
    gc              	          d dl Z d dlmZ d dlmZ d dlmZmZmZm	Z	m
Z
mZ d dlmZmZ  ej        e          Ze G d d                      Ze G d d	                      Z G d
 de          Z G d de          Z G d de          Zdeeeef                  de
eee         f         fdZd Zdedee         deeeef                  fdZde	ee                  de	ee                  fdZdS )    N)defaultdict)	dataclass)AnyDictListOptionalTupleUnion)logging	yaml_dumpc                      e Zd ZU dZeed<   eed<   eed<   eed<   eed<   dZee         ed<   dZ	ee         ed	<   dZ
ee         ed
<   dZee         ed<   dZeeeef                  ed<   dZee         ed<   dZee         ed<   dZeeeef                  ed<   dZee         ed<   dZee         ed<   dZee         ed<   dZee         ed<   edefd            Zdd defdZddZdS )
EvalResultu  
    Flattened representation of individual evaluation results found in model-index of Model Cards.

    For more information on the model-index spec, see https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1.

    Args:
        task_type (`str`):
            The task identifier. Example: "image-classification".
        dataset_type (`str`):
            The dataset identifier. Example: "common_voice". Use dataset id from https://hf.co/datasets.
        dataset_name (`str`):
            A pretty name for the dataset. Example: "Common Voice (French)".
        metric_type (`str`):
            The metric identifier. Example: "wer". Use metric id from https://hf.co/metrics.
        metric_value (`Any`):
            The metric value. Example: 0.9 or "20.0 ± 1.2".
        task_name (`str`, *optional*):
            A pretty name for the task. Example: "Speech Recognition".
        dataset_config (`str`, *optional*):
            The name of the dataset configuration used in `load_dataset()`.
            Example: fr in `load_dataset("common_voice", "fr")`. See the `datasets` docs for more info:
            https://hf.co/docs/datasets/package_reference/loading_methods#datasets.load_dataset.name
        dataset_split (`str`, *optional*):
            The split used in `load_dataset()`. Example: "test".
        dataset_revision (`str`, *optional*):
            The revision (AKA Git Sha) of the dataset used in `load_dataset()`.
            Example: 5503434ddd753f426f4b38109466949a1217c2bb
        dataset_args (`Dict[str, Any]`, *optional*):
            The arguments passed during `Metric.compute()`. Example for `bleu`: `{"max_order": 4}`
        metric_name (`str`, *optional*):
            A pretty name for the metric. Example: "Test WER".
        metric_config (`str`, *optional*):
            The name of the metric configuration used in `load_metric()`.
            Example: bleurt-large-512 in `load_metric("bleurt", "bleurt-large-512")`.
            See the `datasets` docs for more info: https://huggingface.co/docs/datasets/v2.1.0/en/loading#load-configurations
        metric_args (`Dict[str, Any]`, *optional*):
            The arguments passed during `Metric.compute()`. Example for `bleu`: max_order: 4
        verified (`bool`, *optional*):
            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.
        verify_token (`str`, *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.
        source_name (`str`, *optional*):
            The name of the source of the evaluation result. Example: "Open LLM Leaderboard".
        source_url (`str`, *optional*):
            The URL of the source of the evaluation result. Example: "https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard".
    	task_typedataset_typedataset_namemetric_typemetric_valueN	task_namedataset_configdataset_splitdataset_revisiondataset_argsmetric_namemetric_configmetric_argsverifiedverify_tokensource_name
source_urlreturnc                 B    | j         | j        | j        | j        | j        fS )z9Returns a tuple that uniquely identifies this evaluation.)r   r   r   r   r   selfs    Y/var/www/html/ai-engine/env/lib/python3.11/site-packages/huggingface_hub/repocard_data.pyunique_identifierzEvalResult.unique_identifier   s+     N!
 	
    otherc                     | j                                         D ]7\  }}|dk    r|dk    r%t          | |          t          ||          k    r dS 8dS )zx
        Return True if `self` and `other` describe exactly the same metric but with a
        different value.
        r   r   FT)__dict__itemsgetattr)r#   r'   key_s       r$   is_equal_except_valuez EvalResult.is_equal_except_value   sk    
 m))++ 	 	FCn$$ n$$s););wuc?R?R)R)Ruutr&   c                 D    | j         | j        t          d          d S d S )NzAIf `source_name` is provided, `source_url` must also be provided.)r   r   
ValueErrorr"   s    r$   __post_init__zEvalResult.__post_init__   s/    'DO,C`aaa (',C,Cr&   )r    N)__name__
__module____qualname____doc__str__annotations__r   r   r   r   r   r   r   r   r   r   r   r   boolr   r   r   propertytupler%   r.   r1    r&   r$   r   r      s        - -f NNN      $Ix}### %)NHSM((( $(M8C=''' '+hsm*** .2L(4S>*111 "&K#%%%
 $(M8C=''' -1K$sCx.)000  $Hhtn### #'L(3-&&& "&K#%%% !%J$$$
5 
 
 
 X
< D    b b b b b br&   r   c                       e Zd ZdZddefdZd Zd Zddee	e
                  d	e
fd
Zd Zd Zdde
ded	efdZdde
ded	efdZde
d	efdZde
ded	dfdZde
d	efdZd	efdZdS )CardDataa  Structure containing metadata from a RepoCard.

    [`CardData`] is the parent class of [`ModelCardData`] and [`DatasetCardData`].

    Metadata can be exported as a dictionary or YAML. Export can be customized to alter the representation of the data
    (example: flatten evaluation results). `CardData` behaves as a dictionary (can get, pop, set values) but do not
    inherit from `dict` to allow this export step.
    Fignore_metadata_errorsc                 :    | j                             |           d S N)r)   update)r#   r>   kwargss      r$   __init__zCardData.__init__   s    V$$$$$r&   c                 |    t          j        | j                  }|                     |           t	          |          S )zConverts CardData to a dict.

        Returns:
            `dict`: CardData represented as a dictionary ready to be dumped to a YAML
            block for inclusion in a README.md file.
        )copydeepcopyr)   _to_dict_remove_noner#   	data_dicts     r$   to_dictzCardData.to_dict   s5     M$-00	i   I&&&r&   c                     dS )zUse this method in child classes to alter the dict representation of the data. Alter the dict in-place.

        Args:
            data_dict (`dict`): The raw dict representation of the card data.
        Nr;   rI   s     r$   rG   zCardData._to_dict   s	     	r&   Noriginal_orderr    c                 "    |rW fd|t          t           j                                                  t          |          z
            z   D              _        t	                                           d|                                          S )a
  Dumps CardData to a YAML block for inclusion in a README.md file.

        Args:
            line_break (str, *optional*):
                The line break to use when dumping to yaml.

        Returns:
            `str`: CardData represented as a YAML block.
        c                 >    i | ]}|j         v |j         |         S r;   r)   ).0kr#   s     r$   
<dictcomp>z$CardData.to_yaml.<locals>.<dictcomp>   s9       %% 4=#%%%r&   F)	sort_keys
line_break)listsetr)   keysr   rK   strip)r#   rU   rM   s   `  r$   to_yamlzCardData.to_yaml   s      	   '$s4=3E3E3G3G/H/H3~K^K^/^*_*__  DM
 5ZPPPVVXXXr&   c                 *    t          | j                  S r@   )reprr)   r"   s    r$   __repr__zCardData.__repr__   s    DM"""r&   c                 *    |                                  S r@   )rZ   r"   s    r$   __str__zCardData.__str__   s    ||~~r&   r,   defaultc                 8    | j                             ||          S z#Get value for a given metadata key.)r)   getr#   r,   r`   s      r$   rc   zCardData.get       }  g...r&   c                 8    | j                             ||          S )z#Pop value for a given metadata key.)r)   poprd   s      r$   rg   zCardData.pop   re   r&   c                     | j         |         S rb   rP   r#   r,   s     r$   __getitem__zCardData.__getitem__   s    }S!!r&   valuec                     || j         |<   dS )z#Set value for a given metadata key.NrP   )r#   r,   rk   s      r$   __setitem__zCardData.__setitem__   s    "cr&   c                     || j         v S )z%Check if a given metadata key is set.rP   ri   s     r$   __contains__zCardData.__contains__   s    dm##r&   c                 *    t          | j                  S )z'Return the number of metadata keys set.)lenr)   r"   s    r$   __len__zCardData.__len__   s    4=!!!r&   )F)NNr@   )r2   r3   r4   r5   r8   rC   rK   rG   r   r   r6   rZ   r]   r_   r   rc   rg   rj   rm   ro   intrr   r;   r&   r$   r=   r=      s        % %t % % % %
' 
' 
'  Y YxS	7J YVY Y Y Y Y$# # #  / /s /S /C / / / // /s /S /C / / / /"s "s " " " "#s #3 #4 # # # #$ $ $ $ $ $" " " " " " "r&   r=   c                   t    e Zd ZdZdddddddddddddddeeeee         f                  deee                  deee                  deeeee         f                  d	ee         d
ee         dee         dee         deee                  dee         dee         deee                  de	f fdZ
d Z xZS )ModelCardDataa:  Model Card Metadata that is used by Hugging Face Hub when included at the top of your README.md

    Args:
        base_model (`str` or `List[str]`, *optional*):
            The identifier of the base model from which the model derives. This is applicable for example if your model is a
            fine-tune or adapter of an existing model. The value must be the ID of a model on the Hub (or a list of IDs
            if your model derives from multiple models). Defaults to None.
        datasets (`List[str]`, *optional*):
            List of datasets that were used to train this model. Should be a dataset ID
            found on https://hf.co/datasets. Defaults to None.
        eval_results (`Union[List[EvalResult], EvalResult]`, *optional*):
            List of `huggingface_hub.EvalResult` that define evaluation results of the model. If provided,
            `model_name` is used to as a name on PapersWithCode's leaderboards. Defaults to `None`.
        language (`Union[str, List[str]]`, *optional*):
            Language of model's training data or metadata. It must be an ISO 639-1, 639-2 or
            639-3 code (two/three letters), or a special value like "code", "multilingual". Defaults to `None`.
        library_name (`str`, *optional*):
            Name of library used by this model. Example: keras or any library from
            https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/src/model-libraries.ts.
            Defaults to None.
        license (`str`, *optional*):
            License of this model. Example: apache-2.0 or any license from
            https://huggingface.co/docs/hub/repositories-licenses. Defaults to None.
        license_name (`str`, *optional*):
            Name of the license of this model. Defaults to None. To be used in conjunction with `license_link`.
            Common licenses (Apache-2.0, MIT, CC-BY-SA-4.0) do not need a name. In that case, use `license` instead.
        license_link (`str`, *optional*):
            Link to the license of this model. Defaults to None. To be used in conjunction with `license_name`.
            Common licenses (Apache-2.0, MIT, CC-BY-SA-4.0) do not need a link. In that case, use `license` instead.
        metrics (`List[str]`, *optional*):
            List of metrics used to evaluate this model. Should be a metric name that can be found
            at https://hf.co/metrics. Example: 'accuracy'. Defaults to None.
        model_name (`str`, *optional*):
            A name for this model. It is used along with
            `eval_results` to construct the `model-index` within the card's metadata. The name
            you supply here is what will be used on PapersWithCode's leaderboards. If None is provided
            then the repo name is used as a default. Defaults to None.
        pipeline_tag (`str`, *optional*):
            The pipeline tag associated with the model. Example: "text-classification".
        tags (`List[str]`, *optional*):
            List of tags to add to your model that can be used when filtering on the Hugging
            Face Hub. Defaults to None.
        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.
        kwargs (`dict`, *optional*):
            Additional metadata that will be added to the model card. Defaults to None.

    Example:
        ```python
        >>> from huggingface_hub import ModelCardData
        >>> card_data = ModelCardData(
        ...     language="en",
        ...     license="mit",
        ...     library_name="timm",
        ...     tags=['image-classification', 'resnet'],
        ... )
        >>> card_data.to_dict()
        {'language': 'en', 'license': 'mit', 'library_name': 'timm', 'tags': ['image-classification', 'resnet']}

        ```
    NF)
base_modeldatasetseval_resultslanguagelibrary_namelicenselicense_namelicense_linkmetrics
model_namepipeline_tagtagsr>   rv   rw   rx   ry   rz   r{   r|   r}   r~   r   r   r   r>   c                   || _         || _        || _        || _        || _        || _        || _        || _        |	| _        |
| _	        || _
        t          |          | _        |                    dd           }|rx	 t          |          \  }
}|
| _	        || _        nV# t          t           f$ rB}|rt"                              d           nt'          d|j         d| d          Y d }~nd }~ww xY w t+                      j        di | | j        r=t/          | j        t0                    r| j        g| _        | j	        t'          d          d S d S )Nmodel-indexz<Invalid model-index. Not loading eval results into CardData.z4Invalid `model_index` in metadata cannot be parsed:  z. Pass `ignore_metadata_errors=True` to ignore this error while loading a Model Card. Warning: some information will be lost. Use it at your own risk.z7Passing `eval_results` requires `model_name` to be set.r;   )rv   rw   rx   ry   rz   r{   r|   r}   r~   r   r   _to_unique_listr   rg   model_index_to_eval_resultsKeyError	TypeErrorloggerwarningr0   	__class__superrC   
isinstancer   )r#   rv   rw   rx   ry   rz   r{   r|   r}   r~   r   r   r   r>   rB   model_indexerrorr   s                    r$   rC   zModelCardData.__init__7  s   $ % ( ((($(#D))	jj55 	+F{+S+S(
L",$0!!i(   ) NN#abbbb$Su S Saf S S S   cbbbb 	""6""" 	\$+Z88 8%)%6$7!& !Z[[[		\ 	\ '&s   < B C0.8C++C0c                 ^    | j         %t          | j        | j                   |d<   |d= |d= dS dS )z[Format the internal data dict. In this case, we convert eval results to a valid model indexNr   rx   r   )rx   eval_results_to_model_indexr   rI   s     r$   rG   zModelCardData._to_dictn  sB    ('B4?TXTe'f'fIm$.)9\+B+B+B )(r&   )r2   r3   r4   r5   r   r
   r6   r   r   r8   rC   rG   __classcell__r   s   @r$   ru   ru      s       = =D 7;(,3748&*!%&*&*'+$(&*$(',5\ 5\ 5\ U3S	>235\ 49%	5\
 tJ/05\ 5d3i015\ sm5\ #5\ sm5\ sm5\ $s)$5\ SM5\ sm5\ tCy!5\ !%5\ 5\ 5\ 5\ 5\ 5\nC C C C C C Cr&   ru   c                   &    e Zd ZdZddddddddddddddddeeeee         f                  deeeee         f                  deeeee         f                  deeeee         f                  d	eeeee         f                  d
eeeee         f                  deee                  deeeee         f                  deeeee         f                  dee         dee         dee         deeeee         f                  de	f fdZ
d Z xZS )DatasetCardDataa	  Dataset Card Metadata that is used by Hugging Face Hub when included at the top of your README.md

    Args:
        language (`List[str]`, *optional*):
            Language of dataset's data or metadata. It must be an ISO 639-1, 639-2 or
            639-3 code (two/three letters), or a special value like "code", "multilingual".
        license (`Union[str, List[str]]`, *optional*):
            License(s) of this dataset. Example: apache-2.0 or any license from
            https://huggingface.co/docs/hub/repositories-licenses.
        annotations_creators (`Union[str, List[str]]`, *optional*):
            How the annotations for the dataset were created.
            Options are: 'found', 'crowdsourced', 'expert-generated', 'machine-generated', 'no-annotation', 'other'.
        language_creators (`Union[str, List[str]]`, *optional*):
            How the text-based data in the dataset was created.
            Options are: 'found', 'crowdsourced', 'expert-generated', 'machine-generated', 'other'
        multilinguality (`Union[str, List[str]]`, *optional*):
            Whether the dataset is multilingual.
            Options are: 'monolingual', 'multilingual', 'translation', 'other'.
        size_categories (`Union[str, List[str]]`, *optional*):
            The number of examples in the dataset. Options are: 'n<1K', '1K<n<10K', '10K<n<100K',
            '100K<n<1M', '1M<n<10M', '10M<n<100M', '100M<n<1B', '1B<n<10B', '10B<n<100B', '100B<n<1T', 'n>1T', and 'other'.
        source_datasets (`List[str]]`, *optional*):
            Indicates whether the dataset is an original dataset or extended from another existing dataset.
            Options are: 'original' and 'extended'.
        task_categories (`Union[str, List[str]]`, *optional*):
            What categories of task does the dataset support?
        task_ids (`Union[str, List[str]]`, *optional*):
            What specific tasks does the dataset support?
        paperswithcode_id (`str`, *optional*):
            ID of the dataset on PapersWithCode.
        pretty_name (`str`, *optional*):
            A more human-readable name for the dataset. (ex. "Cats vs. Dogs")
        train_eval_index (`Dict`, *optional*):
            A dictionary that describes the necessary spec for doing evaluation on the Hub.
            If not provided, it will be gathered from the 'train-eval-index' key of the kwargs.
        config_names (`Union[str, List[str]]`, *optional*):
            A list of the available dataset configs for the dataset.
    NF)ry   r{   annotations_creatorslanguage_creatorsmultilingualitysize_categoriessource_datasetstask_categoriestask_idspaperswithcode_idpretty_nametrain_eval_indexconfig_namesr>   ry   r{   r   r   r   r   r   r   r   r   r   r   r   r>   c                   || _         || _        || _        || _        || _        || _        || _        || _        |	| _        |
| _	        || _
        || _        |p|                    dd           | _         t                      j        di | d S )Ntrain-eval-indexr;   )r   r   ry   r{   r   r   r   r   r   r   r   r   rg   r   r   rC   )r#   ry   r{   r   r   r   r   r   r   r   r   r   r   r   r>   rB   r   s                   r$   rC   zDatasetCardData.__init__  s    & %9!!2 .... !2&( !1 XFJJ?QSW4X4X""6"""""r&   c                 6    |                     d          |d<   d S )Nr   r   )rg   rI   s     r$   rG   zDatasetCardData._to_dict  s     (16H(I(I	$%%%r&   )r2   r3   r4   r5   r   r
   r6   r   r   r8   rC   rG   r   r   s   @r$   r   r   u  s       % %T 5937@D=A;?;?/3;?48+/%)+/8<',!"# "# "# 5d3i01"# %T#Y/0	"#
 'uS$s)^'<="# $E#tCy.$9:"# "%T#Y"78"# "%T#Y"78"# "$s),"# "%T#Y"78"# 5d3i01"# $C="# c]"# #4."# uS$s)^45"#  !%!"# "# "# "# "# "#HJ J J J J J Jr&   r   c                       e Zd ZdZddddddddddddddee         dee         dee         dee         d	ee         d
ee         dee         dee         deee                  deee                  deee                  def fdZ	 xZ
S )SpaceCardDataa	  Space Card Metadata that is used by Hugging Face Hub when included at the top of your README.md

    To get an exhaustive reference of Spaces configuration, please visit https://huggingface.co/docs/hub/spaces-config-reference#spaces-configuration-reference.

    Args:
        title (`str`, *optional*)
            Title of the Space.
        sdk (`str`, *optional*)
            SDK of the Space (one of `gradio`, `streamlit`, `docker`, or `static`).
        sdk_version (`str`, *optional*)
            Version of the used SDK (if Gradio/Streamlit sdk).
        python_version (`str`, *optional*)
            Python version used in the Space (if Gradio/Streamlit sdk).
        app_file (`str`, *optional*)
            Path to your main application file (which contains either gradio or streamlit Python code, or static html code).
            Path is relative to the root of the repository.
        app_port (`str`, *optional*)
            Port on which your application is running. Used only if sdk is `docker`.
        license (`str`, *optional*)
            License of this model. Example: apache-2.0 or any license from
            https://huggingface.co/docs/hub/repositories-licenses.
        duplicated_from (`str`, *optional*)
            ID of the original Space if this is a duplicated Space.
        models (List[`str`], *optional*)
            List of models related to this Space. Should be a dataset ID found on https://hf.co/models.
        datasets (`List[str]`, *optional*)
            List of datasets related to this Space. Should be a dataset ID found on https://hf.co/datasets.
        tags (`List[str]`, *optional*)
            List of tags to add to your Space that can be used when filtering on the Hub.
        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.
        kwargs (`dict`, *optional*):
            Additional metadata that will be added to the space card.

    Example:
        ```python
        >>> from huggingface_hub import SpaceCardData
        >>> card_data = SpaceCardData(
        ...     title="Dreambooth Training",
        ...     license="mit",
        ...     sdk="gradio",
        ...     duplicated_from="multimodalart/dreambooth-training"
        ... )
        >>> card_data.to_dict()
        {'title': 'Dreambooth Training', 'sdk': 'gradio', 'license': 'mit', 'duplicated_from': 'multimodalart/dreambooth-training'}
        ```
    NF)titlesdksdk_versionpython_versionapp_fileapp_portr{   duplicated_frommodelsrw   r   r>   r   r   r   r   r   r   r{   r   r   rw   r   r>   c                    || _         || _        || _        || _        || _        || _        || _        || _        |	| _        |
| _	        t          |          | _         t                      j        di | d S )Nr;   )r   r   r   r   r   r   r{   r   r   rw   r   r   r   rC   )r#   r   r   r   r   r   r   r{   r   r   rw   r   r>   rB   r   s                 r$   rC   zSpaceCardData.__init__  s    " 
&,  . #D))	""6"""""r&   )r2   r3   r4   r5   r   r6   rs   r   r8   rC   r   r   s   @r$   r   r     s+       / /h  $!%)(,"&"&!%)-&*(,$(',# # # }# c]	#
 c]# !# 3-# 3-# ## "## c## 49%# tCy!# !%# # # # # # # # # #r&   r   r   r    c           	         g }| D ]}|d         }|d         }|D ]}|d         d         }|d                              d          }|d         d         }|d         d         }	|d                              d          }
|d                              d          }|d                              d          }|d                              d	          }|                     d
i                                d          }|                     d
i                                d          }|d         D ]}|d         }|d         }|                     d          }|                     d	          }|                     d          }|                     d          }|                     d          }t          d i d|d|d|	d|d|d|d|
d|d|d|d|d|d|d|d|d|d|}|                    |           ΐސ||fS )!a  Takes in a model index and returns the model name and a list of `huggingface_hub.EvalResult` objects.

    A detailed spec of the model index can be found here:
    https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1

    Args:
        model_index (`List[Dict[str, Any]]`):
            A model index data structure, likely coming from a README.md file on the
            Hugging Face Hub.

    Returns:
        model_name (`str`):
            The name of the model as found in the model index. This is used as the
            identifier for the model on leaderboards like PapersWithCode.
        eval_results (`List[EvalResult]`):
            A list of `huggingface_hub.EvalResult` objects containing the metrics
            reported in the provided model_index.

    Example:
        ```python
        >>> from huggingface_hub.repocard_data import model_index_to_eval_results
        >>> # Define a minimal model index
        >>> model_index = [
        ...     {
        ...         "name": "my-cool-model",
        ...         "results": [
        ...             {
        ...                 "task": {
        ...                     "type": "image-classification"
        ...                 },
        ...                 "dataset": {
        ...                     "type": "beans",
        ...                     "name": "Beans"
        ...                 },
        ...                 "metrics": [
        ...                     {
        ...                         "type": "accuracy",
        ...                         "value": 0.9
        ...                     }
        ...                 ]
        ...             }
        ...         ]
        ...     }
        ... ]
        >>> model_name, eval_results = model_index_to_eval_results(model_index)
        >>> model_name
        'my-cool-model'
        >>> eval_results[0].task_type
        'image-classification'
        >>> eval_results[0].metric_type
        'accuracy'

        ```
    nameresultstasktypedatasetconfigsplitrevisionargssourceurlr~   rk   r   verifyTokenr   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r;   )rc   r   append)r   rx   elemr   r   resultr   r   r   r   r   r   r   r   r   r   metricr   r   r   r   r   r   r   eval_results                            r$   r   r     s   p L +1 +1F|y/ (	1 (	1Fvv.Iv**622I!),V4L!),V4L#I.228<<N"9-11'::M%i044Z@@!),0088L **Xr2266v>>KHb1155e<<J + 1 1$Vn%g$jj00$jj00 &

8 4 4!::j11%zz-88(   'i!- ". !,	
 ". (i $2> #0- &6%5 ". !, !, #0- &X ".  !,!"  *z#& ##K000091(	1R r&   c                     t          | t          t          t          f          r" t	          |           d | D                       S t          | t
                    r4 t	          |           d |                                 D                       S | S )zk
    Recursively remove `None` values from a dict. Borrowed from: https://stackoverflow.com/a/20558778
    c              3   8   K   | ]}|t          |          V  d S r@   rH   )rQ   xs     r$   	<genexpr>z_remove_none.<locals>.<genexpr>  s(      GGQaGGr&   c              3   `   K   | ])\  }}||	t          |          t          |          fV  *d S r@   r   )rQ   rR   vs      r$   r   z_remove_none.<locals>.<genexpr>  sC      ww1WXWdijiv,q//<??;ivivivivwwr&   )r   rV   r:   rW   r   dictr*   )objs    r$   rH   rH   ~  s     #eS)** tCyyGG#GGGGGG	C		 tCyyww		wwwwww
r&   r   rx   c           	         t          t                    }|D ]"}||j                                     |           #g }|                                D ]}|d         }|j        |j        d|j        |j        |j	        |j
        |j        |j        dd |D             d}|j        d|j        i}|j        
|j        |d<   ||d	<   |                    |           | |d
g}	t          |	          S )a  Takes in given model name and list of `huggingface_hub.EvalResult` and returns a
    valid model-index that will be compatible with the format expected by the
    Hugging Face Hub.

    Args:
        model_name (`str`):
            Name of the model (ex. "my-cool-model"). This is used as the identifier
            for the model on leaderboards like PapersWithCode.
        eval_results (`List[EvalResult]`):
            List of `huggingface_hub.EvalResult` objects containing the metrics to be
            reported in the model-index.

    Returns:
        model_index (`List[Dict[str, Any]]`): The eval_results converted to a model-index.

    Example:
        ```python
        >>> from huggingface_hub.repocard_data import eval_results_to_model_index, EvalResult
        >>> # Define minimal eval_results
        >>> eval_results = [
        ...     EvalResult(
        ...         task_type="image-classification",  # Required
        ...         dataset_type="beans",  # Required
        ...         dataset_name="Beans",  # Required
        ...         metric_type="accuracy",  # Required
        ...         metric_value=0.9,  # Required
        ...     )
        ... ]
        >>> eval_results_to_model_index("my-cool-model", eval_results)
        [{'name': 'my-cool-model', 'results': [{'task': {'type': 'image-classification'}, 'dataset': {'name': 'Beans', 'type': 'beans'}, 'metrics': [{'type': 'accuracy', 'value': 0.9}]}]}]

        ```
    r   )r   r   )r   r   r   r   r   r   c           
      h    g | ]/}|j         |j        |j        |j        |j        |j        |j        d 0S ))r   rk   r   r   r   r   r   )r   r   r   r   r   r   r   )rQ   r   s     r$   
<listcomp>z/eval_results_to_model_index.<locals>.<listcomp>  sZ         #.#0".$2". &#)#6   r&   )r   r   r~   Nr   r   r   )r   r   )r   rV   r%   r   valuesr   r   r   r   r   r   r   r   r   r   rH   )
r   rx   task_and_ds_types_mapr   model_index_datar   sample_resultdatar   r   s
             r$   r   r     s\   J :ET9J9J# Q Qk;<CCKPPPP (//11 $& $&
 &/%/ 
 &2%2'6&4):%2   &  
 
4 #/}/F (4!.!:v#DN%%%% '	
 	
K $$$r&   r   c                 N    | | S g }| D ]}||vr|                     |           |S r@   )r   )r   unique_tagstags      r$   r   r     sF    |K $ $k!!s###r&   )rE   collectionsr   dataclassesr   typingr   r   r   r   r	   r
   huggingface_hub.utilsr   r   
get_loggerr2   r   r   r=   ru   r   r   r6   r   rH   r   r   r;   r&   r$   <module>r      s    # # # # # # ! ! ! ! ! ! : : : : : : : : : : : : : : : : 4 4 4 4 4 4 4 4 
	H	%	% Tb Tb Tb Tb Tb Tb Tb Tbn O" O" O" O" O" O" O" O"d{C {C {C {C {CH {C {C {C|MJ MJ MJ MJ MJh MJ MJ MJ`N# N# N# N# N#H N# N# N#beT$sCx.-A eeCQUV`QaLaFb e e e eP	 	 	Y%C Y%tJ?O Y%TXY]^acf^fYgTh Y% Y% Y% Y%x(49- (492E      r&   