





import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
					UpperCamelCase__											= "%20".join(argv[1:]) if len(argv) > 1 else quote(str(input("Search: ")))

					print("Googling.....")

					UpperCamelCase__											= f"""https://www.google.com/search?q={query}&num=100"""

					UpperCamelCase__											= requests.get(
					    url,
					    headers={"User-Agent": str(UserAgent().random)},
					)

					try:
										UpperCamelCase__											= (
										    BeautifulSoup(res.text, "html.parser")
										    .find("div", attrs={"class": "yuRUbf"})
										    .find("a")
										    .get("href")
										)

					except AttributeError:
										UpperCamelCase__											= parse_qs(
										    BeautifulSoup(res.text, "html.parser")
										    .find("div", attrs={"class": "kCrYT"})
										    .find("a")
										    .get("href")
										)["url"][0]

					webbrowser.open(link)











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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCamelCase__											= "▁"

UpperCamelCase__											= {"vocab_file": "spiece.model"}

UpperCamelCase__											= {
    "vocab_file": {"google/pegasus-xsum": "https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model"}
}

UpperCamelCase__											= {
    "google/pegasus-xsum": 512,
}


UpperCamelCase__											= logging.get_logger(__name__)

class        __SCREAMING_SNAKE_CASE					(     _a       ):
							snake_case     :      Union[str, Any]						     =       VOCAB_FILES_NAMES

							snake_case     :      str						     =       VOCAB_FILES_NAMES
							snake_case     :      Any						     =       PRETRAINED_VOCAB_FILES_MAP
							snake_case     :      int						     =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							snake_case     :      Optional[int]						     =       ["""input_ids""", """attention_mask"""]






							def __init__(						self  , __lowerCAmelCase  , __lowerCAmelCase="<pad>"  , __lowerCAmelCase="</s>"  , __lowerCAmelCase="<unk>"  , __lowerCAmelCase="<mask_2>"  , __lowerCAmelCase="<mask_1>"  , __lowerCAmelCase=None  , __lowerCAmelCase=103  , __lowerCAmelCase = None  , **__lowerCAmelCase  , ):
														UpperCamelCase__				     =			offset
														if additional_special_tokens is not None:
																					if not isinstance(__lowerCAmelCase  , __lowerCAmelCase  ):
																												raise TypeError(
																												    f"""additional_special_tokens should be of type {type(__lowerCAmelCase  )}, but is"""
																												    f""" {type(__lowerCAmelCase  )}"""  )

																					UpperCamelCase__				     =			(
																					    ([mask_token_sent] + additional_special_tokens)
																					    if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
																					    else additional_special_tokens
																					)
																					# fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
																					additional_special_tokens_extended += [
																					    f"""<unk_{i}>""" for i in range(len(__lowerCAmelCase  )  , self.offset - 1  )
																					]

																					if len(set(__lowerCAmelCase  )  ) != len(__lowerCAmelCase  ):
																												raise ValueError(
																												    """Please make sure that the provided additional_special_tokens do not contain an incorrectly"""
																												    f""" shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}."""  )
																					UpperCamelCase__				     =			additional_special_tokens_extended
														else:
																					UpperCamelCase__				     =			[mask_token_sent] if mask_token_sent is not None else []
																					additional_special_tokens += [f"""<unk_{i}>""" for i in range(2  , self.offset  )]

														UpperCamelCase__				     =			{} if sp_model_kwargs is None else sp_model_kwargs

														super().__init__(
														    eos_token=__lowerCAmelCase  , unk_token=__lowerCAmelCase  , mask_token=__lowerCAmelCase  , pad_token=__lowerCAmelCase  , mask_token_sent=__lowerCAmelCase  , offset=__lowerCAmelCase  , additional_special_tokens=__lowerCAmelCase  , sp_model_kwargs=self.sp_model_kwargs  , **__lowerCAmelCase  , )
														UpperCamelCase__				     =			mask_token_sent
														UpperCamelCase__				     =			vocab_file
														UpperCamelCase__				     =			spm.SentencePieceProcessor(**self.sp_model_kwargs  )
														self.sp_model.Load(__lowerCAmelCase  )

														# add special tokens to encoder dict
														UpperCamelCase__				     =			{
														    0: self.pad_token,
														    1: self.eos_token,
														}

														if self.mask_token_sent is not None:
																					self.encoder.update(
																					    {
																					        2: self.mask_token_sent,
																					        3: self.mask_token,
																					    }  )

														if self.offset > 0:
																					# entries 2-104 are only used for pretraining and called <mask_1>, <mask_2>, unk_2, ...unk_102
																					# mask_token_sent is already added to list -> so start at 1
																					self.encoder.update({i + 3: additional_special_tokens[i] for i in range(1  , self.offset - 1  )}  )

														UpperCamelCase__				     =			{v: k for k, v in self.encoder.items()}






							@property
							def 				_lowerCamelCase		(						self  ):
														return len(self.sp_model  ) + self.offset






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			{self.convert_ids_to_tokens(__lowerCAmelCase  ): i for i in range(self.vocab_size  )}
														vocab.update(self.added_tokens_encoder  )
														return vocab






							def __getstate__(						self  ):
														UpperCamelCase__				     =			self.__dict__.copy()
														UpperCamelCase__				     =			None
														return state






							def __setstate__(						self  , __lowerCAmelCase  ):
														UpperCamelCase__				     =			d

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

														UpperCamelCase__				     =			spm.SentencePieceProcessor(**self.sp_model_kwargs  )
														self.sp_model.Load(self.vocab_file  )






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  ):
														return self.sp_model.encode(__lowerCAmelCase  , out_type=__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  ):
														if token in self.decoder:
																					return self.decoder[token]
														elif token in self.added_tokens_decoder:
																					return self.added_tokens_decoder[token]
														UpperCamelCase__				     =			self.sp_model.piece_to_id(__lowerCAmelCase  )
														return sp_id + self.offset






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  ):
														if index in self.encoder:
																					return self.encoder[index]
														elif index in self.added_tokens_encoder:
																					return self.added_tokens_encoder[index]
														else:
																					UpperCamelCase__				     =			self.sp_model.IdToPiece(index - self.offset  )
														return token






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  ):
														UpperCamelCase__				     =			[]
														UpperCamelCase__				     =			""""""
														for token in tokens:
																					# make sure that special tokens are not decoded using sentencepiece model
																					if token in self.all_special_tokens:
																												out_string += self.sp_model.decode(__lowerCAmelCase  ) + token
																												UpperCamelCase__				     =			[]
																					else:
																												current_sub_tokens.append(__lowerCAmelCase  )
														out_string += self.sp_model.decode(__lowerCAmelCase  )
														return out_string.strip()






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase=False  ):
														return 1






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  ):
														UpperCamelCase__				     =			set(self.all_special_ids  )  # call it once instead of inside list comp
														all_special_ids.remove(self.unk_token_id  )  # <unk> is only sometimes special

														return [1 if x in all_special_ids else 0 for x in seq]






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase = None  , __lowerCAmelCase = False  ):
														if already_has_special_tokens:
																					return self._special_token_mask(__lowerCAmelCase  )
														elif token_ids_a is None:
																					return self._special_token_mask(__lowerCAmelCase  ) + [1]
														else:
																					return self._special_token_mask(token_ids_a + token_ids_a  ) + [1]






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase=None  ):
														if token_ids_a is None:
																					return token_ids_a + [self.eos_token_id]
														# We don't expect to process pairs, but leave the pair logic for API consistency
														return token_ids_a + token_ids_a + [self.eos_token_id]







							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase = None  ):
														if not os.path.isdir(__lowerCAmelCase  ):
																					logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""  )
																					return
														UpperCamelCase__				     =			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:
																												UpperCamelCase__				     =			self.sp_model.serialized_model_proto()
																												fi.write(__lowerCAmelCase  )

														return (out_vocab_file,)




