






"""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


lowercase    			=       logging.get_logger(__name__)

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

class 						A_							(      lowercase_  ):
				UpperCAmelCase__        =				'''blip_2_vision_model'''







				def __init__(							self							:						Dict						,    __lowerCamelCase							:						Optional[Any]=1_4_0_8						,    __lowerCamelCase							:						Optional[int]=6_1_4_4						,    __lowerCamelCase							:						str=3_9						,    __lowerCamelCase							:						Union[str, Any]=1_6						,    __lowerCamelCase							:						str=2_2_4						,    __lowerCamelCase							:						Dict=1_4						,    __lowerCamelCase							:						Union[str, Any]="gelu"						,    __lowerCamelCase							:						List[str]=0.0_0001						,    __lowerCamelCase							:						Any=0.0						,    __lowerCamelCase							:						List[str]=1e-10						,    __lowerCamelCase							:						Dict=True						,    **__lowerCamelCase							:						Optional[int]						,    )				->					List[str]:
										super().__init__(**lowerCamelCase_	)

										__magic_name__            =     hidden_size
										__magic_name__            =     intermediate_size
										__magic_name__            =     num_hidden_layers
										__magic_name__            =     num_attention_heads
										__magic_name__            =     patch_size
										__magic_name__            =     image_size
										__magic_name__            =     initializer_range
										__magic_name__            =     attention_dropout
										__magic_name__            =     layer_norm_eps
										__magic_name__            =     hidden_act
										__magic_name__            =     qkv_bias







				@classmethod
				def     _snake_case					(							cls							:						List[Any]						,    __lowerCamelCase							:						Union[str, os.PathLike]						,    **__lowerCamelCase							:						str	)				->					str:
										cls._set_token_in_kwargs(lowerCamelCase_	)

										__magic_name__            =     cls.get_config_dict(lowerCamelCase_						,    **lowerCamelCase_	)

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





class 						A_							(      lowercase_  ):
				UpperCAmelCase__        =				'''blip_2_qformer'''







				def __init__(							self							:						List[Any]						,    __lowerCamelCase							:						str=3_0_5_2_2						,    __lowerCamelCase							:						Union[str, Any]=7_6_8						,    __lowerCamelCase							:						Any=1_2						,    __lowerCamelCase							:						str=1_2						,    __lowerCamelCase							:						Union[str, Any]=3_0_7_2						,    __lowerCamelCase							:						List[Any]="gelu"						,    __lowerCamelCase							:						Dict=0.1						,    __lowerCamelCase							:						Dict=0.1						,    __lowerCamelCase							:						Dict=5_1_2						,    __lowerCamelCase							:						Optional[Any]=0.02						,    __lowerCamelCase							:						str=1e-12						,    __lowerCamelCase							:						Dict=0						,    __lowerCamelCase							:						Optional[Any]="absolute"						,    __lowerCamelCase							:						Tuple=2						,    __lowerCamelCase							:						Optional[Any]=1_4_0_8						,    **__lowerCamelCase							:						List[str]						,    )				->					int:
										super().__init__(pad_token_id=lowerCamelCase_						,    **lowerCamelCase_	)

										__magic_name__            =     vocab_size
										__magic_name__            =     hidden_size
										__magic_name__            =     num_hidden_layers
										__magic_name__            =     num_attention_heads
										__magic_name__            =     hidden_act
										__magic_name__            =     intermediate_size
										__magic_name__            =     hidden_dropout_prob
										__magic_name__            =     attention_probs_dropout_prob
										__magic_name__            =     max_position_embeddings
										__magic_name__            =     initializer_range
										__magic_name__            =     layer_norm_eps
										__magic_name__            =     position_embedding_type
										__magic_name__            =     cross_attention_frequency
										__magic_name__            =     encoder_hidden_size







				@classmethod
				def     _snake_case					(							cls							:						Union[str, Any]						,    __lowerCamelCase							:						Union[str, os.PathLike]						,    **__lowerCamelCase							:						Any	)				->					str:
										cls._set_token_in_kwargs(lowerCamelCase_	)

										__magic_name__            =     cls.get_config_dict(lowerCamelCase_						,    **lowerCamelCase_	)

										# get the qformer config dict if we are loading from Blip2Config
										if config_dict.get("model_type"	) == "blip-2":
																__magic_name__            =     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(lowerCamelCase_						,    **lowerCamelCase_	)





class 						A_							(      lowercase_  ):
				UpperCAmelCase__        =				'''blip-2'''
				UpperCAmelCase__        =				True







				def __init__(							self							:						List[Any]						,    __lowerCamelCase							:						List[str]=None						,    __lowerCamelCase							:						Any=None						,    __lowerCamelCase							:						Dict=None						,    __lowerCamelCase							:						str=3_2						,    **__lowerCamelCase							:						Any	)				->					Union[str, Any]:
										super().__init__(**lowerCamelCase_	)

										if vision_config is None:
																__magic_name__            =     {}
																logger.info("vision_config is None. initializing the Blip2VisionConfig with default values."	)

										if qformer_config is None:
																__magic_name__            =     {}
																logger.info("qformer_config is None. Initializing the Blip2QFormerConfig with default values."	)

										if text_config is None:
																__magic_name__            =     {}
																logger.info("text_config is None. Initializing the text config with default values (`OPTConfig`)."	)

										__magic_name__            =     BlipaVisionConfig(**lowerCamelCase_	)
										__magic_name__            =     BlipaQFormerConfig(**lowerCamelCase_	)
										__magic_name__            =     text_config["""model_type"""] if """model_type""" in text_config else """opt"""
										__magic_name__            =     CONFIG_MAPPING[text_model_type](**lowerCamelCase_	)

										__magic_name__            =     self.text_config.tie_word_embeddings
										__magic_name__            =     self.text_config.is_encoder_decoder

										__magic_name__            =     num_query_tokens
										__magic_name__            =     self.vision_config.hidden_size
										__magic_name__            =     self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
										__magic_name__            =     1.0
										__magic_name__            =     0.02







				@classmethod
				def     _snake_case					(							cls							:						int						,    __lowerCamelCase							:						BlipaVisionConfig						,    __lowerCamelCase							:						BlipaQFormerConfig						,    __lowerCamelCase							:						PretrainedConfig						,    **__lowerCamelCase							:						Tuple						,    )				->					str:
										return cls(
										    vision_config=vision_config.to_dict()						,    qformer_config=qformer_config.to_dict()						,    text_config=text_config.to_dict()						,    **lowerCamelCase_						,    )







				def     _snake_case					(							self							:						Optional[Any]	)				->					Optional[Any]:
										__magic_name__            =     copy.deepcopy(self.__dict__	)
										__magic_name__            =     self.vision_config.to_dict()
										__magic_name__            =     self.qformer_config.to_dict()
										__magic_name__            =     self.text_config.to_dict()
										__magic_name__            =     self.__class__.model_type
										return output











"""simple docstring"""

def _lowerCAmelCase	(  __lowerCamelCase:str   ):

						'''simple docstring'''






						return "".join(chr(ord(__lowerCamelCase   ) - 3_2   ) if "a" <= char <= "z" else char for char in word   )


if __name__ == "__main__":
			from doctest import testmod

			testmod()



