1;jiNdZddlZddlZddlZddlZddlZddlZddlZddlm Z ddl m Z m Z m Z ddlmZddlmZmZddlmZmZddlmZd d lmZd d lmZmZmZejeZd Z dZ!dZ"de e#ej$ffdZ%dZ&dZ'dZ(dZ)dZ*e d$de e#ej$fde#de e e#ej$fde+de e+de e e#e#fde e e+e#fde e#d e+fd!Z,e d%de e#ej$fde#d"e e#de e e#ej$fde+de e+de e e#e#fde e e+e#fde e#d e+fd#Z-dS)&z3Utilities to dynamically load objects from the Hub.N)Path)DictOptionalUnion)request)hf_hub_download model_info)RevisionNotFoundErrorvalidate_hf_hub_args)version) __version__)DIFFUSERS_DYNAMIC_MODULE_NAMEHF_MODULES_CACHEloggingz$diffusers/community-pipelines-mirrorcd}tjtj|d}t |dS)Nz$https://pypi.org/pypi/diffusers/jsonreleasesc*tj|S)N)r Version)xs _/root/voice-cloning/.venv/lib/python3.11/site-packages/diffusers/utils/dynamic_modules_utils.pyz(get_diffusers_versions..-s'/!*<*<)key)jsonloadsrurlopenreadkeyssorted)urlrs rget_diffusers_versionsr#*sT 0Cz'/#..335566zBGGIIH ( < < = = ==rc0ttjvrdStjtt jtdt tdz }|s|dSdS)z_ Creates the cache directory for modules with an init, and adds it to the Python path. NTexist_ok __init__.py) rsyspathappendosmakedirsrexiststouch) init_paths rinit_hf_modulesr00s 38##HOO$%%%K 40000%&&6I     rnamec4ttt|z }|jst |jt j|d|dz }|s|dSdS)zF Creates a dynamic module in the cache directory for modules. Tr%r'N) r0rrparentr-create_dynamic_moduler+r,r.)r1dynamic_module_pathr/s rr4r4?s/0047  % , , . .:18999K#d3333#m3I     rc@t|dd5}|}dddn #1swxYwYtjd|tj}|tjd|tjz }t t |S)z Get the list of modules that are relatively imported in a module file. Args: module_file (`str` or `os.PathLike`): The module file to inspect. rutf-8encodingNz^\s*import\s+\.(\S+)\s*$flagsz^\s*from\s+\.(\S+)\s+import)openrrefindall MULTILINElistset) module_filefcontentrelative_importss rget_relative_importsrGNs k3 1 1 1Q&&((z"=wbl[[[ #A7RTR^____ $%% & &&s 488c:d}|g}g|sg}|D]$}|t|%t|jfd|D}fd|D}d|D}t |dk}||S)a) Get the list of all files that are needed for a given module. Note that this function recurses through the relative imports (if a imports b and b imports c, it will return module files for b and c). Args: module_file (`str` or `os.PathLike`): The module file to inspect. Fc4g|]}t|z S)str).0m module_paths r z-get_relative_import_files..ss%FFFQC a00FFFrcg|]}|v| SrJrJ)rLrDall_relative_importss rrOz-get_relative_import_files..ts$YYY!1DX;X;XA;X;X;Xrcg|]}|dS).pyrJ)rLrDs rrOz-get_relative_import_files..us>>>Q)))>>>rr)extendrGrr3len)rC no_changefiles_to_check new_importsrDnew_import_filesrQrNs @@rget_relative_import_filesrZ`sI!]N 4  8 8A   3A66 7 7 7 7;''. FFFF+FFFYYYY'7YYY>>-=>>>())Q. ##N333 4 rct|dd5}|}dddn #1swxYwYtjd|tj}|tjd|tjz }d|D}t t |}g}|D]<} tj|#t$r| |Y9wxYwt|d kr.s8OOOS3>>#;N;NOsyy~~a OOOrrz\This modeling file requires the following packages that were not found in your environment: , z. Run `pip install  `)r=rr>r?r@rArB importlib import_module ImportErrorr*rUjoinrG)filenamerDrEimportsmissing_packagesr`s r check_importsrk}s hg . . .!&&((j2G2<PPPG rz6r|TTTTGOOGOOOG3w<<  G)) )  #C ( ( ( ( ) ) )  # #C ( ( ( ( ( ) q   ]yy)** ] ]?BxxHX?Y?Y ] ] ]    ) ))s4883CC*)C*c|tjjd}t j|}|t |St||S)zY Import a module on the cache directory for modules and extract a class from it. r])replacer+r)seprdrefind_pipeline_classgetattr) class_namerNmodules rget_class_in_modulerssQ%%bgk377K  $[ 1 1F"6*** 6: & &&rc tddlm}ttj|tj}d}|D]n\}}||jkr^t||rN|j dddkr*|&td|jd|jd |d |d |}o|S) z Retrieve pipeline class that inherits from `DiffusionPipeline`. Note that there has to be exactly one class inheriting from `DiffusionPipeline`. r )DiffusionPipelineNr]r diffusersz#Multiple classes that inherit from z have been found: z, and z). Please make sure to define only one in ) pipelinesrudictinspect getmembersisclassitems__name__ issubclass __module__r_ ValueError) loaded_moduleru cls_memberspipeline_classcls_nameclss rroros .-----w)-IIJJKN$**,, ! ! # )2 2 23 122 3$$S))!, ;;) ):K:T))&/))7?))%))) !N rFpretrained_model_name_or_pathrC cache_dirforce_downloadresume_downloadproxiestokenrevisionlocal_files_onlyc & t|}tj||} tj| r| } d} n|ddkr,t } ddtjdddz} |/| dd| vr| nd }t d |dn@|| vrd|}n6|d kr|}n-td |d d | d gzd ttd|d|d||||} d} |dz}n#t$r}td|d|d}~wt$r#td|d|dwxYw t||||||||} tjdd|d} n0#t$r#td|d|dwxYwt#| }t$tjjz| z}t)|t+t,|z }| dks| dkrt/j| ||z |D]}t3|ddkr|d|d}|dd}tj||z stj||z |d}t/jtj||||z npt9|||j}||z }|tjjz|z}t)|||z st3|ddkrT|dd}tj||z stj||z t/j| ||z |D]}t3|ddkr(d|d}||z st=||d||||||| tj||S)at Prepares Downloads a module from a local folder or a distant repo and returns its path inside the cached Transformers module. Args: pretrained_model_name_or_path (`str` or `os.PathLike`): This can be either: - a string, the *model id* of a pretrained model configuration hosted inside a model repo on huggingface.co. Valid model ids can be located at the root-level, like `bert-base-uncased`, or namespaced under a user or organization name, like `dbmdz/bert-base-german-cased`. - a path to a *directory* containing a configuration file saved using the [`~PreTrainedTokenizer.save_pretrained`] method, e.g., `./my_model_directory/`. module_file (`str`): The name of the module file containing the class to look for. cache_dir (`str` or `os.PathLike`, *optional*): Path to a directory in which a downloaded pretrained model configuration should be cached if the standard cache should not be used. force_download (`bool`, *optional*, defaults to `False`): Whether or not to force to (re-)download the configuration files and override the cached versions if they exist. resume_download: Deprecated and ignored. All downloads are now resumed by default when possible. Will be removed in v1 of Diffusers. proxies (`Dict[str, str]`, *optional*): A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}.` The proxies are used on each request. token (`str` or *bool*, *optional*): The token to use as HTTP bearer authorization for remote files. If `True`, will use the token generated when running `transformers-cli login` (stored in `~/.huggingface`). revision (`str`, *optional*, defaults to `"main"`): The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any identifier allowed by git. local_files_only (`bool`, *optional*, defaults to `False`): If `True`, will only try to load the tokenizer configuration from local files. You may pass a token in `token` if you are not logged in (`huggingface-cli login`) and want to use private or [gated models](https://huggingface.co/docs/hub/models-gated#gated-models). Returns: `str`: The path to the module inside the cache. local/rvr]NrmainzDefaulting to latest_version: z`custom_revision`: z3 does not exist. Please make sure to choose one of radatasetrS)repo_id repo_typerhrrrrgitz Revision 'a' not found in the community pipelines mirror. Check available revisions on https://huggingface.co/datasets/diffusers/community-pipelines-mirror/tree/main. If you don't find the revision you are looking for, please open an issue on https://github.com/huggingface/diffusers/issues.zCould not locate the z inside )rrrrrrz--r )rrrrrrrrr)rKr+r)rgisfilecountr#rr_loggerinforrCOMMUNITY_PIPELINES_MIRROR_IDr EnvironmentErrorerrorrkrrnr4rrshutilcopyrUr-r,r shaget_cached_module_file)rrCrrrrrrrmodule_file_or_urlresolved_module_file submoduleavailable_versionslatest_versionemodules_neededfull_submodulesubmodule_path module_needed module_folder commit_hashs rrrsx%((E$F$F!&C[QQ w~~());1 & , ,S 1 1Q 6 6355sxx (9#(>(>rr(BCCC  )7);?Q)Q)Q~~W]H KKDDDD E E E E + + +%8~~HH   HH@h@@II0F8;<<@@@   #25#$II'DIII#-!1$$$ I7%?KK$   "PXPPP        LLfffFcfff g g g   #2-#- /!1 $ $ $  Wdii8U8[8[\_8`8`.a.abbII    LLfffFcfff g g g   ##788N3RW[@9LN.)))*++n???,111M K %BMRRTberTr s s s s t!!>Y^___c (+5'"'+5 Cn---,4466 L;$$S))**a// + 1 1# 6 6q 9 w~~n}&DEE@K >??? K,n{.J K K K,  M=&&s++,,11 #)<) Calling this function will execute the code in the module file found locally or downloaded from the Hub. It should therefore only be called on trusted repos. Args: pretrained_model_name_or_path (`str` or `os.PathLike`): This can be either: - a string, the *model id* of a pretrained model configuration hosted inside a model repo on huggingface.co. Valid model ids can be located at the root-level, like `bert-base-uncased`, or namespaced under a user or organization name, like `dbmdz/bert-base-german-cased`. - a path to a *directory* containing a configuration file saved using the [`~PreTrainedTokenizer.save_pretrained`] method, e.g., `./my_model_directory/`. module_file (`str`): The name of the module file containing the class to look for. class_name (`str`): The name of the class to import in the module. cache_dir (`str` or `os.PathLike`, *optional*): Path to a directory in which a downloaded pretrained model configuration should be cached if the standard cache should not be used. force_download (`bool`, *optional*, defaults to `False`): Whether or not to force to (re-)download the configuration files and override the cached versions if they exist. resume_download: Deprecated and ignored. All downloads are now resumed by default when possible. Will be removed in v1 of Diffusers. proxies (`Dict[str, str]`, *optional*): A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}.` The proxies are used on each request. token (`str` or `bool`, *optional*): The token to use as HTTP bearer authorization for remote files. If `True`, will use the token generated when running `transformers-cli login` (stored in `~/.huggingface`). revision (`str`, *optional*, defaults to `"main"`): The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any identifier allowed by git. local_files_only (`bool`, *optional*, defaults to `False`): If `True`, will only try to load the tokenizer configuration from local files. You may pass a token in `token` if you are not logged in (`huggingface-cli login`) and want to use private or [gated models](https://huggingface.co/docs/hub/models-gated#gated-models). Returns: `type`: The class, dynamically imported from the module. Examples: ```python # Download module `modeling.py` from huggingface.co and cache then extract the class `MyBertModel` from this # module. cls = get_class_from_dynamic_module("sgugger/my-bert-model", "modeling.py", "MyBertModel") ```rrS)rrsrm) rrCrqrrrrrrrkwargs final_modules rget_class_from_dynamic_modulerzsV\*%%')   L z<+?+?r+J+J K KKr)NFNNNNF)NNFNNNNF).__doc__rdryrr+r>rr(pathlibrtypingrrrurllibrhuggingface_hubrr huggingface_hub.utilsr r packagingr rrrrr get_loggerr}rrr#r0rKPathLiker4rGrZrkrsroboolrrrJrrrs:9 ((((((((((77777777MMMMMMMMFFFFFFFFFF  H % %!G>>>    c2;&6 7    '''$   :***@ ' ' '648 &*(,(,""r5r5#(bk)9#:r5r5c2;./0r5 r5 d^ r5 d38n % r5 E$)$ %r5smr5r5r5r5r5j!%37 &*(,(,""XLXL#(bk)9#:XLXL XLc2;./0 XL  XL d^ XLd38n %XL E$)$ %XLsmXLXLXLXLXLXLXLr