





'''simple docstring'''




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowercase__    :      Tuple						=    logging.get_logger(__name__)

lowercase__    :      int						=    {
    '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/config.json''',
    '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/config.json''',
    '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/config.json''',
    '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/config.json''',
    '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json''',
    '''roberta-large-openai-detector''': '''https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json''',
}


class  SCREAMING_SNAKE_CASE    (UpperCAmelCase__							):
     lowerCAmelCase					=       "roberta"


     def __init__(						self						,	_UpperCAmelCase=5_0265						,	_UpperCAmelCase=768						,	_UpperCAmelCase=12						,	_UpperCAmelCase=12						,	_UpperCAmelCase=3072						,	_UpperCAmelCase="gelu"						,	_UpperCAmelCase=0.1						,	_UpperCAmelCase=0.1						,	_UpperCAmelCase=512						,	_UpperCAmelCase=2						,	_UpperCAmelCase=0.02						,	_UpperCAmelCase=1e-1_2						,	_UpperCAmelCase=1						,	_UpperCAmelCase=0						,	_UpperCAmelCase=2						,	_UpperCAmelCase="absolute"						,	_UpperCAmelCase=True						,	_UpperCAmelCase=None						,	**_UpperCAmelCase						,	):

          '''simple docstring'''






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

          __A						: List[str]      =       vocab_size
          __A						: List[Any]      =       hidden_size
          __A						: int      =       num_hidden_layers
          __A						: Optional[int]      =       num_attention_heads
          __A						: Optional[Any]      =       hidden_act
          __A						: Union[str, Any]      =       intermediate_size
          __A						: Optional[Any]      =       hidden_dropout_prob
          __A						: str      =       attention_probs_dropout_prob
          __A						: List[Any]      =       max_position_embeddings
          __A						: List[str]      =       type_vocab_size
          __A						: Optional[Any]      =       initializer_range
          __A						: List[Any]      =       layer_norm_eps
          __A						: Tuple      =       position_embedding_type
          __A						: str      =       use_cache
          __A						: Any      =       classifier_dropout




class  SCREAMING_SNAKE_CASE    (UpperCAmelCase__							):


     @property
     def 							SCREAMING_SNAKE_CASE  (						self):

          '''simple docstring'''






          if self.task == "multiple-choice":
               __A						: str      =       {0: """batch""", 1: """choice""", 2: """sequence"""}
          else:
               __A						: Optional[int]      =       {0: """batch""", 1: """sequence"""}
          return OrderedDict(
              [
                  ('input_ids', dynamic_axis),
                  ('attention_mask', dynamic_axis),
              ])



'''simple docstring'''







from __future__ import annotations

import requests


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	str  )  ->			dict:
       _a    : Any     					=F"https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"
       return requests.get(_UpperCAmelCase  ).json()


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	int = 10  )  ->			list[dict]:
       _a    : Union[str, Any]     					="""https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty"""
       _a    : int     					=requests.get(_UpperCAmelCase  ).json()[:max_stories]
       return [get_hackernews_story(_UpperCAmelCase  ) for story_id in story_ids]


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	int = 10  )  ->			str:
       _a    : Union[str, Any]     					=hackernews_top_stories(_UpperCAmelCase  )
       return "\n".join("""* [{title}]({url})""".format(**_UpperCAmelCase  ) for story in stories  )


if __name__ == "__main__":
   print(hackernews_top_stories_as_markdown())


