o 0j @sLddlZddlZddlmZddlmZmZddlZddlm Z ddl m Z ddl m Z mZmZmZmZmZmZddlmZmZmZmZmZdd lmZdd lmZdd lmZm Z m!Z!e "e#Z$ee%j&d d Z'ee%j&d dZ(e)dZ*GdddZ+Gddde+Z,Gddde+Z-Gddde+Z.de/dedfddZ0de/eBde1dBfddZ2de/eBd e1ddfd!d"Z3dd#ddddd$d%e/d&e/d'e/d(e/d)e/d*ed+e/d,e/d-e/dBd.e4d/e/dBd0e/dBd1e/dBd2e/dBde1fd3d4Z5e!dd#ddddd#dd5d6e/d7e1d8e/dBd9e4d:e/dBd;e/dBde4d?e/dBde/fd@dAZ6dS)BN)Path)AnyLiteral)hf_hub_download) upload_file)CardDataDatasetCardData EvalResult ModelCardData SpaceCardDataeval_results_to_model_indexmodel_index_to_eval_results)HfHubHTTPError get_sessionhf_raise_for_statusis_jinja_available yaml_dump) constants)EntryNotFoundError)SoftTemporaryDirectoryloggingvalidate_hf_hub_argsZ templateszmodelcard_template.mdzdatasetcard_template.mdz1^(\s*---[\r\n]+)([\S\s]*?)([\r\n]+---(\r\n|\n|$))c@s*eZdZeZeZdZd$dede fddZ e ddZ e j defd dZ d d Zd eeBfd dZe   d%deeBdedBdedBde fddZd&dedBfddZ       d'dededBdedBdedBdedBdedBde dBdedBfddZe  d(ded edBd!edBfd"d#ZdS))RepoCardmodelFcontentignore_metadata_errorscCs||_||_dS)aInitialize a RepoCard from string content. The content should be a Markdown file with a YAML block at the beginning and a Markdown body. Args: content (`str`): The content of the Markdown file. Example: ```python >>> from huggingface_hub.repocard import RepoCard >>> text = ''' ... --- ... language: en ... license: mit ... --- ... ... # My repo ... ''' >>> card = RepoCard(text) >>> card.data.to_dict() {'language': 'en', 'license': 'mit'} >>> card.text '\n# My repo\n' ``` > [!TIP] > Raises the following error: > > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError) > when the content of the repo card metadata is not a dictionary. N)rr)selfrrrY/var/www/html/Deteccion_Ine/venv/lib/python3.10/site-packages/huggingface_hub/repocard.py__init__*s" zRepoCard.__init__cCs:t|jpd}d||jj||jd|d||jS)zLThe content of the RepoCard, including the YAML block and the Markdown body. ---) line_breakZoriginal_order)_detect_line_ending_contentdatato_yaml_original_ordertext)rr#rrrrOs,zRepoCard.contentcCs||_t|}|r-|d}||d|_t|}|dur#i}t|t s,t dn t di}||_|j di|d|ji|_t||_dS)z Set the content of the RepoCard.N)repo card metadata block should be a dictzBRepo card metadata block was not found. Setting CardData to empty.rr)r%REGEX_YAML_BLOCKsearchgroupendr)yaml safe_load isinstancedict ValueErrorloggerwarningcard_data_classrr&listkeysr()rrmatch yaml_blockZ data_dictrrrrUs      cCs|jSN)r)rrrr__str__pszRepoCard.__str__filepathcCs\t|}|jjdddt|dddd}|t|WddS1s'wYdS)a{Save a RepoCard to a file. Args: filepath (`Union[Path, str]`): Filepath to the markdown file to save. Example: ```python >>> from huggingface_hub.repocard import RepoCard >>> card = RepoCard("---\nlanguage: en\n---\n# This is a test repo card") >>> card.save("/tmp/test.md") ``` T)parentsexist_okwutf-8modenewlineencodingN)rparentmkdiropenwritestr)rr>frrrsavess "z RepoCard.saveNrepo_id_or_path repo_typetokencCst|r t|}nt|trtt|tj|p|j|d}ntd|d|j dddd}|| |dWd S1sBwYd S) aInitialize a RepoCard from a Hugging Face Hub repo's README.md or a local filepath. Args: repo_id_or_path (`Union[str, Path]`): The repo ID associated with a Hugging Face Hub repo or a local filepath. repo_type (`str`, *optional*): The type of Hugging Face repo to push to. Defaults to None, which will use "model". Other options are "dataset" and "space". Not used when loading from a local filepath. If this is called from a child class, the default value will be the child class's `repo_type`. token (`str`, *optional*): Authentication token, obtained with `huggingface_hub.HfApi.login` method. Will default to the stored token. ignore_metadata_errors (`str`): If True, errors while parsing the metadata section will be ignored. Some information might be lost during the process. Use it at your own risk. Returns: [`huggingface_hub.repocard.RepoCard`]: The RepoCard (or subclass) initialized from the repo's README.md file or filepath. Example: ```python >>> from huggingface_hub.repocard import RepoCard >>> card = RepoCard.load("nateraw/food") >>> assert card.data.tags == ["generated_from_trainer", "image-classification", "pytorch"] ``` )rPrQz.Cannot load RepoCard: path not found on disk (z).rrBrCrD)rN) ris_filer2rLrr REPOCARD_NAMErPr4rJread)clsrOrPrQrZ card_pathrMrrrloads $   $z RepoCard.loadc Csr|p|j}|t|d}ddi}ztjd||d}t|WdSty8}z |jdkr2t|j|d}~ww)aValidates card against Hugging Face Hub's card validation logic. Using this function requires access to the internet, so it is only called internally by [`huggingface_hub.repocard.RepoCard.push_to_hub`]. Args: repo_type (`str`, *optional*, defaults to "model"): The type of Hugging Face repo to push to. Options are "model", "dataset", and "space". If this function is called from a child class, the default will be the child class's `repo_type`. > [!TIP] > Raises the following errors: > > - [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError) > if the card fails validation checks. > - [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError) > if the request to the Hub API fails for any other reason. )ZrepoTyperAcceptz text/plainz(https://huggingface.co/api/validate-yaml)jsonheadersiN) rPrLrpostrr status_coder4r))rrPbodyrZresponseexcrrrvalidates   zRepoCard.validaterepo_idcommit_messagecommit_descriptionrevision create_pr parent_commitc Cs|p|j}|j|dt*} t| tj} | jt|ddtt| tj||||||||d } Wd| S1s;wY| S)aBPush a RepoCard to a Hugging Face Hub repo. Args: repo_id (`str`): The repo ID of the Hugging Face Hub repo to push to. Example: "nateraw/food". token (`str`, *optional*): Authentication token, obtained with `huggingface_hub.HfApi.login` method. Will default to the stored token. repo_type (`str`, *optional*, defaults to "model"): The type of Hugging Face repo to push to. Options are "model", "dataset", and "space". If this function is called by a child class, it will default to the child class's `repo_type`. commit_message (`str`, *optional*): The summary / title / first line of the generated commit. commit_description (`str`, *optional*) The description of the generated commit. revision (`str`, *optional*): The git revision to commit from. Defaults to the head of the `"main"` branch. create_pr (`bool`, *optional*): Whether or not to create a Pull Request with this commit. Defaults to `False`. parent_commit (`str`, *optional*): The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported. If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`. If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`. Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be especially useful if the repo is updated / committed too concurrently. Returns: `str`: URL of the commit which updated the card metadata. )rPrC)rG) Zpath_or_fileobjZ path_in_reporarQrPrbrcrerdrfN) rPr`rrrrT write_textrLr) rrarQrPrbrcrdrerfZtmpdirZtmp_pathurlrrr push_to_hubs* )  zRepoCard.push_to_hub card_data template_path template_strc Kstrddl}ntd|}|||dur!t|}|dur,t|j}| |}|j dd| i|}||S)a'Initialize a RepoCard from a template. By default, it uses the default template. Templates are Jinja2 templates that can be customized by passing keyword arguments. Args: card_data (`huggingface_hub.CardData`): A huggingface_hub.CardData instance containing the metadata you want to include in the YAML header of the repo card on the Hugging Face Hub. template_path (`str`, *optional*): A path to a markdown file with optional Jinja template variables that can be filled in with `template_kwargs`. Defaults to the default template. Returns: [`huggingface_hub.repocard.RepoCard`]: A RepoCard instance with the specified card data and content from the template. rNzjUsing RepoCard.from_template requires Jinja2 to be installed. Please install it with `pip install Jinja2`.rjr) rjinja2 ImportErrorto_dictcopyupdater read_textdefault_template_pathTemplaterenderr') rVrjrkrltemplate_kwargsrmkwargstemplaterrrr from_template!s     zRepoCard.from_template)F)NNFr<)NNNNNNNNN)__name__ __module__ __qualname__rr7TEMPLATE_MODELCARD_PATHrsrPrLboolr propertyrsetterr=rrN classmethodrWr`riryrrrrr%sv%  5( ?rc HeZdZeZeZdZe  ddede dBde dBffdd Z Z S) ModelCardrNrjrkrlc tj|||fi|S)a Initialize a ModelCard from a template. By default, it uses the default template, which can be found here: https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md Templates are Jinja2 templates that can be customized by passing keyword arguments. Args: card_data (`huggingface_hub.ModelCardData`): A huggingface_hub.ModelCardData instance containing the metadata you want to include in the YAML header of the model card on the Hugging Face Hub. template_path (`str`, *optional*): A path to a markdown file with optional Jinja template variables that can be filled in with `template_kwargs`. Defaults to the default template. Returns: [`huggingface_hub.ModelCard`]: A ModelCard instance with the specified card data and content from the template. Example: ```python >>> from huggingface_hub import ModelCard, ModelCardData, EvalResult >>> # Using the Default Template >>> card_data = ModelCardData( ... language='en', ... license='mit', ... library_name='timm', ... tags=['image-classification', 'resnet'], ... datasets=['beans'], ... metrics=['accuracy'], ... ) >>> card = ModelCard.from_template( ... card_data, ... model_description='This model does x + y...' ... ) >>> # Including Evaluation Results >>> card_data = ModelCardData( ... language='en', ... tags=['image-classification', 'resnet'], ... eval_results=[ ... EvalResult( ... task_type='image-classification', ... dataset_type='beans', ... dataset_name='Beans', ... metric_type='accuracy', ... metric_value=0.9, ... ), ... ], ... model_name='my-cool-model', ... ) >>> card = ModelCard.from_template(card_data) >>> # Using a Custom Template >>> card_data = ModelCardData( ... language='en', ... tags=['image-classification', 'resnet'] ... ) >>> card = ModelCard.from_template( ... card_data=card_data, ... template_path='./src/huggingface_hub/templates/modelcard_template.md', ... custom_template_var='custom value', # will be replaced in template if it exists ... ) ``` superryrVrjrkrlrv __class__rrryRsIzModelCard.from_templaterz) r{r|r}r r7r~rsrPrrLry __classcell__rrrrrMrc r) DatasetCarddatasetNrjrkrlc r)aInitialize a DatasetCard from a template. By default, it uses the default template, which can be found here: https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md Templates are Jinja2 templates that can be customized by passing keyword arguments. Args: card_data (`huggingface_hub.DatasetCardData`): A huggingface_hub.DatasetCardData instance containing the metadata you want to include in the YAML header of the dataset card on the Hugging Face Hub. template_path (`str`, *optional*): A path to a markdown file with optional Jinja template variables that can be filled in with `template_kwargs`. Defaults to the default template. Returns: [`huggingface_hub.DatasetCard`]: A DatasetCard instance with the specified card data and content from the template. Example: ```python >>> from huggingface_hub import DatasetCard, DatasetCardData >>> # Using the Default Template >>> card_data = DatasetCardData( ... language='en', ... license='mit', ... annotations_creators='crowdsourced', ... task_categories=['text-classification'], ... task_ids=['sentiment-classification', 'text-scoring'], ... multilinguality='monolingual', ... pretty_name='My Text Classification Dataset', ... ) >>> card = DatasetCard.from_template( ... card_data, ... pretty_name=card_data.pretty_name, ... ) >>> # Using a Custom Template >>> card_data = DatasetCardData( ... language='en', ... license='mit', ... ) >>> card = DatasetCard.from_template( ... card_data=card_data, ... template_path='./src/huggingface_hub/templates/datasetcard_template.md', ... custom_template_var='custom value', # will be replaced in template if it exists ... ) ``` rrrrrrys9zDatasetCard.from_templaterz) r{r|r}rr7TEMPLATE_DATASETCARD_PATHrsrPrrLryrrrrrrrrc@seZdZeZeZdZdS) SpaceCardspaceN)r{r|r}r r7r~rsrPrrrrrsrrreturn) r! NcCsR|d}|d}|d}||dkrdS||kr!||kr!dS||kr'dSdS)zDetect the line ending of a string. Used by RepoCard to avoid making huge diff on newlines. Uses same implementation as in Hub server, keep it in sync. Returns: str: The detected line ending of the string. rr!rrN)count)rcrlfZcrlfrrrr$s    r$ local_pathcCsPt|}t|}|r&|d}t|}|dus t|tr"|St ddS)Nr*r+) rrrr,r-r.r0r1r2r3r4)rrr:r;r&rrr metadata_loads    rr&cCs&d}d}tj|r:t|ddd!}|}t|jtr"|jd}n t|jtr+|j}Wdn1s5wYt|ddddG}t |d|d }t |}|rl|d| d ||d ||| d}n d ||d ||}|||WddS1swYdS) a& Save the metadata dict in the upper YAML part Trying to preserve newlines as in the existing file. Docs about open() with newline="" parameter: https://docs.python.org/3/library/functions.html?highlight=open#open Does not work with "^M" linebreaks, which are replaced by r!rButf8)rFrGrNrAF) sort_keysr#r")ospathexistsrJrUr2newlinestuplerLrr,r-startr/rKclose)rr&r#rZreadmeZ data_yamlr:outputrrr metadata_saves(     6  "rF)metrics_configmetrics_verifieddataset_config dataset_splitdataset_revisionmetrics_verification_tokenmodel_pretty_nametask_pretty_nametask_idmetrics_pretty_name metrics_id metrics_valuedataset_pretty_name dataset_idrrrrrrcCs0dt|t||||||||| | | | | d gdiS)u Creates a metadata dict with the result from a model evaluated on a dataset. Args: model_pretty_name (`str`): The name of the model in natural language. task_pretty_name (`str`): The name of a task in natural language. task_id (`str`): Example: automatic-speech-recognition. A task id. metrics_pretty_name (`str`): A name for the metric in natural language. Example: Test WER. metrics_id (`str`): Example: wer. A metric id from https://hf.co/metrics. metrics_value (`Any`): The value from the metric. Example: 20.0 or "20.0 ± 1.2". dataset_pretty_name (`str`): The name of the dataset in natural language. dataset_id (`str`): Example: common_voice. A dataset id from https://hf.co/datasets. metrics_config (`str`, *optional*): The name of the metric configuration used in `load_metric()`. Example: bleurt-large-512 in `load_metric("bleurt", "bleurt-large-512")`. metrics_verified (`bool`, *optional*, defaults to `False`): Indicates whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not. Automatically computed by Hugging Face, do not set. dataset_config (`str`, *optional*): Example: fr. The name of the dataset configuration used in `load_dataset()`. dataset_split (`str`, *optional*): Example: test. The name of the dataset split used in `load_dataset()`. dataset_revision (`str`, *optional*): Example: 5503434ddd753f426f4b38109466949a1217c2bb. The name of the dataset dataset revision used in `load_dataset()`. metrics_verification_token (`bool`, *optional*): A JSON Web Token that is used to verify whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not. Returns: `dict`: a metadata dict with the result from a model evaluated on a dataset. Example: ```python >>> from huggingface_hub import metadata_eval_result >>> results = metadata_eval_result( ... model_pretty_name="RoBERTa fine-tuned on ReactionGIF", ... task_pretty_name="Text Classification", ... task_id="text-classification", ... metrics_pretty_name="Accuracy", ... metrics_id="accuracy", ... metrics_value=0.2662102282047272, ... dataset_pretty_name="ReactionJPEG", ... dataset_id="julien-c/reactionjpeg", ... dataset_config="default", ... dataset_split="test", ... ) >>> results == { ... 'model-index': [ ... { ... 'name': 'RoBERTa fine-tuned on ReactionGIF', ... 'results': [ ... { ... 'task': { ... 'type': 'text-classification', ... 'name': 'Text Classification' ... }, ... 'dataset': { ... 'name': 'ReactionJPEG', ... 'type': 'julien-c/reactionjpeg', ... 'config': 'default', ... 'split': 'test' ... }, ... 'metrics': [ ... { ... 'type': 'accuracy', ... 'value': 0.2662102282047272, ... 'name': 'Accuracy', ... 'verified': False ... } ... ] ... } ... ] ... } ... ] ... } True ``` model-index) Z task_nameZ task_type metric_name metric_type metric_valueZ dataset_nameZ dataset_typeZ metric_configverified verify_tokenrrr) model_name eval_results)r r )rrrrrrrrrrrrrrrrrmetadata_eval_result's(ir)rP overwriterQrbrcrdrerframetadatarPrrQrbrcrdrerfc Cs|dur|nd}|dus|dkrt} n|dkrt} n|dkr!t} ntd|z | j|||d} WntyI|dkrAtd| t} Ynw|D]\} } | d krd | d vrft | d || d d <t | \}}| j j dur{|| j _ || j _ qN| j j }|D]9}d }|D])}||r||kr|std|jd|jdd}|j|_|jdur|j|_q|s| j j |qqN| j | dur|s| j | | krtd| d| | j | <qN| j|||||||| dS)a Updates the metadata in the README.md of a repository on the Hugging Face Hub. If the README.md file doesn't exist yet, a new one is created with metadata and the default ModelCard or DatasetCard template. For `space` repo, an error is thrown as a Space cannot exist without a `README.md` file. Args: repo_id (`str`): The name of the repository. metadata (`dict`): A dictionary containing the metadata to be updated. repo_type (`str`, *optional*): Set to `"dataset"` or `"space"` if updating to a dataset or space, `None` or `"model"` if updating to a model. Default is `None`. overwrite (`bool`, *optional*, defaults to `False`): If set to `True` an existing field can be overwritten, otherwise attempting to overwrite an existing field will cause an error. token (`str`, *optional*): The Hugging Face authentication token. commit_message (`str`, *optional*): The summary / title / first line of the generated commit. Defaults to `f"Update metadata with huggingface_hub"` commit_description (`str` *optional*) The description of the generated commit revision (`str`, *optional*): The git revision to commit from. Defaults to the head of the `"main"` branch. create_pr (`boolean`, *optional*): Whether or not to create a Pull Request from `revision` with that commit. Defaults to `False`. parent_commit (`str`, *optional*): The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported. If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`. If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`. Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be especially useful if the repo is updated / committed too concurrently. Returns: `str`: URL of the commit which updated the card metadata. Example: ```python >>> from huggingface_hub import metadata_update >>> metadata = {'model-index': [{'name': 'RoBERTa fine-tuned on ReactionGIF', ... 'results': [{'dataset': {'name': 'ReactionGIF', ... 'type': 'julien-c/reactiongif'}, ... 'metrics': [{'name': 'Recall', ... 'type': 'recall', ... 'value': 0.7762102282047272}], ... 'task': {'name': 'Text Classification', ... 'type': 'text-classification'}}]}]} >>> url = metadata_update("hf-internal-testing/reactiongif-roberta-card", metadata) ``` Nz$Update metadata with huggingface_hubrrrzUnknown repo_type: )rQrPzJCannot update metadata on a Space that doesn't contain a `README.md` file.rnamerrFz6You passed a new value for the existing metric 'name: z, type: z6'. Set `overwrite=True` to overwrite existing metrics.Tz9You passed a new value for the existing meta data field 'z7'. Set `overwrite=True` to overwrite existing metadata.)rQrPrbrcrerdrf)rrrr4rWrryritemsgetattrr r&rrZis_equal_except_valuerrrrrappendgetri)rarrPrrQrbrcrdrerfZ card_classZcardkeyvaluerZ new_resultsZexisting_resultsZ new_resultZ result_foundZexisting_resultrrrmetadata_updatesxD        $  r)7rrepathlibrtypingrrr0Zhuggingface_hub.file_downloadrZhuggingface_hub.hf_apirZhuggingface_hub.repocard_datarrr r r r r Zhuggingface_hub.utilsrrrrrrBrerrorsrutilsrrrZ get_loggerr{r5__file__rHr~rcompiler,rrrrrLr$r3rrrrrrrrrs   $    *QA *