'''simple docstring'''


import copy
import os
from typing import TYPE_CHECKING, List, Union


if TYPE_CHECKING:
       pass

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case						  =		logging.get_logger(__name__)

__snake_case						  =		{
    """kakaobrain/align-base""": """https://huggingface.co/kakaobrain/align-base/resolve/main/config.json""",
}





class       _a    (		__a      ):


  """simple docstring"""

  A_    							=						'''align_text_model'''




  def __init__(		self      :       Optional[Any]   ,				lowercase_      :       List[Any]=30_522   ,				lowercase_      :       List[Any]=768   ,				lowercase_      :       Optional[int]=12   ,				lowercase_      :       List[str]=12   ,				lowercase_      :       Optional[int]=3_072   ,				lowercase_      :       str="gelu"   ,				lowercase_      :       Dict=0.1   ,				lowercase_      :       List[str]=0.1   ,				lowercase_      :       List[Any]=512   ,				lowercase_      :       Optional[int]=2   ,				lowercase_      :       List[str]=0.0_2   ,				lowercase_      :       Optional[int]=1e-12   ,				lowercase_      :       str=0   ,				lowercase_      :       Tuple="absolute"   ,				lowercase_      :       List[Any]=True   ,				**lowercase_      :       str   ,				):







    '''simple docstring'''


    super().__init__(**lowercase_      )

    lowercase_     =       vocab_size
    lowercase_     =       hidden_size
    lowercase_     =       num_hidden_layers
    lowercase_     =       num_attention_heads
    lowercase_     =       hidden_act
    lowercase_     =       intermediate_size
    lowercase_     =       hidden_dropout_prob
    lowercase_     =       attention_probs_dropout_prob
    lowercase_     =       max_position_embeddings
    lowercase_     =       type_vocab_size
    lowercase_     =       initializer_range
    lowercase_     =       layer_norm_eps
    lowercase_     =       position_embedding_type
    lowercase_     =       use_cache
    lowercase_     =       pad_token_id





  @classmethod
  def 		lowerCamelCase__  (		cls      :       Dict   ,				lowercase_      :       Union[str, os.PathLike]   ,				**lowercase_      :       Optional[int]      ):







    '''simple docstring'''


    cls._set_token_in_kwargs(lowercase_      )

    lowercase_     ,	lowercase_     =       cls.get_config_dict(lowercase_   ,				**lowercase_      )

    # get the text config dict if we are loading from AlignConfig
    if config_dict.get("""model_type"""      ) == "align":
      lowercase_     =       config_dict["""text_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       _a    (		__a      ):


  """simple docstring"""

  A_    							=						'''align_vision_model'''




  def __init__(		self      :       Union[str, Any]   ,				lowercase_      :       int = 3   ,				lowercase_      :       int = 600   ,				lowercase_      :       float = 2.0   ,				lowercase_      :       float = 3.1   ,				lowercase_      :       int = 8   ,				lowercase_      :       List[int] = [3, 3, 5, 3, 5, 5, 3]   ,				lowercase_      :       List[int] = [32, 16, 24, 40, 80, 112, 192]   ,				lowercase_      :       List[int] = [16, 24, 40, 80, 112, 192, 320]   ,				lowercase_      :       List[int] = []   ,				lowercase_      :       List[int] = [1, 2, 2, 2, 1, 2, 1]   ,				lowercase_      :       List[int] = [1, 2, 2, 3, 3, 4, 1]   ,				lowercase_      :       List[int] = [1, 6, 6, 6, 6, 6, 6]   ,				lowercase_      :       float = 0.2_5   ,				lowercase_      :       str = "swish"   ,				lowercase_      :       int = 2_560   ,				lowercase_      :       str = "mean"   ,				lowercase_      :       float = 0.0_2   ,				lowercase_      :       float = 0.0_0_1   ,				lowercase_      :       float = 0.9_9   ,				lowercase_      :       float = 0.2   ,				**lowercase_      :       List[str]   ,				):







    '''simple docstring'''


    super().__init__(**lowercase_      )

    lowercase_     =       num_channels
    lowercase_     =       image_size
    lowercase_     =       width_coefficient
    lowercase_     =       depth_coefficient
    lowercase_     =       depth_divisor
    lowercase_     =       kernel_sizes
    lowercase_     =       in_channels
    lowercase_     =       out_channels
    lowercase_     =       depthwise_padding
    lowercase_     =       strides
    lowercase_     =       num_block_repeats
    lowercase_     =       expand_ratios
    lowercase_     =       squeeze_expansion_ratio
    lowercase_     =       hidden_act
    lowercase_     =       hidden_dim
    lowercase_     =       pooling_type
    lowercase_     =       initializer_range
    lowercase_     =       batch_norm_eps
    lowercase_     =       batch_norm_momentum
    lowercase_     =       drop_connect_rate
    lowercase_     =       sum(lowercase_      ) * 4





  @classmethod
  def 		lowerCamelCase__  (		cls      :       Tuple   ,				lowercase_      :       Union[str, os.PathLike]   ,				**lowercase_      :       Any      ):







    '''simple docstring'''


    cls._set_token_in_kwargs(lowercase_      )

    lowercase_     ,	lowercase_     =       cls.get_config_dict(lowercase_   ,				**lowercase_      )

    # get the vision config dict if we are loading from AlignConfig
    if config_dict.get("""model_type"""      ) == "align":
      lowercase_     =       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       _a    (		__a      ):


  """simple docstring"""

  A_    							=						'''align'''
  A_    							=						True




  def __init__(		self      :       int   ,				lowercase_      :       Union[str, Any]=None   ,				lowercase_      :       Optional[Any]=None   ,				lowercase_      :       Union[str, Any]=640   ,				lowercase_      :       Union[str, Any]=1.0   ,				lowercase_      :       List[str]=0.0_2   ,				**lowercase_      :       Dict   ,				):







    '''simple docstring'''


    super().__init__(**lowercase_      )

    if text_config is None:
      lowercase_     =       {}
      logger.info("""text_config is None. Initializing the AlignTextConfig with default values."""      )

    if vision_config is None:
      lowercase_     =       {}
      logger.info("""vision_config is None. Initializing the AlignVisionConfig with default values."""      )

    lowercase_     =       AlignTextConfig(**lowercase_      )
    lowercase_     =       AlignVisionConfig(**lowercase_      )

    lowercase_     =       projection_dim
    lowercase_     =       temperature_init_value
    lowercase_     =       initializer_range




  @classmethod
  def 		lowerCamelCase__  (		cls      :       Any   ,				lowercase_      :       AlignTextConfig   ,				lowercase_      :       AlignVisionConfig   ,				**lowercase_      :       Optional[Any]      ):







    '''simple docstring'''


    return cls(text_config=text_config.to_dict()   ,				vision_config=vision_config.to_dict()   ,				**lowercase_      )





  def 		lowerCamelCase__  (		self      :       str      ):







    '''simple docstring'''


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


'''simple docstring'''


import requests

__snake_case						  =		"""https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="""

def   A_      (       SCREAMING_SNAKE_CASE_						)			->None:
  # fetching a list of articles in json format
  lowercase_     =       requests.get(_NEWS_API + bbc_news_api_key						).json()
  # each article in the list is a dict
  for i, article in enumerate(bbc_news_page["""articles"""] ,	1						):
    print(f"""{i}.) {article["title"]}"""						)


if __name__ == "__main__":
       fetch_bbc_news(bbc_news_api_key="""<Your BBC News API key goes here>""")

