



import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowercase		:				Union[str, Any]      		=logging.get_logger(__name__)

_lowercase		:				Optional[Any]      		={
    "microsoft/git-base": "https://huggingface.co/microsoft/git-base/resolve/main/config.json",
}

class        snake_case__    (UpperCAmelCase_		):







				"""simple docstring"""




				__lowerCAmelCase					:List[Any]      =					"""git_vision_model"""

				def __init__(       self ,       __lowercase=7_6_8 ,       __lowercase=3_0_7_2 ,       __lowercase=1_2 ,       __lowercase=1_2 ,       __lowercase=3 ,       __lowercase=2_2_4 ,       __lowercase=1_6 ,       __lowercase="quick_gelu" ,       __lowercase=1E-5 ,       __lowercase=0.0 ,       __lowercase=0.0_2 ,       **__lowercase ,       ) ->				Optional[Any]:
							"""simple docstring"""




							super().__init__(**__lowercase  )

							a__       :						str							=  hidden_size
							a__       :						List[str]							=  intermediate_size
							a__       :						str							=  num_hidden_layers
							a__       :						Any							=  num_attention_heads
							a__       :						int							=  num_channels
							a__       :						Optional[int]							=  patch_size
							a__       :						Any							=  image_size
							a__       :						List[str]							=  initializer_range
							a__       :						Tuple							=  attention_dropout
							a__       :						str							=  layer_norm_eps
							a__       :						Union[str, Any]							=  hidden_act

				@classmethod
				def 							SCREAMING_SNAKE_CASE__(       cls ,       __lowercase ,       **__lowercase  ) ->				"PretrainedConfig":
							"""simple docstring"""




							cls._set_token_in_kwargs(__lowercase  )

							a__       :						Optional[int]							=  cls.get_config_dict(__lowercase ,       **__lowercase  )

							# get the vision config dict if we are loading from GITConfig
							if config_dict.get("""model_type"""  ) == "git":
										a__       :						Optional[int]							=  config_dict['''vision_config''']

							if "model_type" in config_dict and hasattr(cls ,       """model_type"""  ) and config_dict["model_type"] != cls.model_type:
										logger.warning(
										    F'''You are using a model of type {config_dict['model_type']} to instantiate a model of type '''
										    F'''{cls.model_type}. This is not supported for all configurations of models and can yield errors.'''  )

							return cls.from_dict(__lowercase ,       **__lowercase  )




class        snake_case__    (UpperCAmelCase_		):







				"""simple docstring"""




				__lowerCAmelCase					:Any      =					"""git"""

				def __init__(       self ,       __lowercase=None ,       __lowercase=3_0_5_2_2 ,       __lowercase=7_6_8 ,       __lowercase=6 ,       __lowercase=1_2 ,       __lowercase=3_0_7_2 ,       __lowercase="gelu" ,       __lowercase=0.1 ,       __lowercase=0.1 ,       __lowercase=1_0_2_4 ,       __lowercase=0.0_2 ,       __lowercase=1E-12 ,       __lowercase=0 ,       __lowercase="absolute" ,       __lowercase=True ,       __lowercase=False ,       __lowercase=1_0_1 ,       __lowercase=1_0_2 ,       __lowercase=None ,       **__lowercase ,       ) ->				Dict:
							"""simple docstring"""




							super().__init__(bos_token_id=__lowercase ,       eos_token_id=__lowercase ,       pad_token_id=__lowercase ,       **__lowercase  )

							if vision_config is None:
										a__       :						Union[str, Any]							=  {}
										logger.info("""vision_config is None. initializing the GitVisionConfig with default values."""  )

							a__       :						Optional[Any]							=  GitVisionConfig(**__lowercase  )
							a__       :						Optional[int]							=  vocab_size
							a__       :						List[str]							=  hidden_size
							a__       :						int							=  num_hidden_layers
							a__       :						int							=  num_attention_heads
							a__       :						List[Any]							=  hidden_act
							a__       :						List[str]							=  intermediate_size
							a__       :						List[str]							=  hidden_dropout_prob
							a__       :						List[Any]							=  attention_probs_dropout_prob
							a__       :						Tuple							=  max_position_embeddings
							a__       :						int							=  initializer_range
							a__       :						Any							=  layer_norm_eps
							a__       :						Optional[int]							=  position_embedding_type
							a__       :						Union[str, Any]							=  use_cache
							a__       :						str							=  tie_word_embeddings
							a__       :						Optional[Any]							=  num_image_with_embedding

							a__       :						str							=  bos_token_id
							a__       :						Tuple							=  eos_token_id

				def 							SCREAMING_SNAKE_CASE__(       self  ) ->				Tuple:
							"""simple docstring"""




							a__       :						Optional[Any]							=  copy.deepcopy(self.__dict__  )
							a__       :						Optional[int]							=  self.vision_config.to_dict()
							a__       :						str							=  self.__class__.model_type
							return output









from string import ascii_uppercase

_lowercase		:				str      		={char: i for i, char in enumerate(ascii_uppercase)}
_lowercase		:				Dict      		=dict(enumerate(ascii_uppercase))

def      lowerCAmelCase_					(  _lowercase    :       str						,       _lowercase    :       str)							->	str:







			"""simple docstring"""
			a__       :						Any							=  len(_lowercase)
			a__       :						Optional[int]							=  0
			while True:
						if x == i:
									a__       :						Optional[Any]							=  0
						if len(_lowercase) == len(_lowercase):
									break
						key += key[i]
						i += 1
			return key

def      lowerCAmelCase_					(  _lowercase    :       str						,       _lowercase    :       str)							->	str:







			"""simple docstring"""
			a__       :						Tuple							=  """"""
			a__       :						str							=  0
			for letter in message:
						if letter == " ":
									cipher_text += " "
						else:
									a__       :						List[str]							=  (dicta[letter] - dicta[key_new[i]]) % 26
									i += 1
									cipher_text += dicta[x]
			return cipher_text

def      lowerCAmelCase_					(  _lowercase    :       str						,       _lowercase    :       str)							->	str:







			"""simple docstring"""
			a__       :						int							=  """"""
			a__       :						int							=  0
			for letter in cipher_text:
						if letter == " ":
									or_txt += " "
						else:
									a__       :						Dict							=  (dicta[letter] + dicta[key_new[i]] + 26) % 26
									i += 1
									or_txt += dicta[x]
			return or_txt

def      lowerCAmelCase_					(  )							->	None:







			"""simple docstring"""
			a__       :						List[Any]							=  """THE GERMAN ATTACK"""
			a__       :						List[Any]							=  """SECRET"""
			a__       :						Tuple							=  generate_key(_lowercase						,       _lowercase)
			a__       :						str							=  cipher_text(_lowercase						,       _lowercase)
			print(F'''Encrypted Text = {s}''')
			print(F'''Original Text = {original_text(_lowercase						,       _lowercase)}''')


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		main()




