



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

import sentencepiece as spm

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


SCREAMING_SNAKE_CASE__       =      logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__       =      '''▁'''

SCREAMING_SNAKE_CASE__       =      {'''vocab_file''': '''sentencepiece.bpe.model'''}

SCREAMING_SNAKE_CASE__       =      {
    '''vocab_file''': {
        '''facebook/nllb-200-distilled-600M''': (
            '''https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model'''
        ),
    }
}

SCREAMING_SNAKE_CASE__       =      {
    '''facebook/nllb-200-distilled-600M''': 1_0_2_4,
}

# fmt: off
SCREAMING_SNAKE_CASE__       =      ['''ace_Arab''', '''ace_Latn''', '''acm_Arab''', '''acq_Arab''', '''aeb_Arab''', '''afr_Latn''', '''ajp_Arab''', '''aka_Latn''', '''amh_Ethi''', '''apc_Arab''', '''arb_Arab''', '''ars_Arab''', '''ary_Arab''', '''arz_Arab''', '''asm_Beng''', '''ast_Latn''', '''awa_Deva''', '''ayr_Latn''', '''azb_Arab''', '''azj_Latn''', '''bak_Cyrl''', '''bam_Latn''', '''ban_Latn''', '''bel_Cyrl''', '''bem_Latn''', '''ben_Beng''', '''bho_Deva''', '''bjn_Arab''', '''bjn_Latn''', '''bod_Tibt''', '''bos_Latn''', '''bug_Latn''', '''bul_Cyrl''', '''cat_Latn''', '''ceb_Latn''', '''ces_Latn''', '''cjk_Latn''', '''ckb_Arab''', '''crh_Latn''', '''cym_Latn''', '''dan_Latn''', '''deu_Latn''', '''dik_Latn''', '''dyu_Latn''', '''dzo_Tibt''', '''ell_Grek''', '''eng_Latn''', '''epo_Latn''', '''est_Latn''', '''eus_Latn''', '''ewe_Latn''', '''fao_Latn''', '''pes_Arab''', '''fij_Latn''', '''fin_Latn''', '''fon_Latn''', '''fra_Latn''', '''fur_Latn''', '''fuv_Latn''', '''gla_Latn''', '''gle_Latn''', '''glg_Latn''', '''grn_Latn''', '''guj_Gujr''', '''hat_Latn''', '''hau_Latn''', '''heb_Hebr''', '''hin_Deva''', '''hne_Deva''', '''hrv_Latn''', '''hun_Latn''', '''hye_Armn''', '''ibo_Latn''', '''ilo_Latn''', '''ind_Latn''', '''isl_Latn''', '''ita_Latn''', '''jav_Latn''', '''jpn_Jpan''', '''kab_Latn''', '''kac_Latn''', '''kam_Latn''', '''kan_Knda''', '''kas_Arab''', '''kas_Deva''', '''kat_Geor''', '''knc_Arab''', '''knc_Latn''', '''kaz_Cyrl''', '''kbp_Latn''', '''kea_Latn''', '''khm_Khmr''', '''kik_Latn''', '''kin_Latn''', '''kir_Cyrl''', '''kmb_Latn''', '''kon_Latn''', '''kor_Hang''', '''kmr_Latn''', '''lao_Laoo''', '''lvs_Latn''', '''lij_Latn''', '''lim_Latn''', '''lin_Latn''', '''lit_Latn''', '''lmo_Latn''', '''ltg_Latn''', '''ltz_Latn''', '''lua_Latn''', '''lug_Latn''', '''luo_Latn''', '''lus_Latn''', '''mag_Deva''', '''mai_Deva''', '''mal_Mlym''', '''mar_Deva''', '''min_Latn''', '''mkd_Cyrl''', '''plt_Latn''', '''mlt_Latn''', '''mni_Beng''', '''khk_Cyrl''', '''mos_Latn''', '''mri_Latn''', '''zsm_Latn''', '''mya_Mymr''', '''nld_Latn''', '''nno_Latn''', '''nob_Latn''', '''npi_Deva''', '''nso_Latn''', '''nus_Latn''', '''nya_Latn''', '''oci_Latn''', '''gaz_Latn''', '''ory_Orya''', '''pag_Latn''', '''pan_Guru''', '''pap_Latn''', '''pol_Latn''', '''por_Latn''', '''prs_Arab''', '''pbt_Arab''', '''quy_Latn''', '''ron_Latn''', '''run_Latn''', '''rus_Cyrl''', '''sag_Latn''', '''san_Deva''', '''sat_Beng''', '''scn_Latn''', '''shn_Mymr''', '''sin_Sinh''', '''slk_Latn''', '''slv_Latn''', '''smo_Latn''', '''sna_Latn''', '''snd_Arab''', '''som_Latn''', '''sot_Latn''', '''spa_Latn''', '''als_Latn''', '''srd_Latn''', '''srp_Cyrl''', '''ssw_Latn''', '''sun_Latn''', '''swe_Latn''', '''swh_Latn''', '''szl_Latn''', '''tam_Taml''', '''tat_Cyrl''', '''tel_Telu''', '''tgk_Cyrl''', '''tgl_Latn''', '''tha_Thai''', '''tir_Ethi''', '''taq_Latn''', '''taq_Tfng''', '''tpi_Latn''', '''tsn_Latn''', '''tso_Latn''', '''tuk_Latn''', '''tum_Latn''', '''tur_Latn''', '''twi_Latn''', '''tzm_Tfng''', '''uig_Arab''', '''ukr_Cyrl''', '''umb_Latn''', '''urd_Arab''', '''uzn_Latn''', '''vec_Latn''', '''vie_Latn''', '''war_Latn''', '''wol_Latn''', '''xho_Latn''', '''ydd_Hebr''', '''yor_Latn''', '''yue_Hant''', '''zho_Hans''', '''zho_Hant''', '''zul_Latn''']


class      __lowerCAmelCase     (		UpperCAmelCase_      ):
					"""simple docstring"""






					A__				:		Optional[Any]			       =    VOCAB_FILES_NAMES
					A__				:		List[Any]			       =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					A__				:		Optional[int]			       =    PRETRAINED_VOCAB_FILES_MAP
					A__				:		Optional[Any]			       =    ["input_ids", "attention_mask"]

					A__				:		List[int]			       =    []
					A__				:		List[int]			       =    []



					def __init__(     self					:       Tuple				,					_snake_case					:       str				,					_snake_case					:       List[str]="<s>"				,					_snake_case					:       int="</s>"				,					_snake_case					:       Optional[Any]="</s>"				,					_snake_case					:       Union[str, Any]="<s>"				,					_snake_case					:       Any="<unk>"				,					_snake_case					:       str="<pad>"				,					_snake_case					:       Optional[Any]="<mask>"				,					_snake_case					:       Tuple=None				,					_snake_case					:       Optional[int]=None				,					_snake_case					:       Optional[Any]=None				,					_snake_case					:       Optional[Dict[str, Any]] = None				,					_snake_case					:       List[str]=None				,					_snake_case					:       Optional[int]=False				,					**_snake_case					:       List[str]				,					):






								"""simple docstring"""


								A__       =    AddedToken(_snake_case				,					lstrip=_snake_case				,					rstrip=_snake_case					) if isinstance(_snake_case				,					_snake_case					) else mask_token

								A__       =    {} if sp_model_kwargs is None else sp_model_kwargs
								A__       =    legacy_behaviour

								super().__init__(
								    bos_token=_snake_case				,					eos_token=_snake_case				,					unk_token=_snake_case				,					sep_token=_snake_case				,					cls_token=_snake_case				,					pad_token=_snake_case				,					mask_token=_snake_case				,					tokenizer_file=_snake_case				,					src_lang=_snake_case				,					tgt_lang=_snake_case				,					additional_special_tokens=_snake_case				,					sp_model_kwargs=self.sp_model_kwargs				,					legacy_behaviour=_snake_case				,					**_snake_case				,					)

								A__       =    spm.SentencePieceProcessor(**self.sp_model_kwargs					)
								self.sp_model.Load(str(_snake_case					)					)
								A__       =    vocab_file
								# Original fairseq vocab and spm vocab must be "aligned":
								# Vocab    |    0    |    1    |   2    |    3    |  4   |  5   |  6   |   7  |   8  |  9
								# -------- | ------- | ------- | ------ | ------- | ---- | ---- | ---- | ---- | ---- | ----
								# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
								# spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

								# Mimic fairseq token-to-id alignment for the first 4 token
								A__       =    {'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

								# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
								A__       =    1

								A__       =    len(self.sp_model					)
								A__       =    {
								    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(_snake_case					)
								}
								A__       =    {v: k for k, v in self.lang_code_to_id.items()}
								A__       =    len(self.sp_model					) + len(self.lang_code_to_id					) + self.fairseq_offset

								self.fairseq_tokens_to_ids.update(self.lang_code_to_id					)
								A__       =    {v: k for k, v in self.fairseq_tokens_to_ids.items()}
								A__       =    list(self.lang_code_to_id.keys()					)

								if additional_special_tokens is not None:
											# Only add those special tokens if they are not already there.
											self._additional_special_tokens.extend(
											    [t for t in additional_special_tokens if t not in self._additional_special_tokens]					)

								A__       =    src_lang if src_lang is not None else 'eng_Latn'
								A__       =    self.lang_code_to_id[self._src_lang]
								A__       =    tgt_lang
								self.set_src_lang_special_tokens(self._src_lang					)



					def __getstate__(     self					:       Optional[Any]					):






								"""simple docstring"""


								A__       =    self.__dict__.copy()
								A__       =    None
								A__       =    self.sp_model.serialized_model_proto()
								return state



					def __setstate__(     self					:       List[Any]				,					_snake_case					:       Optional[Any]					):






								"""simple docstring"""


								A__       =    d

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

								A__       =    spm.SentencePieceProcessor(**self.sp_model_kwargs					)
								self.sp_model.LoadFromSerializedProto(self.sp_model_proto					)



					@property
					def     _a							(     self					:       Tuple					):






								"""simple docstring"""


								return len(self.sp_model					) + len(self.lang_code_to_id					) + self.fairseq_offset + 1  # Plus 1 for the mask token



					@property
					def     _a							(     self					:       str					):






								"""simple docstring"""


								return self._src_lang



					@src_lang.setter
					def     _a							(     self					:       Any				,					_snake_case					:       str					):






								"""simple docstring"""


								A__       =    new_src_lang
								self.set_src_lang_special_tokens(self._src_lang					)



					def     _a							(     self					:       Optional[Any]				,					_snake_case					:       List[int]				,					_snake_case					:       Optional[List[int]] = None				,					_snake_case					:       bool = False					):






								"""simple docstring"""


								if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=_snake_case				,					token_ids_a=_snake_case				,					already_has_special_tokens=_snake_case					)

								A__       =    [1] * len(self.prefix_tokens					)
								A__       =    [1] * len(self.suffix_tokens					)
								if token_ids_a is None:
											return prefix_ones + ([0] * len(_snake_case					)) + suffix_ones
								return prefix_ones + ([0] * len(_snake_case					)) + ([0] * len(_snake_case					)) + suffix_ones



					def     _a							(     self					:       str				,					_snake_case					:       List[int]				,					_snake_case					:       Optional[List[int]] = None					):






								"""simple docstring"""


								if token_ids_a is None:
											return self.prefix_tokens + token_ids_a + self.suffix_tokens
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens



					def     _a							(     self					:       str				,					_snake_case					:       List[int]				,					_snake_case					:       Optional[List[int]] = None					):






								"""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 + sep + token_ids_a + sep					) * [0]



					def     _a							(     self					:       List[Any]				,					_snake_case					:       Any				,					_snake_case					:       str				,					_snake_case					:       Optional[str]				,					_snake_case					:       Optional[str]				,					**_snake_case					:       Optional[Any]					):






								"""simple docstring"""


								if src_lang is None or tgt_lang is None:
											raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'					)
								A__       =    src_lang
								A__       =    self(_snake_case				,					add_special_tokens=_snake_case				,					return_tensors=_snake_case				,					**_snake_case					)
								A__       =    self.convert_tokens_to_ids(_snake_case					)
								A__       =    tgt_lang_id
								return inputs



					def     _a							(     self					:       Optional[int]					):






								"""simple docstring"""


								A__       =    {self.convert_ids_to_tokens(_snake_case					): i for i in range(self.vocab_size					)}
								vocab.update(self.added_tokens_encoder					)
								return vocab



					def     _a							(     self					:       Any				,					_snake_case					:       str					):






								"""simple docstring"""


								return self.sp_model.encode(_snake_case				,					out_type=_snake_case					)



					def     _a							(     self					:       str				,					_snake_case					:       List[str]					):






								"""simple docstring"""


								if token in self.fairseq_tokens_to_ids:
											return self.fairseq_tokens_to_ids[token]
								A__       =    self.sp_model.PieceToId(_snake_case					)

								# Need to return unknown token if the SP model returned 0
								return spm_id + self.fairseq_offset if spm_id else self.unk_token_id



					def     _a							(     self					:       Optional[Any]				,					_snake_case					:       List[Any]					):






								"""simple docstring"""


								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     _a							(     self					:       Optional[int]				,					_snake_case					:       Dict					):






								"""simple docstring"""


								A__       =    ''.join(_snake_case					).replace(_snake_case				,					' '					).strip()
								return out_string



					def     _a							(     self					:       Optional[Any]				,					_snake_case					:       str				,					_snake_case					:       Optional[str] = None					):






								"""simple docstring"""


								if not os.path.isdir(_snake_case					):
											logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''					)
											return
								A__       =    os.path.join(
								    _snake_case				,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']					)

								if os.path.abspath(self.vocab_file					) != os.path.abspath(_snake_case					) and os.path.isfile(self.vocab_file					):
											copyfile(self.vocab_file				,					_snake_case					)
								elif not os.path.isfile(self.vocab_file					):
											with open(_snake_case				,					'wb'					) as fi:
														A__       =    self.sp_model.serialized_model_proto()
														fi.write(_snake_case					)

								return (out_vocab_file,)



					def     _a							(     self					:       Tuple				,					_snake_case					:       List[str]				,					_snake_case					:       str = "eng_Latn"				,					_snake_case					:       Optional[List[str]] = None				,					_snake_case					:       str = "fra_Latn"				,					**_snake_case					:       Dict				,					):






								"""simple docstring"""


								A__       =    src_lang
								A__       =    tgt_lang
								return super().prepare_seqaseq_batch(_snake_case				,					_snake_case				,					**_snake_case					)



					def     _a							(     self					:       int					):






								"""simple docstring"""


								return self.set_src_lang_special_tokens(self.src_lang					)



					def     _a							(     self					:       List[Any]					):






								"""simple docstring"""


								return self.set_tgt_lang_special_tokens(self.tgt_lang					)



					def     _a							(     self					:       List[str]				,					_snake_case					:       Tuple					):






								"""simple docstring"""


								A__       =    self.lang_code_to_id[src_lang]
								if self.legacy_behaviour:
											A__       =    []
											A__       =    [self.eos_token_id, self.cur_lang_code]
								else:
											A__       =    [self.cur_lang_code]
											A__       =    [self.eos_token_id]



					def     _a							(     self					:       List[Any]				,					_snake_case					:       str					):






								"""simple docstring"""


								A__       =    self.lang_code_to_id[lang]
								if self.legacy_behaviour:
											A__       =    []
											A__       =    [self.eos_token_id, self.cur_lang_code]
								else:
											A__       =    [self.cur_lang_code]
											A__       =    [self.eos_token_id]









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__":
							SCREAMING_SNAKE_CASE__       =      '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input('''Search: ''')))

							print('''Googling.....''')

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

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

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

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

							webbrowser.open(link)




