


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

import yaml



class 				A       (			yaml.SafeLoader				):
					'''simple docstring'''






					def     lowerCamelCase__	(self       :		Tuple ,   _UpperCAmelCase       :		Optional[int]						)		->  Union[str, Any]:




							"""simple docstring"""


							lowercase__	     =						[self.constructed_objects[key_node] for key_node, _ in node.value]
							lowercase__	     =						[tuple(lowerCAmelCase__						) if isinstance(lowerCAmelCase__ ,   lowerCAmelCase__						) else key for key in keys]
							lowercase__	     =						Counter(lowerCAmelCase__						)
							lowercase__	     =						[key for key in counter if counter[key] > 1]
							if duplicate_keys:
									raise TypeError(f'''Got duplicate yaml keys: {duplicate_keys}'''						)


					def     lowerCamelCase__	(self       :		str ,   _UpperCAmelCase       :		List[str] ,   _UpperCAmelCase       :		Optional[Any]=False						)		->  List[Any]:




							"""simple docstring"""


							lowercase__	     =						super().construct_mapping(lowerCAmelCase__ ,   deep=lowerCAmelCase__						)
							self._check_no_duplicates_on_constructed_node(lowerCAmelCase__						)
							return mapping






def 					UpperCamelCase   (      __magic_name__	:				List[Any]	)  ->    Any:
		"""simple docstring"""




		lowercase__	     =						list(readme_content.splitlines()	)
		if full_content and full_content[0] == "---" and "---" in full_content[1:]:
				lowercase__	     =						full_content[1:].index("""---"""	) + 1
				lowercase__	     =						"""\n""".join(full_content[1:sep_idx]	)
				return yamlblock, "\n".join(full_content[sep_idx + 1 :]	)

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



class 				A       (			__a				):
					'''simple docstring'''






					A__     =					{'''train_eval_index'''}  # train-eval-index in the YAML metadata

					@classmethod
					def     lowerCamelCase__	(cls       :		int ,   _UpperCAmelCase       :		Path						)		->  "DatasetMetadata":




							"""simple docstring"""


							with open(lowerCAmelCase__ ,   encoding="""utf-8"""						) as readme_file:
									lowercase__     ,      lowercase__	     =						_split_yaml_from_readme(readme_file.read()						)
							if yaml_string is not None:
									return cls.from_yaml_string(lowerCAmelCase__						)
							else:
									return cls()

					def     lowerCamelCase__	(self       :		Dict ,   _UpperCAmelCase       :		Path						)		->  List[Any]:




							"""simple docstring"""


							if path.exists():
									with open(lowerCAmelCase__ ,   encoding="""utf-8"""						) as readme_file:
											lowercase__	     =						readme_file.read()
							else:
									lowercase__	     =						None
							lowercase__	     =						self._to_readme(lowerCAmelCase__						)
							with open(lowerCAmelCase__ ,   """w""" ,   encoding="""utf-8"""						) as readme_file:
									readme_file.write(lowerCAmelCase__						)

					def     lowerCamelCase__	(self       :		str ,   _UpperCAmelCase       :		Optional[str] = None						)		->  str:




							"""simple docstring"""


							if readme_content is not None:
									lowercase__     ,      lowercase__	     =						_split_yaml_from_readme(lowerCAmelCase__						)
									lowercase__	     =						"""---\n""" + self.to_yaml_string() + """---\n""" + content
							else:
									lowercase__	     =						"""---\n""" + self.to_yaml_string() + """---\n"""
							return full_content

					@classmethod
					def     lowerCamelCase__	(cls       :		int ,   _UpperCAmelCase       :		str						)		->  "DatasetMetadata":




							"""simple docstring"""


							lowercase__	     =						yaml.load(lowerCAmelCase__ ,   Loader=_NoDuplicateSafeLoader						) or {}

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


					def     lowerCamelCase__	(self       :		int						)		->  str:




							"""simple docstring"""


							return yaml.safe_dump(
							    {
							        (key.replace("""_""" ,   """-"""						) if key in self._FIELDS_WITH_DASHES else key): value
							        for key, value in self.items()
							    } ,   sort_keys=lowerCAmelCase__ ,   allow_unicode=lowerCAmelCase__ ,   encoding="""utf-8""" ,   ).decode("""utf-8"""						)






A			:						Optional[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			:						int        =  ArgumentParser(usage='Validate the yaml metadata block of a README.md file.')
	ap.add_argument('readme_filepath')
	A			:						List[str]        =  ap.parse_args()

	A			:						Tuple        =  Path(args.readme_filepath)
	A			:						List[str]        =  DatasetMetadata.from_readme(readme_filepath)
	print(dataset_metadata)
	dataset_metadata.to_readme(readme_filepath)



# Function to print upper half of diamond (pyramid)

def  __snake_case							(	__magic_name__						):







				'''simple docstring'''


				for i in range(0		,    __magic_name__						):
								for _ in range(0		,    n - i - 1						):  # printing spaces
												print(" "		,    end=""						)
								for _ in range(0		,    i + 1						):  # printing stars
												print("* "		,    end=""						)
								print()

def  __snake_case							(	__magic_name__						):







				'''simple docstring'''


				for i in range(__magic_name__		,    0		,    -1						):
								for _ in range(__magic_name__		,    0		,    -1						):  # printing stars
												print("* "		,    end=""						)
								print()
								for _ in range(n - i + 1		,    0		,    -1						):  # printing spaces
												print(" "		,    end=""						)

def  __snake_case							(	__magic_name__						):







				'''simple docstring'''


				if n <= 0:
								print("       ...       ....        nothing printing :("						)
								return
				floyd(__magic_name__						)  # upper half
				reverse_floyd(__magic_name__						)  # lower half


if __name__ == "__main__":
						print(r"| /\ | |- |  |-  |--| |\  /| |-")
						print(r"|/  \| |- |_ |_  |__| | \/ | |_")
						_snake_case      :							Union[str, Any]     	=    1
						while K:
												_snake_case      :							Dict     	=    int(input("enter the number and , and see the magic : "))
												print()
												pretty_print(user_number)
												_snake_case      :							Tuple     	=    int(input("press 0 to exit... and 1 to continue..."))

						print("Good Bye...")
