

import copy
import os
from typing import Union

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


a		=logging.get_logger(__name__)

a		={
    """google/pix2struct-textcaps-base""": (
        """https://huggingface.co/google/pix2struct-textcaps-base/resolve/main/config.json"""
    ),
}






class 	A_		(	SCREAMING_SNAKE_CASE    ):
							_UpperCAmelCase   :  Dict										=				'''pix2struct_text_model'''
							_UpperCAmelCase   :  Union[str, Any]										=				['''past_key_values''']
							_UpperCAmelCase   :  str										=				{
							    '''hidden_size''': '''hidden_size''',
							    '''num_attention_heads''': '''num_heads''',
							    '''num_hidden_layers''': '''num_layers''',
							}
							def __init__(		self		:      Tuple       ,SCREAMING_SNAKE_CASE__		:      Union[str, Any]=5_0_2_4_4       ,SCREAMING_SNAKE_CASE__		:      Optional[int]=7_6_8       ,SCREAMING_SNAKE_CASE__		:      str=6_4       ,SCREAMING_SNAKE_CASE__		:      Dict=2_0_4_8       ,SCREAMING_SNAKE_CASE__		:      List[str]=1_2       ,SCREAMING_SNAKE_CASE__		:      int=1_2       ,SCREAMING_SNAKE_CASE__		:      Optional[Any]=3_2       ,SCREAMING_SNAKE_CASE__		:      List[str]=1_2_8       ,SCREAMING_SNAKE_CASE__		:      List[Any]=0.1       ,SCREAMING_SNAKE_CASE__		:      Any=1E-6       ,SCREAMING_SNAKE_CASE__		:      str=1.0       ,SCREAMING_SNAKE_CASE__		:      Optional[Any]="gelu_new"       ,SCREAMING_SNAKE_CASE__		:      Tuple=0       ,SCREAMING_SNAKE_CASE__		:      List[str]=False       ,SCREAMING_SNAKE_CASE__		:      str=0       ,SCREAMING_SNAKE_CASE__		:      Union[str, Any]=1       ,SCREAMING_SNAKE_CASE__		:      int=False       ,SCREAMING_SNAKE_CASE__		:      Dict=True       ,**SCREAMING_SNAKE_CASE__		:      Tuple       ,):
								__lowerCamelCase    :    int 	=			vocab_size
								__lowerCamelCase    :    List[str] 	=			hidden_size
								__lowerCamelCase    :    int 	=			d_kv
								__lowerCamelCase    :    str 	=			d_ff
								__lowerCamelCase    :    Optional[int] 	=			num_layers
								__lowerCamelCase    :    Optional[int] 	=			num_heads
								__lowerCamelCase    :    Optional[Any] 	=			relative_attention_num_buckets
								__lowerCamelCase    :    Any 	=			relative_attention_max_distance
								__lowerCamelCase    :    int 	=			dropout_rate
								__lowerCamelCase    :    Union[str, Any] 	=			layer_norm_epsilon
								__lowerCamelCase    :    Optional[Any] 	=			initializer_factor
								__lowerCamelCase    :    Optional[Any] 	=			use_cache

								__lowerCamelCase    :    str 	=			eos_token_id
								__lowerCamelCase    :    List[str] 	=			decoder_start_token_id

								# for backwards compatibility
								__lowerCamelCase    :    int 	=			dense_act_fn

								super().__init__(
								    pad_token_id=SCREAMING_SNAKE_CASE__       ,eos_token_id=SCREAMING_SNAKE_CASE__       ,decoder_start_token_id=SCREAMING_SNAKE_CASE__       ,tie_word_embeddings=SCREAMING_SNAKE_CASE__       ,is_decoder=SCREAMING_SNAKE_CASE__       ,**SCREAMING_SNAKE_CASE__       ,)


							@classmethod
							def    lowerCAmelCase					(		cls		:      str       ,SCREAMING_SNAKE_CASE__		:      Union[str, os.PathLike]       ,**SCREAMING_SNAKE_CASE__		:      Dict):
								cls._set_token_in_kwargs(SCREAMING_SNAKE_CASE__)

								__lowerCamelCase	,			__lowerCamelCase    :    Any 	=			cls.get_config_dict(SCREAMING_SNAKE_CASE__       ,**SCREAMING_SNAKE_CASE__)

								# get the text config dict if we are loading from Pix2StructConfig
								if config_dict.get('model_type') == "pix2struct":
									__lowerCamelCase    :    Dict 	=			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(SCREAMING_SNAKE_CASE__       ,**SCREAMING_SNAKE_CASE__)






class 	A_		(	SCREAMING_SNAKE_CASE    ):
							_UpperCAmelCase   :  Optional[Any]										=				'''pix2struct_vision_model'''
							def __init__(		self		:      Any       ,SCREAMING_SNAKE_CASE__		:      Dict=7_6_8       ,SCREAMING_SNAKE_CASE__		:      List[Any]=7_6_8       ,SCREAMING_SNAKE_CASE__		:      List[Any]=2_0_4_8       ,SCREAMING_SNAKE_CASE__		:      Dict=6_4       ,SCREAMING_SNAKE_CASE__		:      Any=1_2       ,SCREAMING_SNAKE_CASE__		:      str=1_2       ,SCREAMING_SNAKE_CASE__		:      Union[str, Any]="gelu_new"       ,SCREAMING_SNAKE_CASE__		:      Optional[int]=1E-6       ,SCREAMING_SNAKE_CASE__		:      str=0.0       ,SCREAMING_SNAKE_CASE__		:      str=0.0       ,SCREAMING_SNAKE_CASE__		:      int=1E-10       ,SCREAMING_SNAKE_CASE__		:      Optional[Any]=1.0       ,SCREAMING_SNAKE_CASE__		:      str=4_0_9_6       ,SCREAMING_SNAKE_CASE__		:      List[Any]=3_2       ,SCREAMING_SNAKE_CASE__		:      int=1_2_8       ,**SCREAMING_SNAKE_CASE__		:      List[str]       ,):
								super().__init__(**SCREAMING_SNAKE_CASE__)

								__lowerCamelCase    :    Any 	=			hidden_size
								__lowerCamelCase    :    Any 	=			patch_embed_hidden_size
								__lowerCamelCase    :    Any 	=			d_ff
								__lowerCamelCase    :    Optional[Any] 	=			dropout_rate
								__lowerCamelCase    :    List[str] 	=			num_hidden_layers
								__lowerCamelCase    :    Optional[int] 	=			num_attention_heads
								__lowerCamelCase    :    Dict 	=			initializer_range
								__lowerCamelCase    :    List[str] 	=			initializer_factor
								__lowerCamelCase    :    Union[str, Any] 	=			attention_dropout
								__lowerCamelCase    :    Any 	=			layer_norm_eps
								__lowerCamelCase    :    Dict 	=			dense_act_fn
								__lowerCamelCase    :    Tuple 	=			seq_len
								__lowerCamelCase    :    Union[str, Any] 	=			relative_attention_num_buckets
								__lowerCamelCase    :    Optional[Any] 	=			relative_attention_max_distance
								__lowerCamelCase    :    Tuple 	=			d_kv


							@classmethod
							def    lowerCAmelCase					(		cls		:      Optional[int]       ,SCREAMING_SNAKE_CASE__		:      Union[str, os.PathLike]       ,**SCREAMING_SNAKE_CASE__		:      Optional[int]):
								cls._set_token_in_kwargs(SCREAMING_SNAKE_CASE__)

								__lowerCamelCase	,			__lowerCamelCase    :    List[Any] 	=			cls.get_config_dict(SCREAMING_SNAKE_CASE__       ,**SCREAMING_SNAKE_CASE__)

								# get the vision config dict if we are loading from Pix2StructConfig
								if config_dict.get('model_type') == "pix2struct":
									__lowerCamelCase    :    Tuple 	=			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(SCREAMING_SNAKE_CASE__       ,**SCREAMING_SNAKE_CASE__)






class 	A_		(	SCREAMING_SNAKE_CASE    ):
							_UpperCAmelCase   :  Optional[int]										=				'''pix2struct'''
							_UpperCAmelCase   :  List[str]										=				True
							def __init__(		self		:      List[Any]       ,SCREAMING_SNAKE_CASE__		:      List[str]=None       ,SCREAMING_SNAKE_CASE__		:      Optional[int]=None       ,SCREAMING_SNAKE_CASE__		:      Union[str, Any]=1.0       ,SCREAMING_SNAKE_CASE__		:      str=0.02       ,SCREAMING_SNAKE_CASE__		:      Tuple=False       ,SCREAMING_SNAKE_CASE__		:      Optional[Any]=False       ,SCREAMING_SNAKE_CASE__		:      Union[str, Any]=True       ,**SCREAMING_SNAKE_CASE__		:      List[Any]       ,):
								super().__init__(tie_word_embeddings=SCREAMING_SNAKE_CASE__       ,is_encoder_decoder=SCREAMING_SNAKE_CASE__       ,**SCREAMING_SNAKE_CASE__)

								if text_config is None:
									__lowerCamelCase    :    Any 	=			{}
									logger.info('text_config is None. Initializing the Pix2StructTextConfig with default values.')

								if vision_config is None:
									__lowerCamelCase    :    Union[str, Any] 	=			{}
									logger.info('vision_config is None. Initializing the Pix2StructVisionConfig with default values.')

								__lowerCamelCase    :    Dict 	=			PixaStructTextConfig(**SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Any 	=			PixaStructVisionConfig(**SCREAMING_SNAKE_CASE__)

								__lowerCamelCase    :    int 	=			self.text_config.decoder_start_token_id
								__lowerCamelCase    :    Optional[int] 	=			self.text_config.pad_token_id
								__lowerCamelCase    :    Any 	=			self.text_config.eos_token_id

								__lowerCamelCase    :    Optional[Any] 	=			initializer_factor
								__lowerCamelCase    :    Optional[Any] 	=			initializer_range

								__lowerCamelCase    :    Optional[Any] 	=			self.initializer_range
								__lowerCamelCase    :    Tuple 	=			self.initializer_range

								__lowerCamelCase    :    Any 	=			is_vqa
							@classmethod
							def    lowerCAmelCase					(		cls		:      Optional[int]       ,SCREAMING_SNAKE_CASE__		:      PixaStructTextConfig       ,SCREAMING_SNAKE_CASE__		:      PixaStructVisionConfig       ,**SCREAMING_SNAKE_CASE__		:      Dict):
								return cls(text_config=text_config.to_dict()       ,vision_config=vision_config.to_dict()       ,**SCREAMING_SNAKE_CASE__)


							def    lowerCAmelCase					(		self		:      Union[str, Any]):
								__lowerCamelCase    :    List[Any] 	=			copy.deepcopy(self.__dict__)
								__lowerCamelCase    :    Union[str, Any] 	=			self.text_config.to_dict()
								__lowerCamelCase    :    Dict 	=			self.vision_config.to_dict()
								__lowerCamelCase    :    Dict 	=			self.__class__.model_type
								return output







import os
import random
import sys

from . import cryptomath_module as cryptomath
from . import rabin_miller

a		=3






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__      )  ->					int:
	print('Generating primitive root of p'      )
	while True:
		__lowerCamelCase    :    Tuple 	=			random.randrange(3     ,			lowerCamelCase__      )
		if pow(lowerCamelCase__     ,			2     ,			lowerCamelCase__      ) == 1:
			continue
		if pow(lowerCamelCase__     ,			lowerCamelCase__     ,			lowerCamelCase__      ) == 1:
			continue
		return g






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__      )  ->					tuple[tuple[int, int, int, int], tuple[int, int]]:
	print('Generating prime p...'      )
	__lowerCamelCase    :    List[str] 	=			rabin_miller.generate_large_prime(lowerCamelCase__      )  # select large prime number.
	__lowerCamelCase    :    Dict 	=			primitive_root(lowerCamelCase__      )  # one primitive root on modulo p.
	__lowerCamelCase    :    Optional[int] 	=			random.randrange(3     ,			lowerCamelCase__      )  # private_key -> have to be greater than 2 for safety.
	__lowerCamelCase    :    List[Any] 	=			cryptomath.find_mod_inverse(pow(lowerCamelCase__     ,			lowerCamelCase__     ,			lowerCamelCase__      )     ,			lowerCamelCase__      )

	__lowerCamelCase    :    int 	=			(key_size, e_a, e_a, p)
	__lowerCamelCase    :    str 	=			(key_size, d)

	return public_key, private_key






def        SCREAMING_SNAKE_CASE__	(  lowerCamelCase__     ,			lowerCamelCase__      )  ->					None:
	if os.path.exists(F"{name}_pubkey.txt"      ) or os.path.exists(F"{name}_privkey.txt"      ):
		print('\nWARNING:'      )
		print(
		    F"\"{name}_pubkey.txt\" or \"{name}_privkey.txt\" already exists. \n"
		    'Use a different name or delete these files and re-run this program.'      )
		sys.exit()

	__lowerCamelCase	,			__lowerCamelCase    :    List[Any] 	=			generate_key(lowerCamelCase__      )
	print(F"\nWriting public key to file {name}_pubkey.txt..."      )
	with open(F"{name}_pubkey.txt"     ,			'w'      ) as fo:
		fo.write(F"{public_key[0]},{public_key[1]},{public_key[2]},{public_key[3]}"      )

	print(F"Writing private key to file {name}_privkey.txt..."      )
	with open(F"{name}_privkey.txt"     ,			'w'      ) as fo:
		fo.write(F"{private_key[0]},{private_key[1]}"      )






def        SCREAMING_SNAKE_CASE__	(  )  ->					None:
	print('Making key files...'      )
	make_key_files('elgamal'     ,			2_0_4_8      )
	print('Key files generation successful'      )


if __name__ == "__main__":
					main()




