


"""simple docstring"""




from string import ascii_uppercase

__UpperCamelCase						=      {char: i for i, char in enumerate(ascii_uppercase)}
__UpperCamelCase						=      dict(enumerate(ascii_uppercase))


def     lowercase			(SCREAMING_SNAKE_CASE_		:				str ,			SCREAMING_SNAKE_CASE_		:				str  )   ->						str:
						SCREAMING_SNAKE_CASE													=					len(SCREAMING_SNAKE_CASE_  )
						SCREAMING_SNAKE_CASE													=					0
						while True:
												if x == i:
																		SCREAMING_SNAKE_CASE													=					0
												if len(SCREAMING_SNAKE_CASE_  ) == len(SCREAMING_SNAKE_CASE_  ):
																		break
												key += key[i]
												i += 1
						return key


def     lowercase			(SCREAMING_SNAKE_CASE_		:				str ,			SCREAMING_SNAKE_CASE_		:				str  )   ->						str:
						SCREAMING_SNAKE_CASE													=					''
						SCREAMING_SNAKE_CASE													=					0
						for letter in message:
												if letter == " ":
																		cipher_text += " "
												else:
																		SCREAMING_SNAKE_CASE													=					(dicta[letter] - dicta[key_new[i]]) % 26
																		i += 1
																		cipher_text += dicta[x]
						return cipher_text


def     lowercase			(SCREAMING_SNAKE_CASE_		:				str ,			SCREAMING_SNAKE_CASE_		:				str  )   ->						str:
						SCREAMING_SNAKE_CASE													=					''
						SCREAMING_SNAKE_CASE													=					0
						for letter in cipher_text:
												if letter == " ":
																		or_txt += " "
												else:
																		SCREAMING_SNAKE_CASE													=					(dicta[letter] + dicta[key_new[i]] + 26) % 26
																		i += 1
																		or_txt += dicta[x]
						return or_txt


def     lowercase			()   ->						None:
						SCREAMING_SNAKE_CASE													=					'THE GERMAN ATTACK'
						SCREAMING_SNAKE_CASE													=					'SECRET'
						SCREAMING_SNAKE_CASE													=					generate_key(SCREAMING_SNAKE_CASE_ ,			SCREAMING_SNAKE_CASE_  )
						SCREAMING_SNAKE_CASE													=					cipher_text(SCREAMING_SNAKE_CASE_ ,			SCREAMING_SNAKE_CASE_  )
						print(F'Encrypted Text = {s}'  )
						print(F'Original Text = {original_text(SCREAMING_SNAKE_CASE_ ,			SCREAMING_SNAKE_CASE_  )}'  )


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()






"""simple docstring"""




from typing import TYPE_CHECKING

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


__UpperCamelCase						=      {
    '''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:
	__UpperCamelCase						=      ['''BlipImageProcessor''']


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

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__UpperCamelCase						=      [
	    '''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

	__UpperCamelCase						=      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


