


'''simple docstring'''



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

import yaml





class 							__UpperCamelCase    (		yaml.SafeLoader ):




	def 				__UpperCAmelCase							(       self						,    __a							):

						'''simple docstring'''





						__a      :	Dict    =  [self.constructed_objects[key_node] for key_node, _ in node.value]
						__a      :	Optional[int]    =  [tuple(_SCREAMING_SNAKE_CASE							) if isinstance(_SCREAMING_SNAKE_CASE						,    _SCREAMING_SNAKE_CASE							) else key for key in keys]
						__a      :	Dict    =  Counter(_SCREAMING_SNAKE_CASE							)
						__a      :	Union[str, Any]    =  [key for key in counter if counter[key] > 1]
						if duplicate_keys:
											raise TypeError(f"""Got duplicate yaml keys: {duplicate_keys}"""							)





	def 				__UpperCAmelCase							(       self						,    __a						,    __a=False							):

						'''simple docstring'''





						__a      :	Any    =  super().construct_mapping(_SCREAMING_SNAKE_CASE						,    deep=_SCREAMING_SNAKE_CASE							)
						self._check_no_duplicates_on_constructed_node(_SCREAMING_SNAKE_CASE							)
						return mapping






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE				:       List[str]       ):
					__a      :	Any    =  list(readme_content.splitlines()       )
					if full_content and full_content[0] == "---" and "---" in full_content[1:]:
										__a      :	List[str]    =  full_content[1:].index('---'       ) + 1
										__a      :	str    =  "\n".join(full_content[1:sep_idx]       )
										return yamlblock, "\n".join(full_content[sep_idx + 1 :]       )

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





class 							__UpperCamelCase    (		__SCREAMING_SNAKE_CASE ):
	A_           =   {"train_eval_index"}  # train-eval-index in the YAML metadata




	@classmethod
	def 				__UpperCAmelCase							(       cls						,    __a							):

						'''simple docstring'''





						with open(_SCREAMING_SNAKE_CASE						,    encoding='utf-8'							) as readme_file:
											__a      :	Dict    =  _split_yaml_from_readme(readme_file.read()							)
						if yaml_string is not None:
											return cls.from_yaml_string(_SCREAMING_SNAKE_CASE							)
						else:
											return cls()




	def 				__UpperCAmelCase							(       self						,    __a							):

						'''simple docstring'''





						if path.exists():
											with open(_SCREAMING_SNAKE_CASE						,    encoding='utf-8'							) as readme_file:
																__a      :	List[Any]    =  readme_file.read()
						else:
											__a      :	Optional[int]    =  None
						__a      :	int    =  self._to_readme(_SCREAMING_SNAKE_CASE							)
						with open(_SCREAMING_SNAKE_CASE						,    'w'						,    encoding='utf-8'							) as readme_file:
											readme_file.write(_SCREAMING_SNAKE_CASE							)




	def 				__UpperCAmelCase							(       self						,    __a = None							):

						'''simple docstring'''





						if readme_content is not None:
											__a      :	Optional[Any]    =  _split_yaml_from_readme(_SCREAMING_SNAKE_CASE							)
											__a      :	List[Any]    =  "---\n" + self.to_yaml_string() + "---\n" + content
						else:
											__a      :	str    =  "---\n" + self.to_yaml_string() + "---\n"
						return full_content




	@classmethod
	def 				__UpperCAmelCase							(       cls						,    __a							):

						'''simple docstring'''





						__a      :	Tuple    =  yaml.load(_SCREAMING_SNAKE_CASE						,    Loader=_NoDuplicateSafeLoader							) or {}

						# Convert the YAML keys to DatasetMetadata fields
						__a      :	Union[str, Any]    =  {
						    (key.replace('-'						,    '_'							) if key.replace('-'						,    '_'							) in cls._FIELDS_WITH_DASHES else key): value
						    for key, value in metadata_dict.items()
						}
						return cls(**_SCREAMING_SNAKE_CASE							)





	def 				__UpperCAmelCase							(       self							):

						'''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=_SCREAMING_SNAKE_CASE						,    allow_unicode=_SCREAMING_SNAKE_CASE						,    encoding='utf-8'						,    ).decode('utf-8'							)



__lowercase     :						int	=     {
    '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

	__lowercase     :						Union[str, Any]	=     ArgumentParser(usage='Validate the yaml metadata block of a README.md file.')
	ap.add_argument('readme_filepath')
	__lowercase     :						Optional[Any]	=     ap.parse_args()

	__lowercase     :						Any	=     Path(args.readme_filepath)
	__lowercase     :						int	=     DatasetMetadata.from_readme(readme_filepath)
	print(dataset_metadata)
	dataset_metadata.to_readme(readme_filepath)







'''simple docstring'''



from __future__ import annotations

from dataclasses import dataclass





@dataclass
class 							__UpperCamelCase    :
	A_           =   42
	A_           =   None
	A_           =   None






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE				:       TreeNode | None       ):

					# Validation
					def is_valid_tree(_SCREAMING_SNAKE_CASE				:       TreeNode | None       ) -> bool:
										if node is None:
															return True

										if not isinstance(_SCREAMING_SNAKE_CASE						,				_SCREAMING_SNAKE_CASE       ):
															return False

										try:
															float(node.data       )
										except (TypeError, ValueError):
															return False

										return is_valid_tree(node.left       ) and is_valid_tree(node.right       )

					if not is_valid_tree(_SCREAMING_SNAKE_CASE       ):
										raise ValueError(
										    'Each node should be type of TreeNode and data should be float.'       )

					def is_binary_search_tree_recursive_check(
					    _SCREAMING_SNAKE_CASE				:       TreeNode | None						,				_SCREAMING_SNAKE_CASE				:       float						,				_SCREAMING_SNAKE_CASE				:       float       ) -> bool:

										if node is None:
															return True

										return (
										    left_bound < node.data < right_bound
										    and is_binary_search_tree_recursive_check(node.left						,				_SCREAMING_SNAKE_CASE						,				node.data       )
										    and is_binary_search_tree_recursive_check(
										        node.right						,				node.data						,				_SCREAMING_SNAKE_CASE       )
										)

					return is_binary_search_tree_recursive_check(_SCREAMING_SNAKE_CASE						,				-float('inf'       )						,				float('inf'       )       )


if __name__ == "__main__":
	import doctest

	doctest.testmod()



