

"""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


snake_case_   :   Any        =       logging.get_logger(__name__)

snake_case_   :   Tuple        =       {
    """Salesforce/instruct-blip-flan-t5""": """https://huggingface.co/Salesforce/instruct-blip-flan-t5/resolve/main/config.json""",
}







class       snake_case__  ( _lowerCAmelCase     ):
			SCREAMING_SNAKE_CASE__     				=						'instructblip_vision_model'







			def __init__(			self			: str			,  lowercase			: Optional[int]=14_08			,  lowercase			: Any=61_44			,  lowercase			: Dict=39			,  lowercase			: Optional[int]=16			,  lowercase			: Optional[Any]=2_24			,  lowercase			: List[Any]=14			,  lowercase			: Optional[Any]="gelu"			,  lowercase			: List[str]=1E-6			,  lowercase			: int=0.0			,  lowercase			: Tuple=1E-10			,  lowercase			: List[Any]=True			,  **lowercase			: Tuple			,  ):





								'''simple docstring'''



								super().__init__(**_lowerCAmelCase  )

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







			@classmethod
			def 			__lowerCAmelCase				(			cls			: Tuple			,  lowercase			: Union[str, os.PathLike]			,  **lowercase			: Optional[int]  ):





								'''simple docstring'''



								cls._set_token_in_kwargs(_lowerCAmelCase  )

								UpperCAmelCase      ,							UpperCAmelCase			:   List[Any]      =				cls.get_config_dict(_lowerCAmelCase			,  **_lowerCAmelCase  )

								# get the vision config dict if we are loading from InstructBlipConfig
								if config_dict.get("model_type"  ) == "instructblip":
													UpperCAmelCase			:   List[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(_lowerCAmelCase			,  **_lowerCAmelCase  )







class       snake_case__  ( _lowerCAmelCase     ):
			SCREAMING_SNAKE_CASE__     				=						'instructblip_qformer'







			def __init__(			self			: Dict			,  lowercase			: Optional[Any]=3_05_22			,  lowercase			: Union[str, Any]=7_68			,  lowercase			: Dict=12			,  lowercase			: int=12			,  lowercase			: Optional[Any]=30_72			,  lowercase			: str="gelu"			,  lowercase			: Union[str, Any]=0.1			,  lowercase			: str=0.1			,  lowercase			: Any=5_12			,  lowercase			: List[str]=0.0_2			,  lowercase			: int=1E-12			,  lowercase			: Any=0			,  lowercase			: Tuple="absolute"			,  lowercase			: Optional[int]=2			,  lowercase			: List[Any]=14_08			,  **lowercase			: str			,  ):





								'''simple docstring'''



								super().__init__(pad_token_id=_lowerCAmelCase			,  **_lowerCAmelCase  )

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







			@classmethod
			def 			__lowerCAmelCase				(			cls			: Optional[Any]			,  lowercase			: Union[str, os.PathLike]			,  **lowercase			: List[Any]  ):





								'''simple docstring'''



								cls._set_token_in_kwargs(_lowerCAmelCase  )

								UpperCAmelCase      ,							UpperCAmelCase			:   Tuple      =				cls.get_config_dict(_lowerCAmelCase			,  **_lowerCAmelCase  )

								# get the qformer config dict if we are loading from InstructBlipConfig
								if config_dict.get("model_type"  ) == "instructblip":
													UpperCAmelCase			:   List[Any]      =				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       snake_case__  ( _lowerCAmelCase     ):
			SCREAMING_SNAKE_CASE__     				=						'instructblip'
			SCREAMING_SNAKE_CASE__     				=						True







			def __init__(			self			: Optional[Any]			,  lowercase			: str=None			,  lowercase			: Union[str, Any]=None			,  lowercase			: Optional[int]=None			,  lowercase			: Dict=32			,  **lowercase			: List[str]  ):





								'''simple docstring'''



								super().__init__(**_lowerCAmelCase  )

								if vision_config is None:
													UpperCAmelCase			:   Optional[Any]      =				{}
													logger.info("vision_config is None. initializing the InstructBlipVisionConfig with default values."  )

								if qformer_config is None:
													UpperCAmelCase			:   Union[str, Any]      =				{}
													logger.info("qformer_config is None. Initializing the InstructBlipQFormerConfig with default values."  )

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

								UpperCAmelCase			:   Union[str, Any]      =				InstructBlipVisionConfig(**_lowerCAmelCase  )
								UpperCAmelCase			:   Tuple      =				InstructBlipQFormerConfig(**_lowerCAmelCase  )
								UpperCAmelCase			:   Optional[int]      =				text_config["model_type"] if "model_type" in text_config else "opt"
								UpperCAmelCase			:   Dict      =				CONFIG_MAPPING[text_model_type](**_lowerCAmelCase  )

								UpperCAmelCase			:   List[Any]      =				self.text_config.tie_word_embeddings
								UpperCAmelCase			:   List[str]      =				self.text_config.is_encoder_decoder

								UpperCAmelCase			:   int      =				num_query_tokens
								UpperCAmelCase			:   Dict      =				self.vision_config.hidden_size
								UpperCAmelCase			:   List[str]      =				self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
								UpperCAmelCase			:   Tuple      =				1.0
								UpperCAmelCase			:   Dict      =				0.0_2







			@classmethod
			def 			__lowerCAmelCase				(			cls			: Optional[Any]			,  lowercase			: InstructBlipVisionConfig			,  lowercase			: InstructBlipQFormerConfig			,  lowercase			: PretrainedConfig			,  **lowercase			: Any			,  ):





								'''simple docstring'''



								return cls(
								    vision_config=vision_config.to_dict()			,  qformer_config=qformer_config.to_dict()			,  text_config=text_config.to_dict()			,  **_lowerCAmelCase			,  )







			def 			__lowerCAmelCase				(			self			: Dict  ):





								'''simple docstring'''



								UpperCAmelCase			:   Optional[int]      =				copy.deepcopy(self.__dict__  )
								UpperCAmelCase			:   int      =				self.vision_config.to_dict()
								UpperCAmelCase			:   str      =				self.qformer_config.to_dict()
								UpperCAmelCase			:   Union[str, Any]      =				self.text_config.to_dict()
								UpperCAmelCase			:   Optional[int]      =				self.__class__.model_type
								return output





"""simple docstring"""






snake_case_   :   List[str]        =       6_5_5_2_1



def   lowercase_	(    _lowercase       :		str	):




					'''simple docstring'''






					UpperCAmelCase			:   Dict      =				1
					UpperCAmelCase			:   Optional[int]      =				0
					for plain_chr in plain_text:
										UpperCAmelCase			:   int      =				(a + ord(_lowercase	)) % MOD_ADLER
										UpperCAmelCase			:   str      =				(b + a) % MOD_ADLER
					return (b << 16) | a


