

import re
import tempfile
import unittest
from pathlib import Path

from datasets.utils.metadata import DatasetMetadata


def  __a    (				SCREAMING_SNAKE_CASE ) ->       str:






    '''simple docstring'''
    __UpperCAmelCase			   =     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 )] )


A_						:     Union[str, Any]			  =				'\\n---\nlanguage:\n- zh\n- en\ntask_ids:\n- sentiment-classification\n---\n# Begin of markdown\n\nSome cool dataset card\n'

A_						:     List[Any]			  =				'\\n---\n---\n# Begin of markdown\n\nSome cool dataset card\n'


A_						:     Dict			  =				'\\n# Begin of markdown\n\nSome cool dataset card\n'
class    A_				( unittest.TestCase  ):


    '''simple docstring'''






    def        lowerCAmelCase_  (self					)       -> Any:
        with tempfile.TemporaryDirectory() as tmp_dir:
            __UpperCAmelCase			   =     Path(lowercase__					) / '''README.md'''
            with open(lowercase__       , '''w+'''					) as readme_file:
                readme_file.write(lowercase__					)
            __UpperCAmelCase			   =     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__					)
            __UpperCAmelCase			   =     DatasetMetadata.from_readme(lowercase__					)
            self.assertDictEqual(lowercase__       , {}					)

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






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

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

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







import warnings

from ...utils import logging
from .image_processing_convnext import ConvNextImageProcessor


A_						:     int			  =				logging.get_logger(__name__)
class    A_				( _a  ):


    '''simple docstring'''






    def __init__(self       , *lowercase__       , **lowercase__					)       -> None:
        warnings.warn(
            '''The class ConvNextFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
            ''' Please use ConvNextImageProcessor instead.'''       , lowercase__       , )
        super().__init__(*lowercase__       , **lowercase__					)




