






"""simple docstring"""






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


UpperCAmelCase_     :				Tuple         =				logging.get_logger(__name__)

UpperCAmelCase_     :				Optional[Any]         =				{
    """vinvino02/glpn-kitti""": """https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json""",
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}




class 							lowerCAmelCase__       (    UpperCAmelCase__				):






      '''simple docstring'''

      __UpperCamelCase							=						"glpn"
      def __init__(		self  :						Any		,			lowercase_  :						Dict=3		,			lowercase_  :						List[str]=4		,			lowercase_  :						Any=[2, 2, 2, 2]		,			lowercase_  :						List[Any]=[8, 4, 2, 1]		,			lowercase_  :						str=[32, 64, 160, 256]		,			lowercase_  :						List[str]=[7, 3, 3, 3]		,			lowercase_  :						str=[4, 2, 2, 2]		,			lowercase_  :						List[str]=[1, 2, 5, 8]		,			lowercase_  :						Optional[int]=[4, 4, 4, 4]		,			lowercase_  :						Optional[Any]="gelu"		,			lowercase_  :						Any=0.0		,			lowercase_  :						List[Any]=0.0		,			lowercase_  :						int=0.02		,			lowercase_  :						str=0.1		,			lowercase_  :						Any=1e-6		,			lowercase_  :						List[str]=64		,			lowercase_  :						str=10		,			lowercase_  :						List[Any]=-1		,			**lowercase_  :						Optional[int]		,			):




          '''simple docstring'''


          super().__init__(**lowercase_)

          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	num_channels
          SCREAMING_SNAKE_CASE_   :						Any							=	num_encoder_blocks
          SCREAMING_SNAKE_CASE_   :						Any							=	depths
          SCREAMING_SNAKE_CASE_   :						str							=	sr_ratios
          SCREAMING_SNAKE_CASE_   :						Tuple							=	hidden_sizes
          SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	patch_sizes
          SCREAMING_SNAKE_CASE_   :						Optional[int]							=	strides
          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	mlp_ratios
          SCREAMING_SNAKE_CASE_   :						Dict							=	num_attention_heads
          SCREAMING_SNAKE_CASE_   :						List[str]							=	hidden_act
          SCREAMING_SNAKE_CASE_   :						Dict							=	hidden_dropout_prob
          SCREAMING_SNAKE_CASE_   :						int							=	attention_probs_dropout_prob
          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	initializer_range
          SCREAMING_SNAKE_CASE_   :						List[str]							=	drop_path_rate
          SCREAMING_SNAKE_CASE_   :						Union[str, Any]							=	layer_norm_eps
          SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	decoder_hidden_size
          SCREAMING_SNAKE_CASE_   :						Dict							=	max_depth
          SCREAMING_SNAKE_CASE_   :						Optional[Any]							=	head_in_index










"""simple docstring"""






from __future__ import annotations

import requests



def       _A    (__a							)				-> dict:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_   :						Any							=	f'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
    return requests.get(__a							).json()



def       _A    (__a = 10							)				-> list[dict]:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_   :						Any							=	'''https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty'''
    SCREAMING_SNAKE_CASE_   :						Dict							=	requests.get(__a							).json()[:max_stories]
    return [get_hackernews_story(__a							) for story_id in story_ids]



def       _A    (__a = 10							)				-> str:
    """simple docstring"""






    SCREAMING_SNAKE_CASE_   :						Tuple							=	hackernews_top_stories(__a							)
    return "\n".join('''* [{title}]({url})'''.format(**__a							) for story in stories							)


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


