

import warnings

from ...utils import logging
from .image_processing_detr import DetrImageProcessor


lowercase_									=    logging.get_logger(__name__)


class 					A		(				_UpperCAmelCase					):







    """simple docstring"""





    def __init__( self					:			Any,*lowercase_					:			Any,**lowercase_					:			Any						)->       None:





        '''simple docstring'''







        warnings.warn(
            'The class DetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
            ' Please use DetrImageProcessor instead.',lowercase_,)
        super().__init__(*lowercase_,**lowercase_						)




import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata
def 		_snake_case(       SCREAMING_SNAKE_CASE__     :      str )				-> str:





    '''simple docstring'''






    A__        =  min(re.search('^ +'       ,     SCREAMING_SNAKE_CASE__ ).end() if t.startswith(' ' ) else 0 for t in string.splitlines() )
    return "\n".join([line[indent_level:] for line in string.splitlines() if indent_level < len(SCREAMING_SNAKE_CASE__ )] )


lowercase_									=    "\\n---\nlanguage:\n- zh\n- en\ntask_ids:\n- sentiment-classification\n---\n# Begin of markdown\n\nSome cool dataset card\n"

lowercase_									=    "\\n---\n---\n# Begin of markdown\n\nSome cool dataset card\n"


lowercase_									=    "\\n# Begin of markdown\n\nSome cool dataset card\n"


class 					A		(				unittest.TestCase					):







    """simple docstring"""





    def 		snake_case__	( self					:			List[Any]						)->       str:





        '''simple docstring'''







        with tempfile.TemporaryDirectory() as tmp_dir:
            A__        =  Path(lowercase_						) / 'README.md'
            with open(lowercase_,'w+'						) as readme_file:
                readme_file.write(lowercase_						)
            A__        =  DatasetMetadata.from_readme(lowercase_						)
            self.assertDictEqual(lowercase_,{'language': ['zh', 'en'], 'task_ids': ['sentiment-classification']}						)

            with open(lowercase_,'w+'						) as readme_file:
                readme_file.write(lowercase_						)
            A__        =  DatasetMetadata.from_readme(lowercase_						)
            self.assertDictEqual(lowercase_,{}						)

            with open(lowercase_,'w+'						) as readme_file:
                readme_file.write(lowercase_						)
            A__        =  DatasetMetadata.from_readme(lowercase_						)
            self.assertEqual(lowercase_,{}						)


    def 		snake_case__	( self					:			Tuple						)->       List[Any]:





        '''simple docstring'''







        A__        =  _dedent(
            '\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            '						)
        assert DatasetMetadata.from_yaml_string(lowercase_						)

        A__        =  _dedent(
            '\\n            annotations_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - question-answering\n            task_ids:\n            - open-domain-qa\n            task_ids:\n            - open-domain-qa\n            '						)
        with self.assertRaises(lowercase_						):
            DatasetMetadata.from_yaml_string(lowercase_						)

        A__        =  _dedent(
            '\\n            annotations_creators:\n            - found\n            language_creators:\n            - found\n            language:\n            - en\n            license:\n            - unknown\n            multilinguality:\n            - monolingual\n            pretty_name: Test Dataset\n            size_categories:\n            - 10K<n<100K\n            source_datasets:\n            - extended|other-yahoo-webscope-l6\n            task_categories:\n            - text-classification\n            task_ids:\n            - multi-class-classification\n            paperswithcode_id:\n            - squad\n            configs:\n            - en\n            train-eval-index:\n            - config: en\n              task: text-classification\n              task_id: multi_class_classification\n              splits:\n                train_split: train\n                eval_split: test\n              col_mapping:\n                text: text\n                label: target\n              metrics:\n                - type: accuracy\n                  name: Accuracy\n            extra_gated_prompt: |\n              By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n              [RESEARCHER_FULLNAME] (the "Researcher") has requested permission to use the ImageNet database (the "Database") at Princeton University and Stanford University. In exchange for such permission, Researcher hereby agrees to the following terms and conditions:\n              1. Researcher shall use the Database only for non-commercial research and educational purposes.\n            extra_gated_fields:\n              Company: text\n              Country: text\n              I agree to use this model for non-commerical use ONLY: checkbox\n            '						)
        assert DatasetMetadata.from_yaml_string(lowercase_						)

