'''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, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


_a   :	Optional[Any] 							=   logging.get_logger(__name__)

_a   :	Tuple 							=   "▁"

_a   :	Dict 							=   {"vocab_file": "sentencepiece.bpe.model"}

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

_a   :	Tuple 							=   {
    "facebook/nllb-200-distilled-600M": 1024,
}

# fmt: off
_a   :	str 							=   ["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 		__A       (__magic_name__   ):
       snake_case       :Optional[Any]				    =					VOCAB_FILES_NAMES
       snake_case       :int				    =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       snake_case       :Union[str, Any]				    =					PRETRAINED_VOCAB_FILES_MAP
       snake_case       :Dict				    =					["input_ids", "attention_mask"]

       snake_case       :List[int]				    =					[]
       snake_case       :List[int]				    =					[]






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

              __UpperCAmelCase  :				Optional[int]       				=		{} if sp_model_kwargs is None else sp_model_kwargs
              __UpperCAmelCase  :				Any       				=		legacy_behaviour

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

              __UpperCAmelCase  :				List[str]       				=		spm.SentencePieceProcessor(**self.sp_model_kwargs      )
              self.sp_model.Load(str(UpperCamelCase_      )      )
              __UpperCAmelCase  :				Optional[Any]       				=		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
              __UpperCAmelCase  :				List[Any]       				=		{"<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
              __UpperCAmelCase  :				str       				=		1

              __UpperCAmelCase  :				Union[str, Any]       				=		len(self.sp_model      )
              __UpperCAmelCase  :				List[Any]       				=		{
                  code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(UpperCamelCase_      )
              }
              __UpperCAmelCase  :				Optional[Any]       				=		{v: k for k, v in self.lang_code_to_id.items()}
              __UpperCAmelCase  :				Optional[int]       				=		len(self.sp_model      ) + len(self.lang_code_to_id      ) + self.fairseq_offset

              self.fairseq_tokens_to_ids.update(self.lang_code_to_id      )
              __UpperCAmelCase  :				Union[str, Any]       				=		{v: k for k, v in self.fairseq_tokens_to_ids.items()}
              __UpperCAmelCase  :				Any       				=		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]      )

              __UpperCAmelCase  :				Optional[Any]       				=		src_lang if src_lang is not None else "eng_Latn"
              __UpperCAmelCase  :				Optional[int]       				=		self.lang_code_to_id[self._src_lang]
              __UpperCAmelCase  :				Tuple       				=		tgt_lang
              self.set_src_lang_special_tokens(self._src_lang      )






       def __getstate__(      self      ):
              __UpperCAmelCase  :				int       				=		self.__dict__.copy()
              __UpperCAmelCase  :				str       				=		None
              __UpperCAmelCase  :				Any       				=		self.sp_model.serialized_model_proto()
              return state






       def __setstate__(      self				,     UpperCamelCase_      ):
              __UpperCAmelCase  :				Optional[Any]       				=		d

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

              __UpperCAmelCase  :				List[Any]       				=		spm.SentencePieceProcessor(**self.sp_model_kwargs      )
              self.sp_model.LoadFromSerializedProto(self.sp_model_proto      )






       @property
       def 			_snake_case						(      self      ):
              return len(self.sp_model      ) + len(self.lang_code_to_id      ) + self.fairseq_offset + 1  # Plus 1 for the mask token






       @property
       def 			_snake_case						(      self      ):
              return self._src_lang






       @src_lang.setter
       def 			_snake_case						(      self				,     UpperCamelCase_      ):
              __UpperCAmelCase  :				List[Any]       				=		new_src_lang
              self.set_src_lang_special_tokens(self._src_lang      )






       def 			_snake_case						(      self				,     UpperCamelCase_				,     UpperCamelCase_ = None				,     UpperCamelCase_ = False      ):

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

              __UpperCAmelCase  :				Optional[int]       				=		[1] * len(self.prefix_tokens      )
              __UpperCAmelCase  :				str       				=		[1] * len(self.suffix_tokens      )
              if token_ids_a is None:
                     return prefix_ones + ([0] * len(UpperCamelCase_      )) + suffix_ones
              return prefix_ones + ([0] * len(UpperCamelCase_      )) + ([0] * len(UpperCamelCase_      )) + suffix_ones






       def 			_snake_case						(      self				,     UpperCamelCase_				,     UpperCamelCase_ = None      ):
              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 			_snake_case						(      self				,     UpperCamelCase_				,     UpperCamelCase_ = None      ):
              __UpperCAmelCase  :				Optional[Any]       				=		[self.sep_token_id]
              __UpperCAmelCase  :				Dict       				=		[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 			_snake_case						(      self				,     UpperCamelCase_				,     UpperCamelCase_				,     UpperCamelCase_				,     UpperCamelCase_				,     **UpperCamelCase_      ):
              if src_lang is None or tgt_lang is None:
                     raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"      )
              __UpperCAmelCase  :				Union[str, Any]       				=		src_lang
              __UpperCAmelCase  :				str       				=		self(UpperCamelCase_				,     add_special_tokens=UpperCamelCase_				,     return_tensors=UpperCamelCase_				,     **UpperCamelCase_      )
              __UpperCAmelCase  :				Union[str, Any]       				=		self.convert_tokens_to_ids(UpperCamelCase_      )
              __UpperCAmelCase  :				Optional[int]       				=		tgt_lang_id
              return inputs






       def 			_snake_case						(      self      ):
              __UpperCAmelCase  :				Optional[Any]       				=		{self.convert_ids_to_tokens(UpperCamelCase_      ): i for i in range(self.vocab_size      )}
              vocab.update(self.added_tokens_encoder      )
              return vocab






       def 			_snake_case						(      self				,     UpperCamelCase_      ):
              return self.sp_model.encode(UpperCamelCase_				,     out_type=UpperCamelCase_      )






       def 			_snake_case						(      self				,     UpperCamelCase_      ):
              if token in self.fairseq_tokens_to_ids:
                     return self.fairseq_tokens_to_ids[token]
              __UpperCAmelCase  :				Union[str, Any]       				=		self.sp_model.PieceToId(UpperCamelCase_      )

              # 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 			_snake_case						(      self				,     UpperCamelCase_      ):
              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 			_snake_case						(      self				,     UpperCamelCase_      ):
              __UpperCAmelCase  :				str       				=		"".join(UpperCamelCase_      ).replace(UpperCamelCase_				,     " "      ).strip()
              return out_string






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

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

              return (out_vocab_file,)






       def 			_snake_case						(      self				,     UpperCamelCase_				,     UpperCamelCase_ = "eng_Latn"				,     UpperCamelCase_ = None				,     UpperCamelCase_ = "fra_Latn"				,     **UpperCamelCase_				,     ):
              __UpperCAmelCase  :				Tuple       				=		src_lang
              __UpperCAmelCase  :				Dict       				=		tgt_lang
              return super().prepare_seqaseq_batch(UpperCamelCase_				,     UpperCamelCase_				,     **UpperCamelCase_      )






       def 			_snake_case						(      self      ):
              return self.set_src_lang_special_tokens(self.src_lang      )






       def 			_snake_case						(      self      ):
              return self.set_tgt_lang_special_tokens(self.tgt_lang      )






       def 			_snake_case						(      self				,     UpperCamelCase_      ):
              __UpperCAmelCase  :				int       				=		self.lang_code_to_id[src_lang]
              if self.legacy_behaviour:
                     __UpperCAmelCase  :				Union[str, Any]       				=		[]
                     __UpperCAmelCase  :				Optional[int]       				=		[self.eos_token_id, self.cur_lang_code]
              else:
                     __UpperCAmelCase  :				Dict       				=		[self.cur_lang_code]
                     __UpperCAmelCase  :				Any       				=		[self.eos_token_id]







       def 			_snake_case						(      self				,     UpperCamelCase_      ):
              __UpperCAmelCase  :				int       				=		self.lang_code_to_id[lang]
              if self.legacy_behaviour:
                     __UpperCAmelCase  :				Union[str, Any]       				=		[]
                     __UpperCAmelCase  :				Optional[int]       				=		[self.eos_token_id, self.cur_lang_code]
              else:
                     __UpperCAmelCase  :				Tuple       				=		[self.cur_lang_code]
                     __UpperCAmelCase  :				Any       				=		[self.eos_token_id]







'''simple docstring'''




def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       int:





       """simple docstring"""


       return number | (1 << position)

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       int:





       """simple docstring"""


       return number & ~(1 << position)

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       int:





       """simple docstring"""


       return number ^ (1 << position)

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       bool:





       """simple docstring"""


       return ((number >> position) & 1) == 1

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       int:





       """simple docstring"""


       return int((number & (1 << position)) != 0						)


if __name__ == "__main__":
   import doctest

   doctest.testmod()






