



'''simple docstring'''




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

import yaml






class 						_UpperCamelCase  (							yaml.SafeLoader    ):


			'''simple docstring'''

			def UpperCamelCase__					(							self     : Tuple							,     lowerCAmelCase__     : Union[str, Any]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		int           =		[self.constructed_objects[key_node] for key_node, _ in node.value]
					__SCREAMING_SNAKE_CASE       :		List[str]           =		[tuple(lowerCAmelCase__						) if isinstance(lowerCAmelCase__							,     lowerCAmelCase__						) else key for key in keys]
					__SCREAMING_SNAKE_CASE       :		Tuple           =		Counter(lowerCAmelCase__						)
					__SCREAMING_SNAKE_CASE       :		List[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     : Any							,     lowerCAmelCase__     : str							,     lowerCAmelCase__     : Optional[int]=False						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		super().construct_mapping(lowerCAmelCase__							,     deep=lowerCAmelCase__						)
					self._check_no_duplicates_on_constructed_node(lowerCAmelCase__						)
					return mapping


def 				lowerCAmelCase_   (	_lowerCamelCase:   str					):
		__SCREAMING_SNAKE_CASE       :		List[Any]           =		list(readme_content.splitlines()					)
		if full_content and full_content[0] == "---" and "---" in full_content[1:]:
				__SCREAMING_SNAKE_CASE       :		List[str]           =		full_content[1:].index("""---"""					) + 1
				__SCREAMING_SNAKE_CASE       :		Optional[int]           =		"""\n""".join(full_content[1:sep_idx]					)
				return yamlblock, "\n".join(full_content[sep_idx + 1 :]					)

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






class 						_UpperCamelCase  (							lowerCamelCase__    ):


			'''simple docstring'''

			_A      :		List[str]			    =		{'''train_eval_index'''}  # train-eval-index in the YAML metadata

			@classmethod
			def UpperCamelCase__					(							cls     : Optional[int]							,     lowerCAmelCase__     : Path						):





					"""simple docstring"""






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

			def UpperCamelCase__					(							self     : str							,     lowerCAmelCase__     : Path						):





					"""simple docstring"""






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

			def UpperCamelCase__					(							self     : Any							,     lowerCAmelCase__     : Optional[str] = None						):





					"""simple docstring"""






					if readme_content is not None:
							__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		_split_yaml_from_readme(lowerCAmelCase__						)
							__SCREAMING_SNAKE_CASE       :		str           =		"""---\n""" + self.to_yaml_string() + """---\n""" + content
					else:
							__SCREAMING_SNAKE_CASE       :		Dict           =		"""---\n""" + self.to_yaml_string() + """---\n"""
					return full_content

			@classmethod
			def UpperCamelCase__					(							cls     : List[str]							,     lowerCAmelCase__     : str						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		List[Any]           =		yaml.load(lowerCAmelCase__							,     Loader=_NoDuplicateSafeLoader						) or {}

					# Convert the YAML keys to DatasetMetadata fields
					__SCREAMING_SNAKE_CASE       :		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(**lowerCAmelCase__						)



			def UpperCamelCase__					(							self     : Optional[Any]						):





					"""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"""						)
UpperCamelCase__       :	Union[str, 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

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

						UpperCamelCase__       :	Optional[int]    = Path(args.readme_filepath)
						UpperCamelCase__       :	Tuple    = DatasetMetadata.from_readme(readme_filepath)
						print(dataset_metadata)
						dataset_metadata.to_readme(readme_filepath)




'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__       :	Any    = {
    '''configuration_instructblip''': [
        '''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''InstructBlipConfig''',
        '''InstructBlipQFormerConfig''',
        '''InstructBlipVisionConfig''',
    ],
    '''processing_instructblip''': ['''InstructBlipProcessor'''],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__       :	Optional[Any]    = [
						    '''INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''InstructBlipQFormerModel''',
						    '''InstructBlipPreTrainedModel''',
						    '''InstructBlipForConditionalGeneration''',
						    '''InstructBlipVisionModel''',
						]

if TYPE_CHECKING:
						from .configuration_instructblip import (
						    INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    InstructBlipConfig,
						    InstructBlipQFormerConfig,
						    InstructBlipVisionConfig,
						)
						from .processing_instructblip import InstructBlipProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_instructblip import (
												    INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
												    InstructBlipForConditionalGeneration,
												    InstructBlipPreTrainedModel,
												    InstructBlipQFormerModel,
												    InstructBlipVisionModel,
												)

else:
						import sys

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