






"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_lowerCAmelCase         =							logging.get_logger(__name__)

_lowerCAmelCase         =							{"vocab_file": "sentencepiece.bpe.model"}

_lowerCAmelCase         =							{
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    }
}

_lowerCAmelCase         =							{
    "camembert-base": 512,
}

_lowerCAmelCase         =							"▁"



class      SCREAMING_SNAKE_CASE  (				_SCREAMING_SNAKE_CASE						):





	"""simple docstring"""




	_A       :				List[Any]    =				VOCAB_FILES_NAMES
	_A       :				List[Any]    =				PRETRAINED_VOCAB_FILES_MAP
	_A       :				List[str]    =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_A       :				Union[str, Any]    =				["""input_ids""", """attention_mask"""]





	def __init__(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_="<s>"     ,     lowerCAmelCase_="</s>"     ,     lowerCAmelCase_="</s>"     ,     lowerCAmelCase_="<s>"     ,     lowerCAmelCase_="<unk>"     ,     lowerCAmelCase_="<pad>"     ,     lowerCAmelCase_="<mask>"     ,     lowerCAmelCase_=["<s>NOTUSED", "</s>NOTUSED"]     ,     lowerCAmelCase_ = None     ,     **lowerCAmelCase_     ,     ):
		# Mask token behave like a normal word, i.e. include the space before it
		A_		:						Any	    =   AddedToken(lowerCAmelCase_     ,     lstrip=lowerCAmelCase_     ,     rstrip=lowerCAmelCase_							) if isinstance(lowerCAmelCase_     ,     lowerCAmelCase_							) else mask_token

		A_		:						Any	    =   {} if sp_model_kwargs is None else sp_model_kwargs

		super().__init__(
		    bos_token=lowerCAmelCase_     ,     eos_token=lowerCAmelCase_     ,     unk_token=lowerCAmelCase_     ,     sep_token=lowerCAmelCase_     ,     cls_token=lowerCAmelCase_     ,     pad_token=lowerCAmelCase_     ,     mask_token=lowerCAmelCase_     ,     additional_special_tokens=lowerCAmelCase_     ,     sp_model_kwargs=self.sp_model_kwargs     ,     **lowerCAmelCase_     ,     )
		A_		:						Optional[int]	    =   spm.SentencePieceProcessor(**self.sp_model_kwargs							)
		self.sp_model.Load(str(lowerCAmelCase_							)							)
		A_		:						Any	    =   vocab_file
		# HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
		# sentencepiece vocabulary (this is the case for <s> and </s>
		A_		:						List[Any]	    =   {"""<s>NOTUSED""": 0, """<pad>""": 1, """</s>NOTUSED""": 2, """<unk>""": 3}
		A_		:						List[str]	    =   len(self.fairseq_tokens_to_ids							)
		A_		:						List[str]	    =   len(self.sp_model							) + len(self.fairseq_tokens_to_ids							)
		A_		:						List[str]	    =   {v: k for k, v in self.fairseq_tokens_to_ids.items()}





	def    lowerCamelCase(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_ = None							):

		if token_ids_a is None:
			return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
		A_		:						List[str]	    =   [self.cls_token_id]
		A_		:						int	    =   [self.sep_token_id]
		return cls + token_ids_a + sep + sep + token_ids_a + sep





	def    lowerCamelCase(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_ = None     ,     lowerCAmelCase_ = False							):
		if already_has_special_tokens:
			return super().get_special_tokens_mask(
			    token_ids_a=lowerCAmelCase_     ,     token_ids_a=lowerCAmelCase_     ,     already_has_special_tokens=lowerCAmelCase_							)

		if token_ids_a is None:
			return [1] + ([0] * len(lowerCAmelCase_							)) + [1]
		return [1] + ([0] * len(lowerCAmelCase_							)) + [1, 1] + ([0] * len(lowerCAmelCase_							)) + [1]





	def    lowerCamelCase(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_ = None							):
		A_		:						Tuple	    =   [self.sep_token_id]
		A_		:						int	    =   [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 + sep + token_ids_a + sep							) * [0]





	@property
	def    lowerCamelCase(self							):
		return len(self.fairseq_tokens_to_ids							) + len(self.sp_model							)





	def    lowerCamelCase(self							):
		A_		:						Dict	    =   {self.convert_ids_to_tokens(lowerCAmelCase_							): i for i in range(self.vocab_size							)}
		vocab.update(self.added_tokens_encoder							)
		return vocab





	def    lowerCamelCase(self     ,     lowerCAmelCase_							):
		return self.sp_model.encode(lowerCAmelCase_     ,     out_type=lowerCAmelCase_							)





	def    lowerCamelCase(self     ,     lowerCAmelCase_							):
		if token in self.fairseq_tokens_to_ids:
			return self.fairseq_tokens_to_ids[token]
		elif self.sp_model.PieceToId(lowerCAmelCase_							) == 0:
			# Convert sentence piece unk token to fairseq unk token index
			return self.unk_token_id
		return self.fairseq_offset + self.sp_model.PieceToId(lowerCAmelCase_							)





	def    lowerCamelCase(self     ,     lowerCAmelCase_							):
		if index in self.fairseq_ids_to_tokens:
			return self.fairseq_ids_to_tokens[index]
		return self.sp_model.IdToPiece(index - self.fairseq_offset							)





	def    lowerCamelCase(self     ,     lowerCAmelCase_							):
		A_		:						Union[str, Any]	    =   []
		A_		:						List[str]	    =   """"""
		A_		:						List[Any]	    =   False
		for token in tokens:
			# make sure that special tokens are not decoded using sentencepiece model
			if token in self.all_special_tokens:
				if not prev_is_special:
					out_string += " "
				out_string += self.sp_model.decode(lowerCAmelCase_							) + token
				A_		:						Union[str, Any]	    =   True
				A_		:						Dict	    =   []
			else:
				current_sub_tokens.append(lowerCAmelCase_							)
				A_		:						Any	    =   False
		out_string += self.sp_model.decode(lowerCAmelCase_							)
		return out_string.strip()





	def __getstate__(self							):
		A_		:						Union[str, Any]	    =   self.__dict__.copy()
		A_		:						List[Any]	    =   None
		return state





	def __setstate__(self     ,     lowerCAmelCase_							):
		A_		:						Tuple	    =   d

		# for backward compatibility
		if not hasattr(self     ,     """sp_model_kwargs"""							):
			A_		:						Dict	    =   {}

		A_		:						Union[str, Any]	    =   spm.SentencePieceProcessor(**self.sp_model_kwargs							)
		self.sp_model.Load(self.vocab_file							)





	def    lowerCamelCase(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_ = None							):
		if not os.path.isdir(lowerCAmelCase_							):
			logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""							)
			return
		A_		:						int	    =   os.path.join(
		    lowerCAmelCase_     ,     (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]							)

		if os.path.abspath(self.vocab_file							) != os.path.abspath(lowerCAmelCase_							) and os.path.isfile(self.vocab_file							):
			copyfile(self.vocab_file     ,     lowerCAmelCase_							)
		elif not os.path.isfile(self.vocab_file							):
			with open(lowerCAmelCase_     ,     """wb"""							) as fi:
				A_		:						Dict	    =   self.sp_model.serialized_model_proto()
				fi.write(lowerCAmelCase_							)

		return (out_vocab_file,)









"""simple docstring"""
import sys
import webbrowser

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
							print("Googling.....")
							_lowerCAmelCase         =							"https://www.google.com/search?q=" + " ".join(sys.argv[1:])
							_lowerCAmelCase         =							requests.get(url, headers={"UserAgent": UserAgent().random})
							# res.raise_for_status()
							with open("project1a.html", "wb") as out_file:  # only for knowing the class
														for data in res.iter_content(10_000):
																					out_file.write(data)
							_lowerCAmelCase         =							BeautifulSoup(res.text, "html.parser")
							_lowerCAmelCase         =							list(soup.select(".eZt8xd"))[:5]

							print(len(links))
							for link in links:
														if link.text == "Maps":
																					webbrowser.open(link.get("href"))
														else:
																					webbrowser.open(F'https://google.com{link.get("href")}')

