



"""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/instruct-blip-flan-t5""": """https://huggingface.co/Salesforce/instruct-blip-flan-t5/resolve/main/config.json""",
}
class 				lowercase__       (   SCREAMING_SNAKE_CASE				):







     '''simple docstring'''


     UpperCamelCase						=					'''instructblip_vision_model'''



     def __init__(							self      :  int		,    _UpperCAmelCase      :  Dict=1408		,    _UpperCAmelCase      :  List[Any]=6144		,    _UpperCAmelCase      :  List[Any]=39		,    _UpperCAmelCase      :  str=16		,    _UpperCAmelCase      :  List[str]=224		,    _UpperCAmelCase      :  List[str]=14		,    _UpperCAmelCase      :  Tuple="gelu"		,    _UpperCAmelCase      :  Dict=1e-6		,    _UpperCAmelCase      :  Any=0.0		,    _UpperCAmelCase      :  Dict=1e-10		,    _UpperCAmelCase      :  Optional[Any]=True		,    **_UpperCAmelCase      :  int		,    )			->						Tuple:


           '''simple docstring'''




           super().__init__(**_UpperCAmelCase   )

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







     @classmethod
     def 					lowercase__    (							cls      :  Dict		,    _UpperCAmelCase      :  Union[str, os.PathLike]		,    **_UpperCAmelCase      :  Union[str, Any]   )			->						"PretrainedConfig":


           '''simple docstring'''




           cls._set_token_in_kwargs(_UpperCAmelCase   )

           UpperCAmelCase_			,   UpperCAmelCase_      			=							cls.get_config_dict(_UpperCAmelCase		,    **_UpperCAmelCase   )

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



class 				lowercase__       (   SCREAMING_SNAKE_CASE				):







     '''simple docstring'''


     UpperCamelCase						=					'''instructblip_qformer'''



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


           '''simple docstring'''




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

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







     @classmethod
     def 					lowercase__    (							cls      :  Union[str, Any]		,    _UpperCAmelCase      :  Union[str, os.PathLike]		,    **_UpperCAmelCase      :  Optional[Any]   )			->						"PretrainedConfig":


           '''simple docstring'''




           cls._set_token_in_kwargs(_UpperCAmelCase   )

           UpperCAmelCase_			,   UpperCAmelCase_      			=							cls.get_config_dict(_UpperCAmelCase		,    **_UpperCAmelCase   )

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



class 				lowercase__       (   SCREAMING_SNAKE_CASE				):







     '''simple docstring'''


     UpperCamelCase						=					'''instructblip'''
     UpperCamelCase						=					True



     def __init__(							self      :  Tuple		,    _UpperCAmelCase      :  Union[str, Any]=None		,    _UpperCAmelCase      :  Tuple=None		,    _UpperCAmelCase      :  str=None		,    _UpperCAmelCase      :  Dict=32		,    **_UpperCAmelCase      :  List[Any]   )			->						Union[str, Any]:


           '''simple docstring'''




           super().__init__(**_UpperCAmelCase   )

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

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

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

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

           UpperCAmelCase_      			=							self.text_config.tie_word_embeddings
           UpperCAmelCase_      			=							self.text_config.is_encoder_decoder

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



     @classmethod
     def 					lowercase__    (							cls      :  Union[str, Any]		,    _UpperCAmelCase      :  InstructBlipVisionConfig		,    _UpperCAmelCase      :  InstructBlipQFormerConfig		,    _UpperCAmelCase      :  PretrainedConfig		,    **_UpperCAmelCase      :  int		,    )			->						List[str]:


           '''simple docstring'''




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







     def 					lowercase__    (							self      :  Dict   )			->						Optional[Any]:


           '''simple docstring'''




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









"""simple docstring"""





from maths.prime_check import is_prime
def        a__     (				lowerCAmelCase__				):
      if not isinstance(lowerCAmelCase__     ,      lowerCAmelCase__				):
            UpperCAmelCase_      			=							f"""Input value of [number={number}] must be an integer"""
            raise TypeError(lowerCAmelCase__				)
      if is_prime(lowerCAmelCase__				) and is_prime(number + 2				):
            return number + 2
      else:
            return -1


if __name__ == "__main__":
  import doctest

  doctest.testmod()




