


'''simple docstring'''



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


__UpperCAmelCase      :Any			    =       logging.get_logger(__name__)

__UpperCAmelCase      :Tuple			    =       {
    "edbeeching/decision-transformer-gym-hopper-medium": (
        "https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json"
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}



class      a    (		_a	):


     """simple docstring"""






     SCREAMING_SNAKE_CASE	:			Optional[Any]							       =       "decision_transformer"
     SCREAMING_SNAKE_CASE	:			Union[str, Any]							       =       ["past_key_values"]
     SCREAMING_SNAKE_CASE	:			Optional[Any]							       =       {
         "max_position_embeddings": "n_positions",
         "num_attention_heads": "n_head",
         "num_hidden_layers": "n_layer",
     }

     def __init__(    self					:		Any							,			snake_case					:		List[Any]=17							,			snake_case					:		List[str]=4							,			snake_case					:		Tuple=128							,			snake_case					:		List[Any]=4096							,			snake_case					:		Union[str, Any]=True							,			snake_case					:		Dict=1							,			snake_case					:		Dict=1024							,			snake_case					:		Optional[Any]=3							,			snake_case					:		Any=1							,			snake_case					:		Tuple=None							,			snake_case					:		List[str]="relu"							,			snake_case					:		Optional[Any]=0.1							,			snake_case					:		str=0.1							,			snake_case					:		str=0.1							,			snake_case					:		Optional[Any]=1E-5							,			snake_case					:		Dict=0.02							,			snake_case					:		Dict=True							,			snake_case					:		Union[str, Any]=True							,			snake_case					:		Optional[int]=5_0256							,			snake_case					:		Tuple=5_0256							,			snake_case					:		Any=False							,			snake_case					:		Union[str, Any]=False							,			**snake_case					:		str							,			)						->							Optional[int]:
          __UpperCAmelCase     :			Optional[int]  							=      state_dim
          __UpperCAmelCase     :			Tuple  							=      act_dim
          __UpperCAmelCase     :			Union[str, Any]  							=      hidden_size
          __UpperCAmelCase     :			Dict  							=      max_ep_len
          __UpperCAmelCase     :			List[Any]  							=      action_tanh
          __UpperCAmelCase     :			List[str]  							=      vocab_size
          __UpperCAmelCase     :			Tuple  							=      n_positions
          __UpperCAmelCase     :			int  							=      n_layer
          __UpperCAmelCase     :			Any  							=      n_head
          __UpperCAmelCase     :			Optional[Any]  							=      n_inner
          __UpperCAmelCase     :			str  							=      activation_function
          __UpperCAmelCase     :			int  							=      resid_pdrop
          __UpperCAmelCase     :			int  							=      embd_pdrop
          __UpperCAmelCase     :			Optional[int]  							=      attn_pdrop
          __UpperCAmelCase     :			str  							=      layer_norm_epsilon
          __UpperCAmelCase     :			Any  							=      initializer_range
          __UpperCAmelCase     :			List[Any]  							=      scale_attn_weights
          __UpperCAmelCase     :			int  							=      use_cache
          __UpperCAmelCase     :			Tuple  							=      scale_attn_by_inverse_layer_idx
          __UpperCAmelCase     :			Dict  							=      reorder_and_upcast_attn

          __UpperCAmelCase     :			List[Any]  							=      bos_token_id
          __UpperCAmelCase     :			Dict  							=      eos_token_id

          super().__init__(bos_token_id=snake_case							,			eos_token_id=snake_case							,			**snake_case      )



'''simple docstring'''



import requests

__UpperCAmelCase      :Union[str, Any]			    =       "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="




def      _a     (						_lowercase :     str  ):





     '''simple docstring'''






     __UpperCAmelCase     :			Union[str, Any]  							=      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>")