




'''simple docstring'''





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

import yaml




class 					snake_case__							(yaml.SafeLoader     ):
				"""simple docstring"""



				def 							__UpperCAmelCase							(   self       :  Any      ,   __lowerCamelCase       :  List[str]							)      ->  str:
							a					=    [self.constructed_objects[key_node] for key_node, _ in node.value]
							a					=    [tuple(__UpperCamelCase							) if isinstance(__UpperCamelCase      ,   __UpperCamelCase							) else key for key in keys]
							a					=    Counter(__UpperCamelCase							)
							a					=    [key for key in counter if counter[key] > 1]
							if duplicate_keys:
										raise TypeError(f"""Got duplicate yaml keys: {duplicate_keys}"""							)





				def 							__UpperCAmelCase							(   self       :  Dict      ,   __lowerCamelCase       :  int      ,   __lowerCamelCase       :  Dict=False							)      ->  Tuple:
							a					=    super().construct_mapping(__UpperCamelCase      ,   deep=__UpperCamelCase							)
							self._check_no_duplicates_on_constructed_node(__UpperCamelCase							)
							return mapping




def     __magic_name__       (				A	:      str     ):






			'''simple docstring'''







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

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




class 					snake_case__							(_UpperCamelCase     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							List[Any]											=      {"""train_eval_index"""}  # train-eval-index in the YAML metadata





				@classmethod
				def 							__UpperCAmelCase							(   cls       :  List[Any]      ,   __lowerCamelCase       :  Path							)      ->  Tuple:
							with open(__UpperCamelCase      ,   encoding="utf-8"							) as readme_file:
										a					,	a					=    _split_yaml_from_readme(readme_file.read()							)
							if yaml_string is not None:
										return cls.from_yaml_string(__UpperCamelCase							)
							else:
										return cls()





				def 							__UpperCAmelCase							(   self       :  Optional[Any]      ,   __lowerCamelCase       :  Path							)      ->  Tuple:
							if path.exists():
										with open(__UpperCamelCase      ,   encoding="utf-8"							) as readme_file:
													a					=    readme_file.read()
							else:
										a					=    None
							a					=    self._to_readme(__UpperCamelCase							)
							with open(__UpperCamelCase      ,   "w"      ,   encoding="utf-8"							) as readme_file:
										readme_file.write(__UpperCamelCase							)





				def 							__UpperCAmelCase							(   self       :  str      ,   __lowerCamelCase       :  Optional[str] = None							)      ->  str:
							if readme_content is not None:
										a					,	a					=    _split_yaml_from_readme(__UpperCamelCase							)
										a					=    "---\n" + self.to_yaml_string() + "---\n" + content
							else:
										a					=    "---\n" + self.to_yaml_string() + "---\n"
							return full_content





				@classmethod
				def 							__UpperCAmelCase							(   cls       :  List[Any]      ,   __lowerCamelCase       :  str							)      ->  List[Any]:
							a					=    yaml.load(__UpperCamelCase      ,   Loader=_NoDuplicateSafeLoader							) or {}

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





				def 							__UpperCAmelCase							(   self       :  Optional[Any]							)      ->  str:
							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"							)

__lowerCAmelCase	:       Dict     =	{
    '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

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

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












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__lowerCAmelCase	:       Any     =	{
    'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'],
    'tokenization_roc_bert': ['RoCBertTokenizer'],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		pass

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase	:       Optional[Any]     =	[
		    'ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'RoCBertForCausalLM',
		    'RoCBertForMaskedLM',
		    'RoCBertForMultipleChoice',
		    'RoCBertForPreTraining',
		    'RoCBertForQuestionAnswering',
		    'RoCBertForSequenceClassification',
		    'RoCBertForTokenClassification',
		    'RoCBertLayer',
		    'RoCBertModel',
		    'RoCBertPreTrainedModel',
		    'load_tf_weights_in_roc_bert',
		]

if TYPE_CHECKING:
		from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
		from .tokenization_roc_bert import RoCBertTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				raise OptionalDependencyNotAvailable()

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_roc_bert import (
				    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    RoCBertForCausalLM,
				    RoCBertForMaskedLM,
				    RoCBertForMultipleChoice,
				    RoCBertForPreTraining,
				    RoCBertForQuestionAnswering,
				    RoCBertForSequenceClassification,
				    RoCBertForTokenClassification,
				    RoCBertLayer,
				    RoCBertModel,
				    RoCBertPreTrainedModel,
				    load_tf_weights_in_roc_bert,
				)


else:
		import sys

		__lowerCAmelCase	:       Union[str, Any]     =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






