




from collections import OrderedDict
from typing import Mapping

from packaging import version

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


UpperCAmelCase_									=	logging.get_logger(__name__)

UpperCAmelCase_									=	{
    'microsoft/beit-base-patch16-224-pt22k': (
        'https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json'
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}





class     lowerCamelCase__(					A_):
      UpperCAmelCase__      :	Union[str, Any]    		=   "beit"
      def __init__(				self: Tuple    ,       UpperCamelCase_: Dict=81_92    ,       UpperCamelCase_: Optional[Any]=7_68    ,       UpperCamelCase_: Dict=12    ,       UpperCamelCase_: Union[str, Any]=12    ,       UpperCamelCase_: List[str]=30_72    ,       UpperCamelCase_: str="gelu"    ,       UpperCamelCase_: Union[str, Any]=0.0    ,       UpperCamelCase_: Dict=0.0    ,       UpperCamelCase_: Union[str, Any]=0.02    ,       UpperCamelCase_: Optional[Any]=1E-12    ,       UpperCamelCase_: List[Any]=2_24    ,       UpperCamelCase_: Any=16    ,       UpperCamelCase_: Tuple=3    ,       UpperCamelCase_: Optional[int]=False    ,       UpperCamelCase_: Optional[Any]=False    ,       UpperCamelCase_: Any=False    ,       UpperCamelCase_: int=False    ,       UpperCamelCase_: Optional[Any]=0.1    ,       UpperCamelCase_: Tuple=0.1    ,       UpperCamelCase_: List[Any]=True    ,       UpperCamelCase_: Tuple=[3, 5, 7, 11]    ,       UpperCamelCase_: Optional[Any]=[1, 2, 3, 6]    ,       UpperCamelCase_: int=True    ,       UpperCamelCase_: str=0.4    ,       UpperCamelCase_: str=2_56    ,       UpperCamelCase_: List[str]=1    ,       UpperCamelCase_: Optional[int]=False    ,       UpperCamelCase_: Dict=2_55    ,       **UpperCamelCase_: Any    ,       ):
             super().__init__(**A_   )

             __lowerCamelCase   =						vocab_size
             __lowerCamelCase   =						hidden_size
             __lowerCamelCase   =						num_hidden_layers
             __lowerCamelCase   =						num_attention_heads
             __lowerCamelCase   =						intermediate_size
             __lowerCamelCase   =						hidden_act
             __lowerCamelCase   =						hidden_dropout_prob
             __lowerCamelCase   =						attention_probs_dropout_prob
             __lowerCamelCase   =						initializer_range
             __lowerCamelCase   =						layer_norm_eps

             __lowerCamelCase   =						image_size
             __lowerCamelCase   =						patch_size
             __lowerCamelCase   =						num_channels
             __lowerCamelCase   =						use_mask_token
             __lowerCamelCase   =						use_absolute_position_embeddings
             __lowerCamelCase   =						use_relative_position_bias
             __lowerCamelCase   =						use_shared_relative_position_bias
             __lowerCamelCase   =						layer_scale_init_value
             __lowerCamelCase   =						drop_path_rate
             __lowerCamelCase   =						use_mean_pooling
             # decode head attributes (semantic segmentation)
             __lowerCamelCase   =						out_indices
             __lowerCamelCase   =						pool_scales
             # auxiliary head attributes (semantic segmentation)
             __lowerCamelCase   =						use_auxiliary_head
             __lowerCamelCase   =						auxiliary_loss_weight
             __lowerCamelCase   =						auxiliary_channels
             __lowerCamelCase   =						auxiliary_num_convs
             __lowerCamelCase   =						auxiliary_concat_input
             __lowerCamelCase   =						semantic_loss_ignore_index





class     lowerCamelCase__(					A_):
      UpperCAmelCase__      :	Tuple    		=   version.parse('1.11')
      @property
      def 			lowerCAmelCase__						(				self: List[str]   ):
             return OrderedDict(
                 [
                     ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
                 ]   )




      @property
      def 			lowerCAmelCase__						(				self: Optional[Any]   ):
             return 1E-4





from __future__ import annotations

import csv

import requests
from bsa import BeautifulSoup

def 						_UpperCAmelCase				(			SCREAMING_SNAKE_CASE__			:					str = ""				):
     __UpperCamelCase    							=url or 'https://www.imdb.com/chart/top/?ref_=nv_mv_250'
     __UpperCamelCase    							=BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE__				).text			,     'html.parser'				)
     __UpperCamelCase    							=soup.find_all('td'			,     attrs='titleColumn'				)
     __UpperCamelCase    							=soup.find_all('td'			,     class_='ratingColumn imdbRating'				)
     return {
         title.a.text: float(rating.strong.text				)
         for title, rating in zip(SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__				)
     }

def 						_UpperCAmelCase				(			SCREAMING_SNAKE_CASE__			:					str = "IMDb_Top_250_Movies.csv"				):
     __UpperCamelCase    							=get_imdb_top_aaa_movies()
     with open(SCREAMING_SNAKE_CASE__			,     'w'			,     newline=''				) as out_file:
          __UpperCamelCase    							=csv.writer(SCREAMING_SNAKE_CASE__				)
          writer.writerow(['Movie title', 'IMDb rating']				)
          for title, rating in movies.items():
               writer.writerow([title, rating]				)


if __name__ == "__main__":
   write_movies()





