


from collections import OrderedDict
from typing import Mapping

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


A      :    Optional[int]		=					logging.get_logger(__name__)

A      :    Union[str, Any]		=					{
    "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/config.json",
    "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/config.json",
    "xlm-roberta-large-finetuned-conll02-dutch": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll02-spanish": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll03-english": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll03-german": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json"
    ),
}







class 			_lowercase (							__a):


       """simple docstring"""




       A__											=			"xlm-roberta"





       def __init__(   self							:			Dict					,      __lowerCamelCase							:			Tuple=30522					,      __lowerCamelCase							:			Any=768					,      __lowerCamelCase							:			Union[str, Any]=12					,      __lowerCamelCase							:			Union[str, Any]=12					,      __lowerCamelCase							:			Optional[Any]=3072					,      __lowerCamelCase							:			Optional[Any]="gelu"					,      __lowerCamelCase							:			Tuple=0.1					,      __lowerCamelCase							:			str=0.1					,      __lowerCamelCase							:			Tuple=512					,      __lowerCamelCase							:			Dict=2					,      __lowerCamelCase							:			Dict=0.0_2					,      __lowerCamelCase							:			List[str]=1E-1_2					,      __lowerCamelCase							:			Tuple=1					,      __lowerCamelCase							:			Optional[Any]=0					,      __lowerCamelCase							:			str=2					,      __lowerCamelCase							:			List[Any]="absolute"					,      __lowerCamelCase							:			str=True					,      __lowerCamelCase							:			Optional[int]=None					,      **__lowerCamelCase							:			Dict					,      ):


             '''simple docstring'''



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

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







class 			_lowercase (							__a):


       """simple docstring"""




       @property
       def 						lowerCAmelCase     (   self							:			str       ):


             '''simple docstring'''



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




from __future__ import annotations

import csv

import requests
from bsa import BeautifulSoup






def    lowerCamelCase__				(				__lowerCAmelCase  :  str = ""				):




			"""simple docstring"""


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






def    lowerCamelCase__				(				__lowerCAmelCase  :  str = "IMDb_Top_250_Movies.csv"				):




			"""simple docstring"""


			lowerCAmelCase_						=	get_imdb_top_aaa_movies()
			with open(__lowerCAmelCase    ,							"w"    ,							newline=""				) as out_file:
						lowerCAmelCase_						=	csv.writer(__lowerCAmelCase				)
						writer.writerow(["Movie title", "IMDb rating"]				)
						for title, rating in movies.items():
									writer.writerow([title, rating]				)


if __name__ == "__main__":
			write_movies()



