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__											=					logging.get_logger(__name__)

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





class      A							(				UpperCAmelCase_     ):
   __UpperCAmelCase : Union[str, Any]      =			'instructblip_vision_model'


   def __init__(self     :						Union[str, Any]       ,  __UpperCAmelCase     :						Optional[int]=1_4_0_8       ,  __UpperCAmelCase     :						List[Any]=6_1_4_4       ,  __UpperCAmelCase     :						Optional[int]=3_9       ,  __UpperCAmelCase     :						Optional[Any]=1_6       ,  __UpperCAmelCase     :						Optional[Any]=2_2_4       ,  __UpperCAmelCase     :						Optional[Any]=1_4       ,  __UpperCAmelCase     :						Dict="gelu"       ,  __UpperCAmelCase     :						Tuple=1E-6       ,  __UpperCAmelCase     :						str=0.0       ,  __UpperCAmelCase     :						Tuple=1E-10       ,  __UpperCAmelCase     :						int=True       ,  **__UpperCAmelCase     :						Union[str, Any]       ,  )						->				Dict:
         """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     :						Union[str, Any]       ,  __UpperCAmelCase     :						Union[str, os.PathLike]       ,  **__UpperCAmelCase     :						Tuple		)						->				"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      A							(				UpperCAmelCase_     ):
   __UpperCAmelCase : List[Any]      =			'instructblip_qformer'


   def __init__(self     :						str       ,  __UpperCAmelCase     :						Tuple=3_0_5_2_2       ,  __UpperCAmelCase     :						Dict=7_6_8       ,  __UpperCAmelCase     :						Any=1_2       ,  __UpperCAmelCase     :						List[Any]=1_2       ,  __UpperCAmelCase     :						Any=3_0_7_2       ,  __UpperCAmelCase     :						List[str]="gelu"       ,  __UpperCAmelCase     :						Union[str, Any]=0.1       ,  __UpperCAmelCase     :						Optional[int]=0.1       ,  __UpperCAmelCase     :						Optional[int]=5_1_2       ,  __UpperCAmelCase     :						List[str]=0.02       ,  __UpperCAmelCase     :						List[str]=1E-12       ,  __UpperCAmelCase     :						Union[str, Any]=0       ,  __UpperCAmelCase     :						Union[str, Any]="absolute"       ,  __UpperCAmelCase     :						List[Any]=2       ,  __UpperCAmelCase     :						Any=1_4_0_8       ,  **__UpperCAmelCase     :						List[Any]       ,  )						->				Dict:
         """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     :						Optional[Any]       ,  __UpperCAmelCase     :						Union[str, os.PathLike]       ,  **__UpperCAmelCase     :						Dict		)						->				"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      A							(				UpperCAmelCase_     ):
   __UpperCAmelCase : Dict      =			'instructblip'
   __UpperCAmelCase : Optional[int]      =			True


   def __init__(self     :						Tuple       ,  __UpperCAmelCase     :						Union[str, Any]=None       ,  __UpperCAmelCase     :						int=None       ,  __UpperCAmelCase     :						int=None       ,  __UpperCAmelCase     :						str=3_2       ,  **__UpperCAmelCase     :						Optional[Any]		)						->				Optional[int]:
         """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     :						List[Any]       ,  __UpperCAmelCase     :						InstructBlipVisionConfig       ,  __UpperCAmelCase     :						InstructBlipQFormerConfig       ,  __UpperCAmelCase     :						PretrainedConfig       ,  **__UpperCAmelCase     :						List[Any]       ,  )						->				Tuple:
         """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     :						Union[str, Any]		)						->				Union[str, 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"""





import requests
from bsa import BeautifulSoup



def 						_lowerCAmelCase				(				UpperCamelCase_ = "AAPL"				):
		__SCREAMING_SNAKE_CASE            = f"https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"
		__SCREAMING_SNAKE_CASE            = BeautifulSoup(requests.get(UpperCamelCase_				).text  ,				"""html.parser"""				)
		__SCREAMING_SNAKE_CASE            = """My(6px) Pos(r) smartphone_Mt(6px)"""
		return soup.find("""div"""  ,				class_=class_				).find("""span"""				).text


if __name__ == "__main__":
							for symbol in "AAPL AMZN IBM GOOG MSFT ORCL".split():
														print(F"""Current {symbol:<4} stock price is {stock_price(symbol):>8}""")




