[^(h!_ddlZddlZddlZddlZddlZddlZddlZddlmZ ddl Z dZ edgdZgdZgdZgd Zgd Zd Zd Zd ZdZd+dZdZdZdZdZdZdZdZdZ dZ!dZ"dZ#dZ$dZ%dZ&dZ'dZ(d Z)d+d!Z*d"Z+d#Z,d$Z-d%Z.d&j_Z0d'Z1d(Z2d)Z3e4d*k(re3yy#e e e ef$rdZ YwxYw),N) namedtupleTF SystemEnv) torch_versionis_debug_buildcuda_compiled_version gcc_version clang_version cmake_versionos libc_versionpython_versionpython_platformis_cuda_availablecuda_runtime_versioncuda_module_loadingnvidia_driver_versionnvidia_gpu_models cudnn_version pip_version pip_packagesconda_packageship_compiled_versionhip_runtime_versionmiopen_runtime_versioncaching_allocator_configis_xnnpack_availablecpu_info)torchnumpytritonoptree)z cuda-cudartz cuda-cuptizcuda-librariesz cuda-openclz cuda-nvrtcz cuda-runtimecublascudnncufftcurandcusolvercusparsenccl nvjitlinknvtx) cudatoolkitsoumithmklmagma)mypyflake8onnxct|turdnd}tj|tjtj|}|j \}}|j }tdk(rd}ntj}|j|}|j|}||j|jfS)z%Return (return-code, stdout, stderr).TF)stdoutstderrshellwin32oem) typestr subprocessPopenPIPE communicate returncode get_platformlocalegetpreferredencodingdecodestrip) commandr5p raw_outputraw_errrcencoutputerrs U/var/www/skyplay_api_hub/venv/lib/python3.12/site-packages/torch/utils/collect_env.pyrunrMZsMS(DeE *u >A--/J B~ ))+   s #F .. C v||~syy{ **c*||\}}}|dk7ry|S)zIRun command using run_lambda; reads and returns entire output if rc is 0.rN run_lambdarDrHout_s rLrun_and_read_allrUjs!G$JBQ Qw JrNcz||\}}}|dk7rytj||}|y|jdS)zIRun command using run_lambda, returns the first regex match if it exists.rN)researchgroup)rRrDregexrHrSrTmatchs rLrun_and_parse_first_matchr]rsBG$JBQ Qw IIeS !E } ;;q>rNcN||\}}}|dk7ry|jddS)zKRun command using run_lambda and returns first line if output is not empty.rN )splitrQs rLrun_and_return_first_linera|s/G$JBQ Qw 99T?1 rNcttztztjj dd}t |dj|}||Sdjfd|jDS)N CONDA_EXEcondaz{} listr_c3nK|]+jdstfdDr-yw)#c3&K|]}|v ywNrP.0namelines rL z/get_conda_packages...s2 2N) startswithanyrjrlpatternss @rLrmz%get_conda_packages..s3 s# 22 2 s15) CONDA_PATTERNSCOMMON_PATTERNSNVIDIA_PATTERNSr environgetrUformatjoin splitlines)rRrrrdrSs ` rLget_conda_packagesr{sr!O3oE JJNN; 0E :y'7'7'> ?C { 99NN$ rNct|ddS)Nz gcc --versionzgcc (.*)r]rRs rLget_gcc_versionrs $Z+ NNrNct|ddS)Nzclang --versionzclang version (.*)r}r~s rLget_clang_versionrs $Z1BDY ZZrNct|ddS)Nzcmake --versionz cmake (.*)r}r~s rLget_cmake_versionrs $Z1BM RRrNchtdk(rd}t||dSt}t||dS)Ndarwinzkextstat | grep -i cudazcom[.]nvidia[.]CUDA [(](.*?)[)]zDriver Version: (.*?) )r?r]get_nvidia_smi)rRcmdsmis rLget_nvidia_driver_versionrs?~!'(S)KM M  C $Z6O PPrNctdk(s:trttjdrtjj trtj jrtjj Jtj jd}t|drdj|j}nd}nd}tj jd|zSyt}tjd}||d z\}}}|dk7rytj|d|S) Nrhipr gcnArchNamez ({})NoGCNArchNameOnOldPyTorchz \(UUID: .+?\)z -L)r?TORCH_AVAILABLEhasattrrversionrcuda is_availableget_device_propertiesrxrget_device_namerrXcompilesub)rRpropgcnArchr uuid_regexrHrSrTs rL get_gpu_infors~!o'%--QV:W\a\i\i\m\m\y uzz668}}  ,zz77:4/%nnT-=-=>G9G::--d3g= =  C-.JC%K(JBQ Qw 66*b# &&rNct|ddS)Nznvcc --versionzrelease .+ V(.*)r}r~s rLget_running_cuda_versionrs $Z1ACV WWrNctdk(rttjjdd}tjjdd}tjj |dd}dj ||}ntd k(rd }nd }||\}}}t|d k(s |d k7re|d k7r`tjjd}|>tjj|rtjj|Syt} |jdD]R} tjj| } tjj| sB| j| T| syt| } t| d k(r| d Sdj | } dj | S)zHReturn a list of libcudnn.so; it's hard to tell which one is being used.r6 SYSTEMROOT C:\Windows CUDA_PATHz %CUDA_PATH%System32wherez{} /R "{}\bin" cudnn*.dllrz ls /usr/local/cuda/lib/libcudnn*z7ldconfig -p | grep libcudnn | rev | cut -d" " -f1 | revrrW CUDNN_LIBRARYNr_z!Probably one of the following: {})r?r rvrwpathryrxlenisfilerealpathsetr`addsorted) rR system_root cuda_path where_cmd cudnn_cmdrHrSrTl files_setfnfilesresults rLget_cudnn_versionrsj~ jjnn\=A JJNN; > GGLLj'B 077 9M 8 # 7 M I&JBQ 3x1}qR1W JJNN? + =RWW^^A.77##A& &Iiio WW  b ! 77>>"  MM"   9 E 5zQQx YYu F / 6 6v >>rNcd}tdk(rtjjdd}tjjdd}tjj |dd|}tjj |d |}||g}|D]5}tjj |s#d j|}|S|S) Nz nvidia-smir6rr PROGRAMFILESzC:\Program FileszNVIDIA CorporationNVSMIrz"{}")r?r rvrwrryexistsrx)rrprogram_files_root legacy_pathnew_pathsmis candidate_smis rLrrs C~ jjnn\=A ZZ^^N+E..E3c"tjjdrytjjdrytjjdrytjjdrytjS)Nrr6cygwinr)sysplatformrorPrNrLr?r?cs` ||w'   )   *   *||rNct|ddS)Nzsw_vers -productVersionz(.*)r}r~s rLget_mac_versionrps $Z1JG TTrNct|d} tj|}|dd|dd|dd}|S#t$r}|dt |z }Yd}~|Sd}~wwxYw) Nzpowershell.exe "gwmi -Class Win32_OperatingSystem | Select-Object -Property Caption, OSArchitecture,Version | ConvertTo-Json"Captionz (Version OSArchitecture)r_)rUrrrr9)rRretrrs rLget_windows_versionrts  2 C jjoY 3y>"2!C8H4I3J!L J  CF8} Js)9 AAAct|ddS)Nzlsb_release -azDescription:\t(.*)r}r~s rLget_lsb_versionrs $Z1ACX YYrNct|ddS)Nzcat /etc/*-releasezPRETTY_NAME="(.*)"r}r~s rLcheck_release_filers $Z1E%: <..s1tt|1rnN)rprqs @rLrmz#get_pip_packages..s'  11 1 s $) PIP_PATTERNSrtrurrr rvrU executableryrz)rRrrrrS filtered_outs ` rLget_pip_packagesrs/1OCKKNc1&uK25BJJ./ :IZ'[ \C99NN$L  $$rNcFtjjdd}|S)NPYTORCH_CUDA_ALLOC_CONFr)r rvrw) ca_configs rLget_cachingallocator_configrs 8"=I rNctr^tjjr@tjj t j jdd}|Sy)NCUDA_MODULE_LOADINGrr)rrrrinitr rvrw)configs rLget_cuda_module_loading_configrs?5::224  5r: rNcjtr-ddl}t|jjj Sy)Nrr)rtorch.backends.xnnpackr9backendsxnnpackenabled)rs rLrrs&%5>>))1122rNc t}t|\}}trtj}t tj j}t tjj}tj j}ttj drtj jdx}x}} nmd} tjjjd} | | d}| | d} d}tj j}ndx}x}x}}dx}x}} tj j!dd} t#|} t%d#id|d |d d j'| tj(j+d zd t-d|d|dt/|dt1dt3|dt5|dt7|d|d|d| d|d|d| dt9|dt;dt=|dt?|dtA|d tCd!tEd"tG|S)$a Collects environment information to aid in debugging. The returned environment information contains details on torch version, is debug build or not, cuda compiled version, gcc version, clang version, cmake version, operating system, libc version, python version, python platform, CUDA availability, CUDA runtime version, CUDA module loading config, GPU model and configuration, Nvidia driver version, cuDNN version, pip version and versions of relevant pip and conda packages, HIP runtime version, MIOpen runtime version, Caching allocator config, XNNPACK availability and CPU information. Returns: SystemEnv (namedtuple): A tuple containining various environment details and system information. rrcl|Dcgc]}||vs|jddd}}|r|dSdScc}w)NrWrr)rsplit)cfgprefixs_lsts rLget_version_or_naz'get_env_info..get_version_or_nasB7:J!fkq)"-JJ"&tAw1E1Ks 11r_z HIP RuntimeMIOpenrrrr z{} ({}-bit runtime)rWrrrrrrrrrrrrrrr r rr r rrrrP)$rMrrr __version__r9rdebugrrrr_C _show_configr`rreplacer{rrxmaxsize bit_lengthrrrrrrrrrrrrrr)rRrpip_list_output version_strdebug_mode_strcuda_available_strcuda_version_strrrrrr sys_versionrs rL get_env_infor!s J#3J#? K'' U]]001 !8!8!:; ==--u}}e, 0A0A0IRW W W#69O 2(('')//5C"3C"G %6sH%E "$ #(==#4#4 OTT TnT'9/ 0231 2j)3 rNaP PyTorch version: {torch_version} Is debug build: {is_debug_build} CUDA used to build PyTorch: {cuda_compiled_version} ROCM used to build PyTorch: {hip_compiled_version} OS: {os} GCC version: {gcc_version} Clang version: {clang_version} CMake version: {cmake_version} Libc version: {libc_version} Python version: {python_version} Python platform: {python_platform} Is CUDA available: {is_cuda_available} CUDA runtime version: {cuda_runtime_version} CUDA_MODULE_LOADING set to: {cuda_module_loading} GPU models and configuration: {nvidia_gpu_models} Nvidia driver version: {nvidia_driver_version} cuDNN version: {cudnn_version} HIP runtime version: {hip_runtime_version} MIOpen runtime version: {miopen_runtime_version} Is XNNPACK available: {is_xnnpack_available} CPU: {cpu_info} Versions of relevant libraries: {pip_packages} {conda_packages} cX dd}dd}dd}dd}d}|j ||j d<gd}|dgz}t fd |D}tr=tj j s|r|D]} d | < |jd d <|  |  | d  d <| d d< d r(| d dj|j d < dr| dd d<|j d<tjdi S)NcF|jD] }|| |||<|Srhkeys)dct replacementkeys rL replace_nonesz!pretty_str..replace_nonesHs488: #C3x#"CH # rNcd|jD]}||dur|||<||dus|||<|S)NTFr$)r&truefalser(s rL replace_boolsz!pretty_str..replace_boolsOsH88: !C3x4CSU" C  !  rNct|jd}|Dcgc]}||z }}dj|Scc}w)Nr_)r`ry)texttaglinesrl updated_liness rLprependzpretty_str..prependWs; 4 056t6 6yy''7s 5c*|t|dk(r|S|Sr)r)r/r's rLreplace_if_emptyz$pretty_str..replace_if_empty\s  D Q  rNcf|.t|jddkDrdj|S|S)Nr_rWz {} )rr`rx)strings rLmaybe_start_on_next_linez,pretty_str..maybe_start_on_next_lineas1  #fll4&8"9A"=??6* * rNr)rrrrc3,K|] }|du ywrhrP)rjfield mutable_dicts rLrmzpretty_str..ts"*F(- Ut#*FszNo CUDArrrrz[{}] z[conda] r)zCould not collect)YesNo)z [prepend])zNo relevant packagesrP) _asdictrallrrrrrrxrr env_info_fmt) envinfor)r-r3r5r8dynamic_cuda_fieldsall_cuda_fieldsall_dynamic_cuda_fields_missingr:r;s @rL pretty_strrEGs{(   ??$L !!:!:;$% *_,==O&)*F1D*F'F#uzz668=\$ ,E"+L  ,  ( ( 04:L0 1!.L!.L$4L4P#QL %5lCS6T%UL!"N#'.|N/K/6~~g>Q>Q/R(T ^$$%)0>N1O1;*= %&&//L    . ..rNc(ttS)a Returns a pretty string of environment information. This function retrieves environment information by calling the `get_env_info` function and then formats the information into a human-readable string. The retrieved environment information is listed in the document of `get_env_info`. This function is used in `python collect_env.py` that should be executed when reporting a bug. Returns: str: A pretty string of the environment information. )rEr!rPrNrLget_pretty_env_inforGs ln %%rNc0tdt}t|trjttdrXttj drrcsG   "O {%  8$  +  O[SQ',X"?J vD U Z< < )%( FP< EG= BH/V &($ zFA Y8OsB?? C  C