
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenization_utils import JiebaPreTokenizer


SCREAMING_SNAKE_CASE :		Union[str, Any]       			=							logging.get_logger(__name__)

SCREAMING_SNAKE_CASE :		Tuple       			=							{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

SCREAMING_SNAKE_CASE :		Any       			=							{
    "vocab_file": {
        "junnyu/roformer_chinese_small": "https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/vocab.txt",
        "junnyu/roformer_chinese_base": "https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/vocab.txt",
        "junnyu/roformer_chinese_char_small": (
            "https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/vocab.txt"
        ),
        "junnyu/roformer_chinese_char_base": (
            "https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/vocab.txt"
        ),
        "junnyu/roformer_small_discriminator": (
            "https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/vocab.txt"
        ),
        "junnyu/roformer_small_generator": (
            "https://huggingface.co/junnyu/roformer_small_generator/resolve/main/vocab.txt"
        ),
    }
}

SCREAMING_SNAKE_CASE :		List[str]       			=							{
    "junnyu/roformer_chinese_small": 1536,
    "junnyu/roformer_chinese_base": 1536,
    "junnyu/roformer_chinese_char_small": 512,
    "junnyu/roformer_chinese_char_base": 512,
    "junnyu/roformer_small_discriminator": 128,
    "junnyu/roformer_small_generator": 128,
}


SCREAMING_SNAKE_CASE :		List[str]       			=							{
    "junnyu/roformer_chinese_small": {"do_lower_case": True},
    "junnyu/roformer_chinese_base": {"do_lower_case": True},
    "junnyu/roformer_chinese_char_small": {"do_lower_case": True},
    "junnyu/roformer_chinese_char_base": {"do_lower_case": True},
    "junnyu/roformer_small_discriminator": {"do_lower_case": True},
    "junnyu/roformer_small_generator": {"do_lower_case": True},
}






class        __lowercase		(       a_							):
					__magic_name__    :				int  						=						VOCAB_FILES_NAMES
					__magic_name__    :				Union[str, Any]  						=						PRETRAINED_VOCAB_FILES_MAP
					__magic_name__    :				str  						=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					__magic_name__    :				List[str]  						=						PRETRAINED_INIT_CONFIGURATION
					__magic_name__    :				Tuple  						=						RoFormerTokenizer


					def __init__(						self							,							a__=None							,							a__=None							,							a__=True							,							a__="[UNK]"							,							a__="[SEP]"							,							a__="[PAD]"							,							a__="[CLS]"							,							a__="[MASK]"							,							a__=True							,							a__=None							,							**a__							,							)		->				Any:





									'''simple docstring'''
									super().__init__(
									    lowerCAmelCase_							,							tokenizer_file=lowerCAmelCase_							,							do_lower_case=lowerCAmelCase_							,							unk_token=lowerCAmelCase_							,							sep_token=lowerCAmelCase_							,							pad_token=lowerCAmelCase_							,							cls_token=lowerCAmelCase_							,							mask_token=lowerCAmelCase_							,							tokenize_chinese_chars=lowerCAmelCase_							,							strip_accents=lowerCAmelCase_							,							**lowerCAmelCase_							,							)

									A_													=	json.loads(self.backend_tokenizer.normalizer.__getstate__()    )
									if (
									    pre_tok_state.get('''lowercase'''							,							lowerCAmelCase_    ) != do_lower_case
									    or pre_tok_state.get('''strip_accents'''							,							lowerCAmelCase_    ) != strip_accents
									):
													A_													=	getattr(lowerCAmelCase_							,							pre_tok_state.pop('''type'''    )    )
													A_													=	do_lower_case
													A_													=	strip_accents
													A_													=	pre_tok_class(**lowerCAmelCase_    )

									A_													=	do_lower_case


					def __getstate__(						self    )		->				int:





									'''simple docstring'''
									A_													=	self.__dict__.copy()
									A_													=	BertPreTokenizer()
									return state


					def __setstate__(						self							,							a__    )		->				Optional[Any]:





									'''simple docstring'''
									A_													=	d
									A_													=	self.__dict__['''_tokenizer'''].get_vocab()
									A_													=	PreTokenizer.custom(JiebaPreTokenizer(lowerCAmelCase_    )    )


					def 							lowerCAmelCase_     (						self							,							a__							,							a__=None    )		->				int:





									'''simple docstring'''
									A_													=	[self.cls_token_id] + token_ids_a + [self.sep_token_id]

									if token_ids_a:
													output += token_ids_a + [self.sep_token_id]

									return output


					def 							lowerCAmelCase_     (						self							,							a__							,							a__ = None    )		->				List[int]:





									'''simple docstring'''
									A_													=	[self.sep_token_id]
									A_													=	[self.cls_token_id]
									if token_ids_a is None:
													return len(cls + token_ids_a + sep    ) * [0]
									return len(cls + token_ids_a + sep    ) * [0] + len(token_ids_a + sep    ) * [1]


					def 							lowerCAmelCase_     (						self							,							a__							,							a__ = None    )		->				Tuple[str]:





									'''simple docstring'''
									A_													=	self._tokenizer.model.save(lowerCAmelCase_							,							name=lowerCAmelCase_    )
									return tuple(lowerCAmelCase_    )


					def 							lowerCAmelCase_     (						self							,							a__							,							a__=None							,							a__=None							,							a__=False							,							**a__							,							)		->				Optional[Any]:





									'''simple docstring'''
									A_													=	BertPreTokenizer()
									return super().save_pretrained(lowerCAmelCase_							,							lowerCAmelCase_							,							lowerCAmelCase_							,							lowerCAmelCase_							,							**lowerCAmelCase_    )



'''simple docstring'''





from __future__ import annotations

import csv

import requests
from bsa import BeautifulSoup






def 						UpperCAmelCase__(				_SCREAMING_SNAKE_CASE					: str = "" ):






			"""simple docstring"""




			__A=	url or 'https://www.imdb.com/chart/top/?ref_=nv_mv_250'
			__A=	BeautifulSoup(requests.get(_SCREAMING_SNAKE_CASE ).text,'html.parser' )
			__A=	soup.find_all('td',attrs='titleColumn' )
			__A=	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" ):






			"""simple docstring"""




			__A=	get_imdb_top_aaa_movies()
			with open(_SCREAMING_SNAKE_CASE,'w',newline='' ) as out_file:
						__A=	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()



