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    :				int							     =	logging.get_logger(__name__)

__lowerCamelCase    :				str							     =	{
    '''Salesforce/instruct-blip-flan-t5''': '''https://huggingface.co/Salesforce/instruct-blip-flan-t5/resolve/main/config.json''',
}







class __snake_case       (		lowerCamelCase_	):
   lowerCAmelCase_														=							"instructblip_vision_model"




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



     """simple docstring"""






     super().__init__(**_lowercase   )

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




   @classmethod
   def 			__a		(					cls    :       Optional[Any] ,			_lowercase    :       Union[str, os.PathLike] ,			**_lowercase    :       Dict   ):



     """simple docstring"""






     cls._set_token_in_kwargs(_lowercase   )

     SCREAMING_SNAKE_CASE__							,  SCREAMING_SNAKE_CASE__    							=   cls.get_config_dict(_lowercase ,			**_lowercase   )

     # get the vision config dict if we are loading from InstructBlipConfig
     if config_dict.get("""model_type"""   ) == "instructblip":
       SCREAMING_SNAKE_CASE__    							=   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(_lowercase ,			**_lowercase   )







class __snake_case       (		lowerCamelCase_	):
   lowerCAmelCase_														=							"instructblip_qformer"




   def __init__(					self    :       Union[str, Any] ,			_lowercase    :       int=3_05_22 ,			_lowercase    :       List[Any]=7_68 ,			_lowercase    :       List[Any]=12 ,			_lowercase    :       Tuple=12 ,			_lowercase    :       Tuple=30_72 ,			_lowercase    :       Union[str, Any]="gelu" ,			_lowercase    :       Dict=0.1 ,			_lowercase    :       Dict=0.1 ,			_lowercase    :       Union[str, Any]=5_12 ,			_lowercase    :       Optional[int]=0.02 ,			_lowercase    :       Dict=1E-12 ,			_lowercase    :       Optional[int]=0 ,			_lowercase    :       Optional[Any]="absolute" ,			_lowercase    :       Optional[Any]=2 ,			_lowercase    :       Dict=14_08 ,			**_lowercase    :       List[Any] ,			):



     """simple docstring"""






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

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




   @classmethod
   def 			__a		(					cls    :       Dict ,			_lowercase    :       Union[str, os.PathLike] ,			**_lowercase    :       List[Any]   ):



     """simple docstring"""






     cls._set_token_in_kwargs(_lowercase   )

     SCREAMING_SNAKE_CASE__							,  SCREAMING_SNAKE_CASE__    							=   cls.get_config_dict(_lowercase ,			**_lowercase   )

     # get the qformer config dict if we are loading from InstructBlipConfig
     if config_dict.get("""model_type"""   ) == "instructblip":
       SCREAMING_SNAKE_CASE__    							=   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(_lowercase ,			**_lowercase   )







class __snake_case       (		lowerCamelCase_	):
   lowerCAmelCase_														=							"instructblip"
   lowerCAmelCase_														=							True




   def __init__(					self    :       Union[str, Any] ,			_lowercase    :       Tuple=None ,			_lowercase    :       Tuple=None ,			_lowercase    :       int=None ,			_lowercase    :       Tuple=32 ,			**_lowercase    :       Optional[Any]   ):



     """simple docstring"""






     super().__init__(**_lowercase   )

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

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

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

     SCREAMING_SNAKE_CASE__    							=   InstructBlipVisionConfig(**_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   InstructBlipQFormerConfig(**_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   text_config["""model_type"""] if """model_type""" in text_config else """opt"""
     SCREAMING_SNAKE_CASE__    							=   CONFIG_MAPPING[text_model_type](**_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   self.text_config.tie_word_embeddings
     SCREAMING_SNAKE_CASE__    							=   self.text_config.is_encoder_decoder

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




   @classmethod
   def 			__a		(					cls    :       Optional[int] ,			_lowercase    :       InstructBlipVisionConfig ,			_lowercase    :       InstructBlipQFormerConfig ,			_lowercase    :       PretrainedConfig ,			**_lowercase    :       str ,			):



     """simple docstring"""






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




   def 			__a		(					self    :       Any   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   copy.deepcopy(self.__dict__   )
     SCREAMING_SNAKE_CASE__    							=   self.vision_config.to_dict()
     SCREAMING_SNAKE_CASE__    							=   self.qformer_config.to_dict()
     SCREAMING_SNAKE_CASE__    							=   self.text_config.to_dict()
     SCREAMING_SNAKE_CASE__    							=   self.__class__.model_type
     return output

from __future__ import annotations



def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: list			)							->      float:







  """simple docstring"""





  if not nums:
    raise ValueError("""List is empty"""			)
  return sum(__UpperCamelCase			) / len(__UpperCamelCase			)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
