






'''simple docstring'''







from collections import Counter
from pathlib import Path
from typing import Optional, Tuple

import yaml

class _lowercase			(       yaml.SafeLoader	):




							def 	lowerCamelCase_       (							self:       str    ,							UpperCamelCase__:       Optional[int]  ):
														lowerCamelCase__      :			int 						= [self.constructed_objects[key_node] for key_node, _ in node.value]
														lowerCamelCase__      :			Optional[Any] 						= [tuple(UpperCamelCase__  ) if isinstance(UpperCamelCase__    ,							UpperCamelCase__  ) else key for key in keys]
														lowerCamelCase__      :			List[Any] 						= Counter(UpperCamelCase__  )
														lowerCamelCase__      :			int 						= [key for key in counter if counter[key] > 1]
														if duplicate_keys:
																					raise TypeError(F'''Got duplicate yaml keys: {duplicate_keys}'''  )




							def 	lowerCamelCase_       (							self:       Dict    ,							UpperCamelCase__:       Dict    ,							UpperCamelCase__:       List[str]=False  ):
														lowerCamelCase__      :			str 						= super().construct_mapping(UpperCamelCase__    ,							deep=UpperCamelCase__  )
														self._check_no_duplicates_on_constructed_node(UpperCamelCase__  )
														return mapping





def 				SCREAMING_SNAKE_CASE_ (UpperCamelCase   )   -> Tuple[Optional[str], str]:
							lowerCamelCase__      :			Dict 						= list(readme_content.splitlines()   )
							if full_content and full_content[0] == "---" and "---" in full_content[1:]:
														lowerCamelCase__      :			Any 						= full_content[1:].index("""---"""   ) + 1
														lowerCamelCase__      :			int 						= """\n""".join(full_content[1:sep_idx]   )
														return yamlblock, "\n".join(full_content[sep_idx + 1 :]   )

							return None, "\n".join(UpperCamelCase   )

class _lowercase			(       _lowercase	):
							# class attributes
							a          = {"""train_eval_index"""}  # train-eval-index in the YAML metadata




							@classmethod
							def 	lowerCamelCase_       (							cls:       List[str]    ,							UpperCamelCase__:       Path  ):
														with open(UpperCamelCase__    ,							encoding="""utf-8"""  ) as readme_file:
																					lowerCamelCase__						,	lowerCamelCase__      :			Union[str, Any] 						= _split_yaml_from_readme(readme_file.read()  )
														if yaml_string is not None:
																					return cls.from_yaml_string(UpperCamelCase__  )
														else:
																					return cls()




							def 	lowerCamelCase_       (							self:       List[str]    ,							UpperCamelCase__:       Path  ):
														if path.exists():
																					with open(UpperCamelCase__    ,							encoding="""utf-8"""  ) as readme_file:
																												lowerCamelCase__      :			List[str] 						= readme_file.read()
														else:
																					lowerCamelCase__      :			Optional[int] 						= None
														lowerCamelCase__      :			Union[str, Any] 						= self._to_readme(UpperCamelCase__  )
														with open(UpperCamelCase__    ,							"""w"""    ,							encoding="""utf-8"""  ) as readme_file:
																					readme_file.write(UpperCamelCase__  )




							def 	lowerCamelCase_       (							self:       List[str]    ,							UpperCamelCase__:       Optional[str] = None  ):
														if readme_content is not None:
																					lowerCamelCase__						,	lowerCamelCase__      :			Tuple 						= _split_yaml_from_readme(UpperCamelCase__  )
																					lowerCamelCase__      :			List[Any] 						= """---\n""" + self.to_yaml_string() + """---\n""" + content
														else:
																					lowerCamelCase__      :			Tuple 						= """---\n""" + self.to_yaml_string() + """---\n"""
														return full_content




							@classmethod
							def 	lowerCamelCase_       (							cls:       List[Any]    ,							UpperCamelCase__:       str  ):
														lowerCamelCase__      :			Tuple 						= yaml.load(UpperCamelCase__    ,							Loader=_NoDuplicateSafeLoader  ) or {}

														# Convert the YAML keys to DatasetMetadata fields
														lowerCamelCase__      :			List[str] 						= {
														    (key.replace("""-"""    ,							"""_"""  ) if key.replace("""-"""    ,							"""_"""  ) in cls._FIELDS_WITH_DASHES else key): value
														    for key, value in metadata_dict.items()
														}
														return cls(**UpperCamelCase__  )




							def 	lowerCamelCase_       (							self:       Optional[int]  ):
														return yaml.safe_dump(
														    {
														        (key.replace("""_"""    ,							"""-"""  ) if key in self._FIELDS_WITH_DASHES else key): value
														        for key, value in self.items()
														    }    ,							sort_keys=UpperCamelCase__    ,							allow_unicode=UpperCamelCase__    ,							encoding="""utf-8"""    ,							).decode("""utf-8"""  )



_A			:    List[Any]					  ={
    '''image-classification''': [],
    '''translation''': [],
    '''image-segmentation''': [],
    '''fill-mask''': [],
    '''automatic-speech-recognition''': [],
    '''token-classification''': [],
    '''sentence-similarity''': [],
    '''audio-classification''': [],
    '''question-answering''': [],
    '''summarization''': [],
    '''zero-shot-classification''': [],
    '''table-to-text''': [],
    '''feature-extraction''': [],
    '''other''': [],
    '''multiple-choice''': [],
    '''text-classification''': [],
    '''text-to-image''': [],
    '''text2text-generation''': [],
    '''zero-shot-image-classification''': [],
    '''tabular-classification''': [],
    '''tabular-regression''': [],
    '''image-to-image''': [],
    '''tabular-to-text''': [],
    '''unconditional-image-generation''': [],
    '''text-retrieval''': [],
    '''text-to-speech''': [],
    '''object-detection''': [],
    '''audio-to-audio''': [],
    '''text-generation''': [],
    '''conversational''': [],
    '''table-question-answering''': [],
    '''visual-question-answering''': [],
    '''image-to-text''': [],
    '''reinforcement-learning''': [],
    '''voice-activity-detection''': [],
    '''time-series-forecasting''': [],
    '''document-question-answering''': [],
}


if __name__ == "__main__":
			from argparse import ArgumentParser

			_A			:    Tuple					  =ArgumentParser(usage='''Validate the yaml metadata block of a README.md file.''')
			ap.add_argument('''readme_filepath''')
			_A			:    int					  =ap.parse_args()

			_A			:    Optional[Any]					  =Path(args.readme_filepath)
			_A			:    List[str]					  =DatasetMetadata.from_readme(readme_filepath)
			print(dataset_metadata)
			dataset_metadata.to_readme(readme_filepath)









'''simple docstring'''







import sys
import turtle





def 				SCREAMING_SNAKE_CASE_ (UpperCamelCase       ,    UpperCamelCase   )   -> tuple[float, float]:
							return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2





def 				SCREAMING_SNAKE_CASE_ (UpperCamelCase       ,    UpperCamelCase       ,    UpperCamelCase       ,    UpperCamelCase       ,    )   -> None:
							my_pen.up()
							my_pen.goto(vertexa[0]       ,    vertexa[1]   )
							my_pen.down()
							my_pen.goto(vertexa[0]       ,    vertexa[1]   )
							my_pen.goto(vertexa[0]       ,    vertexa[1]   )
							my_pen.goto(vertexa[0]       ,    vertexa[1]   )

							if depth == 0:
														return

							triangle(UpperCamelCase       ,    get_mid(UpperCamelCase       ,    UpperCamelCase   )       ,    get_mid(UpperCamelCase       ,    UpperCamelCase   )       ,    depth - 1   )
							triangle(UpperCamelCase       ,    get_mid(UpperCamelCase       ,    UpperCamelCase   )       ,    get_mid(UpperCamelCase       ,    UpperCamelCase   )       ,    depth - 1   )
							triangle(UpperCamelCase       ,    get_mid(UpperCamelCase       ,    UpperCamelCase   )       ,    get_mid(UpperCamelCase       ,    UpperCamelCase   )       ,    depth - 1   )


if __name__ == "__main__":
			if len(sys.argv) != 2:
						raise ValueError(
						    '''Correct format for using this script: '''
						    '''python fractals.py <int:depth_for_fractal>'''
						)
			_A			:    Any					  =turtle.Turtle()
			my_pen.ht()
			my_pen.speed(5)
			my_pen.pencolor('''red''')

			_A			:    Dict					  =[(-175, -125), (0, 175), (175, -125)]  # vertices of triangle
			triangle(vertices[0], vertices[1], vertices[2], int(sys.argv[1]))

