tjUddlmZddlZddlZddlZddlZddlmZddlm Z m Z ddl Z ddl m Z ejeZgdZded<ejdd Zdd ZddZddZddZddZddZdS)) annotationsN) Generator)PackageNotFoundErrormetadata)is_torch_npu_available)))pillowpil-pip install -U "sentence-transformers[image]")) read_videozQpip install -U "sentence-transformers[video]" # or [audio] for audio-only models)) torchvisionr )) torchcodeczpip install -U torchcodec)) soundfilelibrosaz-pip install -U "sentence-transformers[audio]"z!list[tuple[tuple[str, ...], str]]_DEPENDENCY_EXTRA_HINTSreturnGenerator[None, None, None]c#VK dVdS#ttf$r}t|tD]]\}}t fd|Dr=t |t|d||^d}~wwxYw)zaRe-raise ImportError/AttributeError with an install hint when a multimodal dependency is missing.Nc3 K|]}|vV dS)N).0kwmsgs d/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/sentence_transformers/util/environment.py z-suggest_extra_on_exception..#s'0029000000z- To install the required dependencies, run: ) ImportErrorAttributeErrorstrlowerranytypestrip)ekeywordshintrs @rsuggest_extra_on_exceptionr&s   (!ffllnn5 p pNHd0000x00000 pd1ggQggaegghhnoo p s B(BB##B(boolcztjotjS)aP Returns whether ``torch.distributed`` is available and has been initialized. The availability check must come first: some PyTorch builds (e.g. ROCm or CPU-only) report ``torch.distributed.is_available() == False`` and do not expose APIs like ``is_initialized``, so calling them directly raises ``AttributeError``. )torch distributed is_availableis_initializedrrris_dist_initializedr-(s-   ) ) + + R0A0P0P0R0RRrrctjrdtjvr t tjd}nmt r]tjtj krtj }nd}d|Stj j rdStrdSttdr tjrdStjdddlmcm}|rd Sd S) aV Returns the name of the device where this module is running on. This function only supports single device or basic distributed training setups. In distributed mode for cuda device, it uses the rank to assign a specific CUDA device. Returns: str: Device name, like 'cuda:2', 'mps', 'npu', 'xpu', 'hpu', or 'cpu' LOCAL_RANKrzcuda:mpsnpuxpuhabana_frameworksNhpucpu)r)cudar+osenvironintr- device_countr*get_rankbackendsr0rhasattrr2 importlibutil find_spechabana_frameworks.torch.hpur4) local_rankhthpus rget_device_namerD3sH z   2: % %RZ 566JJ " " uz'>'>'@'@5CTC]C]C_C_'_'_*3355JJJ#z###   ( ( * * u  ! !u   59#9#9#;#;u  ! !"5 6 6 B333333333      5 5r package_nameownerc| t|}|d}|d|ko|duo||vS#t$rYdSwxYw)zB Checks if a package is available from the correct owner. z Home-pageNameNF)rr)rErFmeta home_pages rcheck_package_availabilityrKSsd %%% F||+\ 0E\%S\J\\ uus *- ;;c"tddS)zJ Returns True if the Huggingface accelerate library is available. accelerate huggingfacerKrrris_accelerate_availablerP_s &lM B BBrc"tddS)zH Returns True if the Huggingface datasets library is available. datasetsrNrOrrris_datasets_availablerSfs &j- @ @@rc:to tS)z Returns True if we have the required dependencies for training Sentence Transformers models, i.e. Huggingface datasets and Huggingface accelerate. )rPrSrrris_training_availablerUms # $ $ @)>)@)@@r)rr)rr')rr)rErrFrrr') __future__r contextlibr>loggingr7collections.abcrimportlib.metadatarrr) transformersr getLogger__name__loggerr__annotations__contextmanagerr&r-rDrKrPrSrUrrrrasz""""""" %%%%%%======== //////  8 $ $>>>     SSSS@    CCCCAAAAAAAAAAr