




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


_UpperCAmelCase	:						List[Any]			=     logging.get_logger(__name__)

_UpperCAmelCase	:						Optional[Any]			=     {
    "Salesforce/instruct-blip-flan-t5": "https://huggingface.co/Salesforce/instruct-blip-flan-t5/resolve/main/config.json",
}




class    __lowerCAmelCase       (							lowerCAmelCase):
       _a 					=						'''instructblip_vision_model'''






       def __init__(   self:					Tuple       ,					_lowerCAmelCase:					Dict=14_08       ,					_lowerCAmelCase:					Optional[Any]=61_44       ,					_lowerCAmelCase:					Any=39       ,					_lowerCAmelCase:					Tuple=16       ,					_lowerCAmelCase:					Optional[Any]=2_24       ,					_lowerCAmelCase:					Any=14       ,					_lowerCAmelCase:					Any="gelu"       ,					_lowerCAmelCase:					List[Any]=1e-6       ,					_lowerCAmelCase:					Optional[Any]=0.0       ,					_lowerCAmelCase:					Any=1e-1_0       ,					_lowerCAmelCase:					int=True       ,					**_lowerCAmelCase:					Optional[Any]       ,					):
         super().__init__(**_lowerCAmelCase				)

         lowercase    :int      	=						hidden_size
         lowercase    :List[Any]      	=						intermediate_size
         lowercase    :Optional[Any]      	=						num_hidden_layers
         lowercase    :Optional[Any]      	=						num_attention_heads
         lowercase    :Dict      	=						patch_size
         lowercase    :Optional[Any]      	=						image_size
         lowercase    :Optional[int]      	=						initializer_range
         lowercase    :Optional[Any]      	=						attention_dropout
         lowercase    :Tuple      	=						layer_norm_eps
         lowercase    :Optional[int]      	=						hidden_act
         lowercase    :List[Any]      	=						qkv_bias






       @classmethod
       def 					SCREAMING_SNAKE_CASE    (   cls:					str       ,					_lowerCAmelCase:					Union[str, os.PathLike]       ,					**_lowerCAmelCase:					Any				):
         cls._set_token_in_kwargs(_lowerCAmelCase				)

         lowercase	,    lowercase    :str      	=						cls.get_config_dict(_lowerCAmelCase       ,					**_lowerCAmelCase				)

         # get the vision config dict if we are loading from InstructBlipConfig
         if config_dict.get("model_type"				) == "instructblip":
           lowercase    :str      	=						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    __lowerCAmelCase       (							lowerCAmelCase):
       _a 					=						'''instructblip_qformer'''






       def __init__(   self:					int       ,					_lowerCAmelCase:					Any=3_05_22       ,					_lowerCAmelCase:					Tuple=7_68       ,					_lowerCAmelCase:					List[Any]=12       ,					_lowerCAmelCase:					Optional[Any]=12       ,					_lowerCAmelCase:					List[str]=30_72       ,					_lowerCAmelCase:					Union[str, Any]="gelu"       ,					_lowerCAmelCase:					Any=0.1       ,					_lowerCAmelCase:					List[str]=0.1       ,					_lowerCAmelCase:					Any=5_12       ,					_lowerCAmelCase:					str=0.02       ,					_lowerCAmelCase:					Union[str, Any]=1e-1_2       ,					_lowerCAmelCase:					str=0       ,					_lowerCAmelCase:					Dict="absolute"       ,					_lowerCAmelCase:					Optional[Any]=2       ,					_lowerCAmelCase:					Union[str, Any]=14_08       ,					**_lowerCAmelCase:					Optional[Any]       ,					):
         super().__init__(pad_token_id=_lowerCAmelCase       ,					**_lowerCAmelCase				)

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






       @classmethod
       def 					SCREAMING_SNAKE_CASE    (   cls:					Tuple       ,					_lowerCAmelCase:					Union[str, os.PathLike]       ,					**_lowerCAmelCase:					Optional[int]				):
         cls._set_token_in_kwargs(_lowerCAmelCase				)

         lowercase	,    lowercase    :str      	=						cls.get_config_dict(_lowerCAmelCase       ,					**_lowerCAmelCase				)

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







class    __lowerCAmelCase       (							lowerCAmelCase):
       _a 					=						'''instructblip'''
       _a 					=						True






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

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

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

         if text_config is None:
           lowercase    :List[str]      	=						{}
           logger.info("text_config is None. Initializing the text config with default values (`OPTConfig`)."				)

         lowercase    :Dict      	=						InstructBlipVisionConfig(**_lowerCAmelCase				)
         lowercase    :Tuple      	=						InstructBlipQFormerConfig(**_lowerCAmelCase				)
         lowercase    :int      	=						text_config["model_type"] if "model_type" in text_config else "opt"
         lowercase    :str      	=						CONFIG_MAPPING[text_model_type](**_lowerCAmelCase				)

         lowercase    :Any      	=						self.text_config.tie_word_embeddings
         lowercase    :Any      	=						self.text_config.is_encoder_decoder

         lowercase    :Dict      	=						num_query_tokens
         lowercase    :List[str]      	=						self.vision_config.hidden_size
         lowercase    :Any      	=						self.text_config.model_type in MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
         lowercase    :List[str]      	=						1.0
         lowercase    :int      	=						0.02






       @classmethod
       def 					SCREAMING_SNAKE_CASE    (   cls:					int       ,					_lowerCAmelCase:					InstructBlipVisionConfig       ,					_lowerCAmelCase:					InstructBlipQFormerConfig       ,					_lowerCAmelCase:					PretrainedConfig       ,					**_lowerCAmelCase:					int       ,					):
         return cls(
             vision_config=vision_config.to_dict()       ,					qformer_config=qformer_config.to_dict()       ,					text_config=text_config.to_dict()       ,					**_lowerCAmelCase       ,					)






       def 					SCREAMING_SNAKE_CASE    (   self:					Optional[Any]				):
         lowercase    :List[str]      	=						copy.deepcopy(self.__dict__				)
         lowercase    :Any      	=						self.vision_config.to_dict()
         lowercase    :str      	=						self.qformer_config.to_dict()
         lowercase    :Dict      	=						self.text_config.to_dict()
         lowercase    :Tuple      	=						self.__class__.model_type
         return output









def       UpperCAmelCase__  (     lowerCamelCase   ):
  return 10 - x * x



def       UpperCAmelCase__  (     lowerCamelCase,			lowerCamelCase   ):
  # Bolzano theory in order to find if there is a root between a and b
  if equation(lowerCamelCase   ) * equation(lowerCamelCase   ) >= 0:
    raise ValueError("Wrong space!"   )

  lowercase    :Optional[int]      	=						a
  while (b - a) >= 0.01:
    # Find middle point
    lowercase    :Optional[Any]      	=						(a + b) / 2
    # Check if middle point is root
    if equation(lowerCamelCase   ) == 0.0:
      break
    # Decide the side to repeat the steps
    if equation(lowerCamelCase   ) * equation(lowerCamelCase   ) < 0:
      lowercase    :Any      	=						c
    else:
      lowercase    :List[Any]      	=						c
  return c


if __name__ == "__main__":
     import doctest

     doctest.testmod()

     print(bisection(-2, 5))
     print(bisection(0, 6))



