




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


__lowerCAmelCase	:       Dict     =	{
    'configuration_blip': [
        'BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlipConfig',
        'BlipTextConfig',
        'BlipVisionConfig',
    ],
    'processing_blip': ['BlipProcessor'],
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase	:       Optional[Any]     =	['BlipImageProcessor']


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase	:       List[Any]     =	[
		    'BLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'BlipModel',
		    'BlipPreTrainedModel',
		    'BlipForConditionalGeneration',
		    'BlipForQuestionAnswering',
		    'BlipVisionModel',
		    'BlipTextModel',
		    'BlipForImageTextRetrieval',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase	:       Any     =	[
		    'TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TFBlipModel',
		    'TFBlipPreTrainedModel',
		    'TFBlipForConditionalGeneration',
		    'TFBlipForQuestionAnswering',
		    'TFBlipVisionModel',
		    'TFBlipTextModel',
		    'TFBlipForImageTextRetrieval',
		]

if TYPE_CHECKING:
		from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
		from .processing_blip import BlipProcessor

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .image_processing_blip import BlipImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_blip import (
				    BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BlipForConditionalGeneration,
				    BlipForImageTextRetrieval,
				    BlipForQuestionAnswering,
				    BlipModel,
				    BlipPreTrainedModel,
				    BlipTextModel,
				    BlipVisionModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_blip import (
				    TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFBlipForConditionalGeneration,
				    TFBlipForImageTextRetrieval,
				    TFBlipForQuestionAnswering,
				    TFBlipModel,
				    TFBlipPreTrainedModel,
				    TFBlipTextModel,
				    TFBlipVisionModel,
				)

else:
		import sys

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












def     __magic_name__       (				A	:      str,						A	:      str     ):






			'''simple docstring'''







			def get_matched_characters(A	:      str,						A	:      str     ) -> str:
						a					=    []
						a					=    min(len(_stra     ),						len(_stra     )     ) // 2
						for i, l in enumerate(_stra     ):
									a					=    int(max(0,						i - limit     )     )
									a					=    int(min(i + limit + 1,						len(_stra     )     )     )
									if l in _stra[left:right]:
												matched.append(A     )
												a					=    F"""{_stra[0:_stra.index(A     )]} {_stra[_stra.index(A     ) + 1:]}"""

						return "".join(A     )

			# matching characters
			a					=    get_matched_characters(A,						A     )
			a					=    get_matched_characters(A,						A     )
			a					=    len(A     )

			# transposition
			a					=    (
			    len([(ca, ca) for ca, ca in zip(A,						A     ) if ca != ca]     ) // 2
			)

			if not match_count:
						a					=    0.0
			else:
						a					=    (
						    1
						    / 3
						    * (
						        match_count / len(A     )
						        + match_count / len(A     )
						        + (match_count - transpositions) / match_count
						    )
						)

			# common prefix up to 4 characters
			a					=    0
			for ca, ca in zip(stra[:4],						stra[:4]     ):
						if ca == ca:
									prefix_len += 1
						else:
									break

			return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		print(jaro_winkler('hello', 'world'))






