



'''simple docstring'''

import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING


__lowerCAmelCase						      =       logging.get_logger(__name__)

__lowerCAmelCase						      =       {
    "salesforce/blip2-opt-2.7b": "https://huggingface.co/salesforce/blip2-opt-2.7b/resolve/main/config.json",
}

class      __magic_name__						(   SCREAMING_SNAKE_CASE__       ):
       lowerCAmelCase	:   Dict           = 'blip_2_vision_model'







       def __init__(							self :	Dict     ,_UpperCAmelCase :	int=1408     ,_UpperCAmelCase :	Any=6144     ,_UpperCAmelCase :	Union[str, Any]=39     ,_UpperCAmelCase :	Union[str, Any]=16     ,_UpperCAmelCase :	List[str]=224     ,_UpperCAmelCase :	Optional[int]=14     ,_UpperCAmelCase :	Tuple="gelu"     ,_UpperCAmelCase :	Tuple=0.0_00_01     ,_UpperCAmelCase :	Dict=0.0     ,_UpperCAmelCase :	Union[str, Any]=1E-10     ,_UpperCAmelCase :	int=True     ,**_UpperCAmelCase :	Tuple     ,):
         super().__init__(**a_		)

         _a					:				Union[str, Any]				=							hidden_size
         _a					:				List[str]				=							intermediate_size
         _a					:				Dict				=							num_hidden_layers
         _a					:				List[Any]				=							num_attention_heads
         _a					:				Any				=							patch_size
         _a					:				Union[str, Any]				=							image_size
         _a					:				Union[str, Any]				=							initializer_range
         _a					:				Union[str, Any]				=							attention_dropout
         _a					:				Optional[int]				=							layer_norm_eps
         _a					:				Optional[Any]				=							hidden_act
         _a					:				List[str]				=							qkv_bias







       @classmethod
       def 							__lowercase      (							cls :	Any     ,_UpperCAmelCase :	Union[str, os.PathLike]     ,**_UpperCAmelCase :	Any		):
         cls._set_token_in_kwargs(a_		)

         _a	, _a					:				Optional[Any]				=							cls.get_config_dict(a_     ,**a_		)

         # get the vision config dict if we are loading from Blip2Config
         if config_dict.get('model_type'		) == "blip-2":
           _a					:				Any				=							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(a_     ,**a_		)

class      __magic_name__						(   SCREAMING_SNAKE_CASE__       ):
       lowerCAmelCase	:   Optional[int]           = 'blip_2_qformer'







       def __init__(							self :	Tuple     ,_UpperCAmelCase :	Tuple=30522     ,_UpperCAmelCase :	Any=768     ,_UpperCAmelCase :	Union[str, Any]=12     ,_UpperCAmelCase :	Optional[int]=12     ,_UpperCAmelCase :	Union[str, Any]=3072     ,_UpperCAmelCase :	List[Any]="gelu"     ,_UpperCAmelCase :	Dict=0.1     ,_UpperCAmelCase :	Dict=0.1     ,_UpperCAmelCase :	List[Any]=512     ,_UpperCAmelCase :	Any=0.02     ,_UpperCAmelCase :	Optional[Any]=1E-12     ,_UpperCAmelCase :	str=0     ,_UpperCAmelCase :	List[str]="absolute"     ,_UpperCAmelCase :	List[str]=2     ,_UpperCAmelCase :	List[Any]=1408     ,**_UpperCAmelCase :	Tuple     ,):
         super().__init__(pad_token_id=a_     ,**a_		)

         _a					:				int				=							vocab_size
         _a					:				Optional[Any]				=							hidden_size
         _a					:				str				=							num_hidden_layers
         _a					:				List[Any]				=							num_attention_heads
         _a					:				List[Any]				=							hidden_act
         _a					:				int				=							intermediate_size
         _a					:				Optional[Any]				=							hidden_dropout_prob
         _a					:				List[Any]				=							attention_probs_dropout_prob
         _a					:				Optional[int]				=							max_position_embeddings
         _a					:				List[Any]				=							initializer_range
         _a					:				Optional[Any]				=							layer_norm_eps
         _a					:				Any				=							position_embedding_type
         _a					:				Optional[int]				=							cross_attention_frequency
         _a					:				Tuple				=							encoder_hidden_size







       @classmethod
       def 							__lowercase      (							cls :	Optional[int]     ,_UpperCAmelCase :	Union[str, os.PathLike]     ,**_UpperCAmelCase :	List[str]		):
         cls._set_token_in_kwargs(a_		)

         _a	, _a					:				Dict				=							cls.get_config_dict(a_     ,**a_		)

         # get the qformer config dict if we are loading from Blip2Config
         if config_dict.get('model_type'		) == "blip-2":
           _a					:				int				=							config_dict['qformer_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(a_     ,**a_		)

class      __magic_name__						(   SCREAMING_SNAKE_CASE__       ):
       lowerCAmelCase	:   Optional[int]           = 'blip-2'
       lowerCAmelCase	:   Dict           = True







       def __init__(							self :	Dict     ,_UpperCAmelCase :	List[Any]=None     ,_UpperCAmelCase :	Optional[Any]=None     ,_UpperCAmelCase :	Dict=None     ,_UpperCAmelCase :	Tuple=32     ,**_UpperCAmelCase :	Optional[int]		):
         super().__init__(**a_		)

         if vision_config is None:
           _a					:				List[Any]				=							{}
           logger.info('vision_config is None. initializing the Blip2VisionConfig with default values.'		)

         if qformer_config is None:
           _a					:				List[Any]				=							{}
           logger.info('qformer_config is None. Initializing the Blip2QFormerConfig with default values.'		)

         if text_config is None:
           _a					:				Optional[Any]				=							{}
           logger.info('text_config is None. Initializing the text config with default values (`OPTConfig`).'		)

         _a					:				Optional[Any]				=							BlipaVisionConfig(**a_		)
         _a					:				Optional[Any]				=							BlipaQFormerConfig(**a_		)
         _a					:				Optional[Any]				=							text_config['model_type'] if 'model_type' in text_config else 'opt'
         _a					:				Dict				=							CONFIG_MAPPING[text_model_type](**a_		)

         _a					:				Dict				=							self.text_config.tie_word_embeddings
         _a					:				Union[str, Any]				=							self.text_config.is_encoder_decoder

         _a					:				str				=							num_query_tokens
         _a					:				int				=							self.vision_config.hidden_size
         _a					:				Optional[int]				=							self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
         _a					:				int				=							1.0
         _a					:				Any				=							0.02







       @classmethod
       def 							__lowercase      (							cls :	int     ,_UpperCAmelCase :	BlipaVisionConfig     ,_UpperCAmelCase :	BlipaQFormerConfig     ,_UpperCAmelCase :	PretrainedConfig     ,**_UpperCAmelCase :	int     ,):
         return cls(
             vision_config=vision_config.to_dict()     ,qformer_config=qformer_config.to_dict()     ,text_config=text_config.to_dict()     ,**a_     ,)







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









'''simple docstring'''

from binascii import hexlify
from hashlib import shaaaa
from os import urandom

# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526

__lowerCAmelCase						      =       {
    # 1536-bit
    5: {
        '''prime''': int(
            '''FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1'''
            + '''29024E088A67CC74020BBEA63B139B22514A08798E3404DD'''
            + '''EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245'''
            + '''E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED'''
            + '''EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D'''
            + '''C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F'''
            + '''83655D23DCA3AD961C62F356208552BB9ED529077096966D'''
            + '''670C354E4ABC9804F1746C08CA237327FFFFFFFFFFFFFFFF''',
            base=16,
        ),
        '''generator''': 2,
    },
    # 2048-bit
    14: {
        '''prime''': int(
            '''FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1'''
            + '''29024E088A67CC74020BBEA63B139B22514A08798E3404DD'''
            + '''EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245'''
            + '''E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED'''
            + '''EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D'''
            + '''C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F'''
            + '''83655D23DCA3AD961C62F356208552BB9ED529077096966D'''
            + '''670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B'''
            + '''E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9'''
            + '''DE2BCBF6955817183995497CEA956AE515D2261898FA0510'''
            + '''15728E5A8AACAA68FFFFFFFFFFFFFFFF''',
            base=16,
        ),
        '''generator''': 2,
    },
    # 3072-bit
    15: {
        '''prime''': int(
            '''FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1'''
            + '''29024E088A67CC74020BBEA63B139B22514A08798E3404DD'''
            + '''EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245'''
            + '''E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED'''
            + '''EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D'''
            + '''C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F'''
            + '''83655D23DCA3AD961C62F356208552BB9ED529077096966D'''
            + '''670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B'''
            + '''E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9'''
            + '''DE2BCBF6955817183995497CEA956AE515D2261898FA0510'''
            + '''15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64'''
            + '''ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7'''
            + '''ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B'''
            + '''F12FFA06D98A0864D87602733EC86A64521F2B18177B200C'''
            + '''BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31'''
            + '''43DB5BFCE0FD108E4B82D120A93AD2CAFFFFFFFFFFFFFFFF''',
            base=16,
        ),
        '''generator''': 2,
    },
    # 4096-bit
    16: {
        '''prime''': int(
            '''FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1'''
            + '''29024E088A67CC74020BBEA63B139B22514A08798E3404DD'''
            + '''EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245'''
            + '''E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED'''
            + '''EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D'''
            + '''C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F'''
            + '''83655D23DCA3AD961C62F356208552BB9ED529077096966D'''
            + '''670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B'''
            + '''E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9'''
            + '''DE2BCBF6955817183995497CEA956AE515D2261898FA0510'''
            + '''15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64'''
            + '''ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7'''
            + '''ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B'''
            + '''F12FFA06D98A0864D87602733EC86A64521F2B18177B200C'''
            + '''BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31'''
            + '''43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7'''
            + '''88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA'''
            + '''2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6'''
            + '''287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED'''
            + '''1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9'''
            + '''93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934063199'''
            + '''FFFFFFFFFFFFFFFF''',
            base=16,
        ),
        '''generator''': 2,
    },
    # 6144-bit
    17: {
        '''prime''': int(
            '''FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD129024E08'''
            + '''8A67CC74020BBEA63B139B22514A08798E3404DDEF9519B3CD3A431B'''
            + '''302B0A6DF25F14374FE1356D6D51C245E485B576625E7EC6F44C42E9'''
            + '''A637ED6B0BFF5CB6F406B7EDEE386BFB5A899FA5AE9F24117C4B1FE6'''
            + '''49286651ECE45B3DC2007CB8A163BF0598DA48361C55D39A69163FA8'''
            + '''FD24CF5F83655D23DCA3AD961C62F356208552BB9ED529077096966D'''
            + '''670C354E4ABC9804F1746C08CA18217C32905E462E36CE3BE39E772C'''
            + '''180E86039B2783A2EC07A28FB5C55DF06F4C52C9DE2BCBF695581718'''
            + '''3995497CEA956AE515D2261898FA051015728E5A8AAAC42DAD33170D'''
            + '''04507A33A85521ABDF1CBA64ECFB850458DBEF0A8AEA71575D060C7D'''
            + '''B3970F85A6E1E4C7ABF5AE8CDB0933D71E8C94E04A25619DCEE3D226'''
            + '''1AD2EE6BF12FFA06D98A0864D87602733EC86A64521F2B18177B200C'''
            + '''BBE117577A615D6C770988C0BAD946E208E24FA074E5AB3143DB5BFC'''
            + '''E0FD108E4B82D120A92108011A723C12A787E6D788719A10BDBA5B26'''
            + '''99C327186AF4E23C1A946834B6150BDA2583E9CA2AD44CE8DBBBC2DB'''
            + '''04DE8EF92E8EFC141FBECAA6287C59474E6BC05D99B2964FA090C3A2'''
            + '''233BA186515BE7ED1F612970CEE2D7AFB81BDD762170481CD0069127'''
            + '''D5B05AA993B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492'''
            + '''36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BDF8FF9406'''
            + '''AD9E530EE5DB382F413001AEB06A53ED9027D831179727B0865A8918'''
            + '''DA3EDBEBCF9B14ED44CE6CBACED4BB1BDB7F1447E6CC254B33205151'''
            + '''2BD7AF426FB8F401378CD2BF5983CA01C64B92ECF032EA15D1721D03'''
            + '''F482D7CE6E74FEF6D55E702F46980C82B5A84031900B1C9E59E7C97F'''
            + '''BEC7E8F323A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA'''
            + '''CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE32806A1D58B'''
            + '''B7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55CDA56C9EC2EF29632'''
            + '''387FE8D76E3C0468043E8F663F4860EE12BF2D5B0B7474D6E694F91E'''
            + '''6DCC4024FFFFFFFFFFFFFFFF''',
            base=16,
        ),
        '''generator''': 2,
    },
    # 8192-bit
    18: {
        '''prime''': int(
            '''FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1'''
            + '''29024E088A67CC74020BBEA63B139B22514A08798E3404DD'''
            + '''EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245'''
            + '''E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED'''
            + '''EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D'''
            + '''C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F'''
            + '''83655D23DCA3AD961C62F356208552BB9ED529077096966D'''
            + '''670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B'''
            + '''E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9'''
            + '''DE2BCBF6955817183995497CEA956AE515D2261898FA0510'''
            + '''15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64'''
            + '''ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7'''
            + '''ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B'''
            + '''F12FFA06D98A0864D87602733EC86A64521F2B18177B200C'''
            + '''BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31'''
            + '''43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7'''
            + '''88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA'''
            + '''2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6'''
            + '''287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED'''
            + '''1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9'''
            + '''93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492'''
            + '''36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BD'''
            + '''F8FF9406AD9E530EE5DB382F413001AEB06A53ED9027D831'''
            + '''179727B0865A8918DA3EDBEBCF9B14ED44CE6CBACED4BB1B'''
            + '''DB7F1447E6CC254B332051512BD7AF426FB8F401378CD2BF'''
            + '''5983CA01C64B92ECF032EA15D1721D03F482D7CE6E74FEF6'''
            + '''D55E702F46980C82B5A84031900B1C9E59E7C97FBEC7E8F3'''
            + '''23A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA'''
            + '''CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE328'''
            + '''06A1D58BB7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55C'''
            + '''DA56C9EC2EF29632387FE8D76E3C0468043E8F663F4860EE'''
            + '''12BF2D5B0B7474D6E694F91E6DBE115974A3926F12FEE5E4'''
            + '''38777CB6A932DF8CD8BEC4D073B931BA3BC832B68D9DD300'''
            + '''741FA7BF8AFC47ED2576F6936BA424663AAB639C5AE4F568'''
            + '''3423B4742BF1C978238F16CBE39D652DE3FDB8BEFC848AD9'''
            + '''22222E04A4037C0713EB57A81A23F0C73473FC646CEA306B'''
            + '''4BCBC8862F8385DDFA9D4B7FA2C087E879683303ED5BDD3A'''
            + '''062B3CF5B3A278A66D2A13F83F44F82DDF310EE074AB6A36'''
            + '''4597E899A0255DC164F31CC50846851DF9AB48195DED7EA1'''
            + '''B1D510BD7EE74D73FAF36BC31ECFA268359046F4EB879F92'''
            + '''4009438B481C6CD7889A002ED5EE382BC9190DA6FC026E47'''
            + '''9558E4475677E9AA9E3050E2765694DFC81F56E880B96E71'''
            + '''60C980DD98EDD3DFFFFFFFFFFFFFFFFF''',
            base=16,
        ),
        '''generator''': 2,
    },
}

class      __magic_name__						:







							def __init__(							self :	Union[str, Any]     ,_UpperCAmelCase :	int = 14		):
									if group not in primes:
											raise ValueError('Unsupported Group'		)
									_a					:				str				=							primes[group]['prime']
									_a					:				Optional[int]				=							primes[group]['generator']

									_a					:				Tuple				=							int(hexlify(urandom(32		)		)     ,base=16		)







							def 							__lowercase      (							self :	Dict		):
									return hex(self.__private_key		)[2:]







							def 							__lowercase      (							self :	List[str]		):
									_a					:				int				=							pow(self.generator     ,self.__private_key     ,self.prime		)
									return hex(_UpperCAmelCase		)[2:]







							def 							__lowercase      (							self :	int     ,_UpperCAmelCase :	int		):
									# check if the other public key is valid based on NIST SP800-56
									return (
									    2 <= key <= self.prime - 2
									    and pow(_UpperCAmelCase     ,(self.prime - 1) // 2     ,self.prime		) == 1
									)







							def 							__lowercase      (							self :	Tuple     ,_UpperCAmelCase :	str		):
									_a					:				List[Any]				=							int(_UpperCAmelCase     ,base=16		)
									if not self.is_valid_public_key(_UpperCAmelCase		):
											raise ValueError('Invalid public key'		)
									_a					:				Any				=							pow(_UpperCAmelCase     ,self.__private_key     ,self.prime		)
									return shaaaa(str(_UpperCAmelCase		).encode()		).hexdigest()







							@staticmethod
							def 							__lowercase      (							_UpperCAmelCase :	int     ,_UpperCAmelCase :	int		):
									# check if the other public key is valid based on NIST SP800-56
									return (
									    2 <= remote_public_key_str <= prime - 2
									    and pow(_UpperCAmelCase     ,(prime - 1) // 2     ,_UpperCAmelCase		) == 1
									)







							@staticmethod
							def 							__lowercase      (							_UpperCAmelCase :	str     ,_UpperCAmelCase :	str     ,_UpperCAmelCase :	int = 14		):
									_a					:				str				=							int(_UpperCAmelCase     ,base=16		)
									_a					:				int				=							int(_UpperCAmelCase     ,base=16		)
									_a					:				Any				=							primes[group]['prime']
									if not DiffieHellman.is_valid_public_key_static(_UpperCAmelCase     ,_UpperCAmelCase		):
											raise ValueError('Invalid public key'		)
									_a					:				List[str]				=							pow(_UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase		)
									return shaaaa(str(_UpperCAmelCase		).encode()		).hexdigest()


if __name__ == "__main__":
							import doctest

							doctest.testmod()




