



"""simple docstring"""





import copy
import os
from typing import Union

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


__lowerCAmelCase							:       List[Any]          =       logging.get_logger(__name__)

__lowerCAmelCase							:       Union[str, Any]          =       {
    '''BridgeTower/bridgetower-base''': '''https://huggingface.co/BridgeTower/bridgetower-base/blob/main/config.json''',
    '''BridgeTower/bridgetower-base-itm-mlm''': (
        '''https://huggingface.co/BridgeTower/bridgetower-base-itm-mlm/blob/main/config.json'''
    ),
}



class  _lowerCAmelCase     (					SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		_lowerCamelCase      	=							'''bridgetower_vision_model'''





		def __init__(       self				,     _lowercase=7_6_8				,     _lowercase=1_2				,     _lowercase=3				,     _lowercase=1_6				,     _lowercase=2_8_8				,     _lowercase=1				,     _lowercase=1E-05				,     _lowercase=False				,     _lowercase=True				,     _lowercase=False				,     **_lowercase				,     )			->    List[Any]:







								'''simple docstring'''

								super().__init__(**_lowercase )
								snake_case_ :			Any            =      hidden_size
								snake_case_ :			Tuple            =      num_hidden_layers
								snake_case_ :			Union[str, Any]            =      num_channels
								snake_case_ :			List[Any]            =      patch_size
								snake_case_ :			int            =      image_size
								snake_case_ :			Tuple            =      initializer_factor
								snake_case_ :			List[str]            =      layer_norm_eps
								snake_case_ :			Optional[int]            =      stop_gradient
								snake_case_ :			Optional[Any]            =      share_layernorm
								snake_case_ :			Tuple            =      remove_last_layer





		@classmethod
		def  UpperCAmelCase__				(       cls				,     _lowercase				,     **_lowercase )			->    "PretrainedConfig":







								'''simple docstring'''

								snake_case_      ,		snake_case_ :			Any            =      cls.get_config_dict(_lowercase				,     **_lowercase )

								if config_dict.get("""model_type""" ) == "bridgetower":
														snake_case_ :			Any            =      config_dict["""text_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  _lowerCAmelCase     (					SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		_lowerCamelCase      	=							'''bridgetower_text_model'''





		def __init__(       self				,     _lowercase=5_0_2_6_5				,     _lowercase=7_6_8				,     _lowercase=1_2				,     _lowercase=1_2				,     _lowercase=1				,     _lowercase=3_0_7_2				,     _lowercase="gelu"				,     _lowercase=0.1				,     _lowercase=0.1				,     _lowercase=5_1_4				,     _lowercase=1				,     _lowercase=1E-05				,     _lowercase=1				,     _lowercase=0				,     _lowercase=2				,     _lowercase="absolute"				,     _lowercase=True				,     **_lowercase				,     )			->    str:







								'''simple docstring'''

								super().__init__(**_lowercase )

								snake_case_ :			Any            =      vocab_size
								snake_case_ :			Dict            =      hidden_size
								snake_case_ :			int            =      num_hidden_layers
								snake_case_ :			Dict            =      num_attention_heads
								snake_case_ :			Any            =      hidden_act
								snake_case_ :			Dict            =      initializer_factor
								snake_case_ :			List[Any]            =      intermediate_size
								snake_case_ :			Dict            =      hidden_dropout_prob
								snake_case_ :			Optional[int]            =      attention_probs_dropout_prob
								snake_case_ :			str            =      max_position_embeddings
								snake_case_ :			List[str]            =      type_vocab_size
								snake_case_ :			Tuple            =      layer_norm_eps
								snake_case_ :			int            =      position_embedding_type
								snake_case_ :			Optional[int]            =      use_cache
								snake_case_ :			List[str]            =      pad_token_id
								snake_case_ :			int            =      bos_token_id
								snake_case_ :			Dict            =      eos_token_id





		@classmethod
		def  UpperCAmelCase__				(       cls				,     _lowercase				,     **_lowercase )			->    "PretrainedConfig":







								'''simple docstring'''

								snake_case_      ,		snake_case_ :			int            =      cls.get_config_dict(_lowercase				,     **_lowercase )

								if config_dict.get("""model_type""" ) == "bridgetower":
														snake_case_ :			Union[str, Any]            =      config_dict["""text_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  _lowerCAmelCase     (					SCREAMING_SNAKE_CASE__		):





		"""simple docstring"""






		_lowerCamelCase      	=							'''bridgetower'''





		def __init__(       self				,     _lowercase=True				,     _lowercase="gelu"				,     _lowercase=7_6_8				,     _lowercase=1				,     _lowercase=1E-05				,     _lowercase=False				,     _lowercase="add"				,     _lowercase=1_2				,     _lowercase=6				,     _lowercase=False				,     _lowercase=False				,     _lowercase=None				,     _lowercase=None				,     **_lowercase				,     )			->    Dict:







								'''simple docstring'''

								snake_case_ :			Dict            =      kwargs.pop("""text_config_dict"""				,     _lowercase )
								snake_case_ :			List[str]            =      kwargs.pop("""vision_config_dict"""				,     _lowercase )

								super().__init__(**_lowercase )
								snake_case_ :			str            =      share_cross_modal_transformer_layers
								snake_case_ :			int            =      hidden_act
								snake_case_ :			Tuple            =      hidden_size
								snake_case_ :			List[Any]            =      initializer_factor
								snake_case_ :			Dict            =      layer_norm_eps
								snake_case_ :			str            =      share_link_tower_layers
								snake_case_ :			int            =      link_tower_type
								snake_case_ :			str            =      num_attention_heads
								snake_case_ :			int            =      num_hidden_layers
								snake_case_ :			Tuple            =      tie_word_embeddings
								snake_case_ :			Tuple            =      init_layernorm_from_vision_encoder

								if text_config is None:
														snake_case_ :			Optional[Any]            =      {}
														logger.info("""`text_config` is `None`. Initializing the `BridgeTowerTextConfig` with default values.""" )

								if vision_config is None:
														snake_case_ :			Optional[int]            =      {}
														logger.info("""`vision_config` is `None`. Initializing the `BridgeTowerVisionConfig` with default values.""" )

								snake_case_ :			str            =      BridgeTowerTextConfig(**_lowercase )
								snake_case_ :			Any            =      BridgeTowerVisionConfig(**_lowercase )





		@classmethod
		def  UpperCAmelCase__				(       cls				,     _lowercase				,     _lowercase				,     **_lowercase )			->    Dict:







								'''simple docstring'''

								return cls(text_config=text_config.to_dict()				,     vision_config=vision_config.to_dict()				,     **_lowercase )





		def  UpperCAmelCase__				(       self )			->    Union[str, Any]:







								'''simple docstring'''

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








"""simple docstring"""


def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		List[Any]				   =			""""""
						for i in table:
												res += inp[i - 1]
						return res

def      UpperCamelCase							(SCREAMING_SNAKE_CASE     ):
						return data[1:] + data[0]

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		Union[str, Any]				   =			""""""
						for i in range(len(SCREAMING_SNAKE_CASE     )     ):
												if a[i] == b[i]:
																		res += "0"
												else:
																		res += "1"
						return res

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		Optional[int]				   =			int("""0b""" + data[0] + data[-1]							,     2     )
						UpperCamelCase				:		Any				   =			int("""0b""" + data[1:3]							,     2     )
						return bin(s[row][col]     )[2:]

def      UpperCamelCase							(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     ):
						UpperCamelCase				:		Any				   =			message[:4]
						UpperCamelCase				:		int				   =			message[4:]
						UpperCamelCase				:		int				   =			apply_table(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )
						UpperCamelCase				:		str				   =			xor(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )
						UpperCamelCase				:		Union[str, Any]				   =			apply_sbox(SCREAMING_SNAKE_CASE							,     temp[:4]     )  # noqa: E741
						UpperCamelCase				:		str				   =			apply_sbox(SCREAMING_SNAKE_CASE							,     temp[4:]     )
						UpperCamelCase				:		Union[str, Any]				   =			"""0""" * (2 - len(SCREAMING_SNAKE_CASE     )) + l  # noqa: E741
						UpperCamelCase				:		Union[str, Any]				   =			"""0""" * (2 - len(SCREAMING_SNAKE_CASE     )) + r
						UpperCamelCase				:		int				   =			apply_table(l + r							,     SCREAMING_SNAKE_CASE     )
						UpperCamelCase				:		int				   =			xor(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )
						return temp + right


if __name__ == "__main__":
		__magic_name__       :					Union[str, Any]						=			input("""Enter 10 bit key: """)
		__magic_name__       :					Union[str, Any]						=			input("""Enter 8 bit message: """)

		__magic_name__       :					Dict						=			[6, 3, 7, 4, 8, 5, 1_0, 9]
		__magic_name__       :					str						=			[3, 5, 2, 7, 4, 1_0, 1, 9, 8, 6]
		__magic_name__       :					Optional[Any]						=			[2, 4, 3, 1]
		__magic_name__       :					Tuple						=			[2, 6, 3, 1, 4, 8, 5, 7]
		__magic_name__       :					str						=			[4, 1, 3, 5, 7, 2, 8, 6]
		__magic_name__       :					str						=			[4, 1, 2, 3, 2, 3, 4, 1]
		__magic_name__       :					Any						=			[[1, 0, 3, 2], [3, 2, 1, 0], [0, 2, 1, 3], [3, 1, 3, 2]]
		__magic_name__       :					Any						=			[[0, 1, 2, 3], [2, 0, 1, 3], [3, 0, 1, 0], [2, 1, 0, 3]]

		# key generation
		__magic_name__       :					Dict						=			apply_table(key, paa_table)
		__magic_name__       :					Union[str, Any]						=			temp[:5]
		__magic_name__       :					Optional[Any]						=			temp[5:]
		__magic_name__       :					str						=			left_shift(left)
		__magic_name__       :					List[str]						=			left_shift(right)
		__magic_name__       :					Tuple						=			apply_table(left + right, pa_table)
		__magic_name__       :					Dict						=			left_shift(left)
		__magic_name__       :					Union[str, Any]						=			left_shift(right)
		__magic_name__       :					List[Any]						=			left_shift(left)
		__magic_name__       :					str						=			left_shift(right)
		__magic_name__       :					List[str]						=			apply_table(left + right, pa_table)

		# encryption
		__magic_name__       :					List[str]						=			apply_table(message, IP)
		__magic_name__       :					str						=			function(expansion, sa, sa, keya, temp)
		__magic_name__       :					str						=			temp[4:] + temp[:4]
		__magic_name__       :					Optional[Any]						=			function(expansion, sa, sa, keya, temp)
		__magic_name__       :					Any						=			apply_table(temp, IP_inv)
		print("""Cipher text is:""", CT)

		# decryption
		__magic_name__       :					Tuple						=			apply_table(CT, IP)
		__magic_name__       :					List[str]						=			function(expansion, sa, sa, keya, temp)
		__magic_name__       :					Dict						=			temp[4:] + temp[:4]
		__magic_name__       :					int						=			function(expansion, sa, sa, keya, temp)
		__magic_name__       :					Any						=			apply_table(temp, IP_inv)
		print("""Plain text after decypting is:""", PT)



