

from typing import TYPE_CHECKING

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


lowerCAmelCase							:						Union[str, Any]     			=		{
    '''configuration_flava''': [
        '''FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''FlavaConfig''',
        '''FlavaImageCodebookConfig''',
        '''FlavaImageConfig''',
        '''FlavaMultimodalConfig''',
        '''FlavaTextConfig''',
    ],
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase							:						List[str]     			=		['''FlavaFeatureExtractor''']
		lowerCAmelCase							:						str     			=		['''FlavaImageProcessor''']
		lowerCAmelCase							:						int     			=		['''FlavaProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase							:						Union[str, Any]     			=		[
		    '''FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''FlavaForPreTraining''',
		    '''FlavaImageCodebook''',
		    '''FlavaImageModel''',
		    '''FlavaModel''',
		    '''FlavaMultimodalModel''',
		    '''FlavaPreTrainedModel''',
		    '''FlavaTextModel''',
		]

if TYPE_CHECKING:
		from .configuration_flava import (
		    FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    FlavaConfig,
		    FlavaImageCodebookConfig,
		    FlavaImageConfig,
		    FlavaMultimodalConfig,
		    FlavaTextConfig,
		)

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_flava import FlavaFeatureExtractor
				from .image_processing_flava import FlavaImageProcessor
				from .processing_flava import FlavaProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flava import (
				    FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    FlavaForPreTraining,
				    FlavaImageCodebook,
				    FlavaImageModel,
				    FlavaModel,
				    FlavaMultimodalModel,
				    FlavaPreTrainedModel,
				    FlavaTextModel,
				)

else:
		import sys

		lowerCAmelCase							:						Any     			=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)









def     A_   (					_UpperCAmelCase					):
						SCREAMING_SNAKE_CASE_:				Optional[Any]							= []
						SCREAMING_SNAKE_CASE_:				Any							= 1

						for i in range(len(_UpperCAmelCase					)					):
												if i + 1 < len(_UpperCAmelCase					) and text[i] == text[i + 1]:
																		count += 1
												else:
																		encoded.append((text[i], count)					)
																		SCREAMING_SNAKE_CASE_:				List[Any]							= 1

						return encoded







def     A_   (					_UpperCAmelCase					):
						return "".join(char * length for char, length in encoded					)


if __name__ == "__main__":
						from doctest import testmod

						testmod(name="""run_length_encode""", verbose=True)
						testmod(name="""run_length_decode""", verbose=True)






