚ sysconfigÚget_pathÚlenÚctypesÚwindllÚLoadLibraryÚcastÚ_handleÚc_void_pÚvaluer=Ú_set_dlhandle_cudnn©Úlib_pathÚlibrOs r Ú load_cudnnrn¸sÈ€åŒyœŸš¥iÔ&8¸Ñ&CÔ&CÐEeÑfÔfÑgÔg€Hàð9Ý8‰}Œ} Ò!Ð!Ð!Ð#`C°©M¬MÐ#`Ð#`Ð#`Ñ!Ô!Ð!ÝŒm×'Ò'¨°¬Ñ4Ô4ˆˆåŒm×'Ò'¨Ñ8Ô8ˆå Œ[˜œ¥f¤oÑ 6Ô 6Ô <€FÝ×&Ò& vÑ.Ô.Ð.Ð.Ð.r cóÚ—tjtj t jd¦«d¦«¦«}|sDtjtj t jd¦«d¦«¦«}|rIt |¦«dksJdt |¦«›d¦«‚tj|d¦«}nN tjd¦«}n8#t$r+ tjd ¦«}n#t$rd}YnwxYwYnwxYw|Etj |jtj¦«j }t |¦«dSdS) NrZz#nvidia/cudnn/lib/libcudnn.so.*[0-9]z'nvidia/cudnn_jit/lib/libcudnn.so.*[0-9]r%r[z$ libcudnn.so.x in nvidia-cudnn-cuXX.rz libcudnn.so.9zlibcudnn.so)r\r]r^r_r`rarbrcÚCDLLÚ Exceptionrfrgrhrir=rjrks r Ú _dlopen_cudnnrrÆs\€åŒyœŸš¥iÔ&8¸Ñ&CÔ&CÐEjÑkÔkÑlÔl€HàðuÝ”9RœWŸ\š\)Ô*<¸YÑ*GÔ*GÐIrÑsÔsÑtÔtˆàð Ý8‰}Œ} Ò!Ð!Ð!Ð#_C°©M¬MÐ#_Ð#_Ð#_Ñ!Ô!Ð!ÝŒk˜( 1œ+Ñ&Ô&ˆˆð Ý”+˜oÑ.Ô.ˆCˆCøÝð ð ð ð Ý”k -Ñ0Ô0øÝð ð ð Øð øøøøøð øøøð€Ý”˜Sœ[&¬/Ñ:Ô:Ô@ˆÝ×*Ò*¨6Ñ2Ô2Ð2Ð2Ð2ð€s6ÃC,Ã, D!Ã7DÄD!ÄDÄD!ÄDÄD!Ä D!)ÚgraphÚjitÚgraph_cache)ÚGraph)ÚAnyr1Úreturncó`—|dkr. ddlm}|S#t$r}td|›¦«|‚d}~wwxYw|dkr. ddlm}|S#t$r}td|›¦«|‚d}~wwxYw|dkr. dd lm}|S#t$r}td |›¦«|‚d}~wwxYw|dkr. ddlm}|S#t$r}td |›¦«|‚d}~wwxYw|dkr. ddlm }|S#t$r}td|›¦«|‚d}~wwxYw|dkr. ddl m}|S#t$r}td|›¦«|‚d}~wwxYw|dkr. ddlm}|S#t$r}td|›¦«|‚d}~wwxYw|dkr. ddlm } | S#t$r}td|›¦«|‚d}~wwxYwt|¦«‚)NÚNSAr%)rzz_NSA requires optional dependencies. Install with 'pip install nvidia-cudnn-frontend[cutedsl]': ÚGemmSwigluSm100)r{zkGemmSwigluSm100 requires optional dependencies. Install with 'pip install nvidia-cudnn-frontend[cutedsl]': Úgemm_swiglu_wrapper_sm100)r|zugemm_swiglu_wrapper_sm100 requires optional dependencies. Install with 'pip install nvidia-cudnn-frontend[cutedsl]': Ú GemmAmaxSm100)r}ziGemmAmaxSm100 requires optional dependencies. Install with 'pip install nvidia-cudnn-frontend[cutedsl]': Úgemm_amax_wrapper_sm100)r~zsgemm_amax_wrapper_sm100 requires optional dependencies. Install with 'pip install nvidia-cudnn-frontend[cutedsl]': Úgrouped_gemm)rzhgrouped_gemm requires optional dependencies. Install with 'pip install nvidia-cudnn-frontend[cutedsl]': ÚGroupedGemmSwigluSm100)r€zrGroupedGemmSwigluSm100 requires optional dependencies. Install with 'pip install nvidia-cudnn-frontend[cutedsl]': Ú!grouped_gemm_swiglu_wrapper_sm100)rz}grouped_gemm_swiglu_wrapper_sm100 requires optional dependencies. Install with 'pip install nvidia-cudnn-frontend[cutedsl]': )Únative_sparse_attentionrzrqÚImportErrorÚgemm_swiglur{r|Ú gemm_amaxr}r~r(rr€rÚAttributeError) r1Ú_NSAÚeÚ_GemmSwigluSm100Ú_gemm_swiglu_wrapper_sm100Ú_GemmAmaxSm100Ú_gemm_amax_wrapper_sm100Ú _grouped_gemmÚ_GroupedGemmSwigluSm100Ú"_grouped_gemm_swiglu_wrapper_sm100s r Ú__getattr__rés<€Øˆu‚}€}ð LØ<Ð<Ð<Ð<Ð<Ð<àˆKøÝð Lð Lð LÝðDðABðDðDñEôEðKLð Løøøøð Løøøð Ð"Ò "Ð "ð XØHÐHÐHÐHÐHÐHà#Ð#øÝð Xð Xð XÝðPðMNðPðPñQôQðWXð Xøøøøð Xøøøð Ð,Ò ,Ð ,ð ð ð ð ð ð ð ð.Ð-øÝð ð ð ÝðLðIJðLðLñôàð øøøøð øøøð Ò Ð ð VØBÐBÐBÐBÐBÐBà!Ð!øÝð Vð Vð VÝðNðKLðNðNñOôOðUVð Vøøøøð Vøøøð Ð*Ò *Ð *ð `ð ð ð ð ð ð ð,Ð+øÝð `ð `ð `ÝðXðUVðXðXñYôYð_`ð `øøøøð `øøøð Ò Ð ð UØ7Ð7Ð7Ð7Ð7Ð7à Ð øÝð Uð Uð UÝðMðJKðMðMñNôNðTUð Uøøøøð Uøøøð Ð)Ò )Ð )ð _ØWÐWÐWÐWÐWÐWà*Ð*øÝð _ð _ð _ÝðWðTUðWðWñXôXð^_ð _øøøøð _øøøð Ð4Ò 4Ð 4ð ð ð ð ð ð ð ð6Ð5øÝð ð ð ÝðTðQRðTðTñôàð øøøøð øøøõ˜TÑ"Ô"Ð"s·ˆ 2š-2¼AÁ A&ÁA!Á!A&Á0A8Á8 BÂBÂBÂ$B,Â, CÂ6C Ã CÃC Ã DÃ*C=Ã=DÄDÄ D6ÄD1Ä1D6ÅEÅ E*ÅE%Å%E*Å4E<Å< FÆFÆF)NNNN),rcr\r]rr`Ú importlibrÚmodule_nameÚ import_moduleÚ__name__r=Úsymbols_to_importÚsymbol_nameÚgetattrÚglobalsÚ datatypesr&r'Ú__version__rÚNOT_SETrÚNONEr5r8r Ú set_data_typerr@rLrWÚexecuteÚexecute_plan_at_indexrnrrrsrtruÚwrapperrvÚtypingrwÚstrrrr r úr£siðØ € € € Ø€€€Ø € € € Ø € € € ØÐÐÐØÐÐÐð*ð*ð*ð.8¨Z©\¬\ÐRÐ)Ð)Ð?R€à(Ô(¨¸hÐGÑGÔG€ðððÐð6%ðBðB€KØ$˜W ^°[ÑAÔA€G€GI„IˆkÑÐà6Ð6Ð6Ð6Ð6Ð6Ð6Ð6à€ðÔØØØØ%Ô*Ø Ø ð&ð&ð&ð&ðVÔð9ð9ð9ð9ð'5€ÔÔ#Ø€„ð :ð :ð :ð ØØØðDðDðDðDð@ØØØð"ð"ð"ð"ðJ€„Ø 6€Ôð/ð/ð/ð3ð3ð3ð0€:<„<ðØ€JL„L€L€Là€MO„O€Oà*Ð*Ð*Ð*Ð*Ð*Ð*Ð*Ð*Ð*ØÐÐÐÐÐàÐÐÐÐÐðM#cðM#˜cðM#ðM#ðM#ðM#ðM#ðM#r