

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


snake_case_			  = logging.get_logger(__name__)

snake_case_			  = '▁'

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

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

snake_case_			  = {
    'facebook/nllb-200-distilled-600M': 1_024,
}

# fmt: off
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       SCREAMING_SNAKE_CASE__					(_lowerCamelCase     ):
    __lowerCamelCase						:       str														=     VOCAB_FILES_NAMES
    __lowerCamelCase						:       str														=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __lowerCamelCase						:       List[str]														=     PRETRAINED_VOCAB_FILES_MAP
    __lowerCamelCase						:       Union[str, Any]														=     ["""input_ids""", """attention_mask"""]

    __lowerCamelCase						:       Union[str, Any]														=     []
    __lowerCamelCase						:       Union[str, Any]														=     []





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

         lowercase__    :   str      =       {} if sp_model_kwargs is None else sp_model_kwargs
         lowercase__    :   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						,   )

         lowercase__    :   List[str]      =       spm.SentencePieceProcessor(**self.sp_model_kwargs)
         self.sp_model.Load(str(_UpperCamelCase))
         lowercase__    :   List[str]      =       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
         lowercase__    :   int      =       {'<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
         lowercase__    :   Any      =       1

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

         lowercase__    :   Optional[Any]      =       src_lang if src_lang is not None else 'eng_Latn'
         lowercase__    :   Optional[int]      =       self.lang_code_to_id[self._src_lang]
         lowercase__    :   Dict      =       tgt_lang
         self.set_src_lang_special_tokens(self._src_lang)





    def __getstate__(      self):
         lowercase__    :   Optional[int]      =       self.__dict__.copy()
         lowercase__    :   int      =       None
         lowercase__    :   str      =       self.sp_model.serialized_model_proto()
         return state





    def __setstate__(      self						,   a):
         lowercase__    :   Any      =       d

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

         lowercase__    :   List[str]      =       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						,   a):
         lowercase__    :   List[str]      =       new_src_lang
         self.set_src_lang_special_tokens(self._src_lang)





    def       snake_case_				(      self						,   a						,   a = None						,   a = 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)

         lowercase__    :   Optional[int]      =       [1] * len(self.prefix_tokens)
         lowercase__    :   List[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						,   a						,   a = 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						,   a						,   a = None):
         lowercase__    :   List[Any]      =       [self.sep_token_id]
         lowercase__    :   str      =       [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						,   a						,   a						,   a						,   a						,   **a):
         if src_lang is None or tgt_lang is None:
              raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model')
         lowercase__    :   Union[str, Any]      =       src_lang
         lowercase__    :   List[str]      =       self(_UpperCamelCase						,   add_special_tokens=_UpperCamelCase						,   return_tensors=_UpperCamelCase						,   **_UpperCamelCase)
         lowercase__    :   List[str]      =       self.convert_tokens_to_ids(_UpperCamelCase)
         lowercase__    :   Tuple      =       tgt_lang_id
         return inputs





    def       snake_case_				(      self):
         lowercase__    :   Dict      =       {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						,   a):
         return self.sp_model.encode(_UpperCamelCase						,   out_type=_UpperCamelCase)





    def       snake_case_				(      self						,   a):
         if token in self.fairseq_tokens_to_ids:
              return self.fairseq_tokens_to_ids[token]
         lowercase__    :   List[str]      =       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						,   a):
         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						,   a):
         lowercase__    :   int      =       ''.join(_UpperCamelCase).replace(_UpperCamelCase						,   ' ').strip()
         return out_string





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

         return (out_vocab_file,)





    def       snake_case_				(      self						,   a						,   a = "eng_Latn"						,   a = None						,   a = "fra_Latn"						,   **a						,   ):
         lowercase__    :   List[Any]      =       src_lang
         lowercase__    :   int      =       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						,   a):
         lowercase__    :   Optional[int]      =       self.lang_code_to_id[src_lang]
         if self.legacy_behaviour:
              lowercase__    :   List[str]      =       []
              lowercase__    :   List[str]      =       [self.eos_token_id, self.cur_lang_code]
         else:
              lowercase__    :   List[Any]      =       [self.cur_lang_code]
              lowercase__    :   List[str]      =       [self.eos_token_id]





    def       snake_case_				(      self						,   a):
         lowercase__    :   str      =       self.lang_code_to_id[lang]
         if self.legacy_behaviour:
              lowercase__    :   Optional[int]      =       []
              lowercase__    :   Any      =       [self.eos_token_id, self.cur_lang_code]
         else:
              lowercase__    :   List[str]      =       [self.cur_lang_code]
              lowercase__    :   str      =       [self.eos_token_id]








from __future__ import annotations



def _a				(	lowerCamelCase:   list[int | str] )	->						None:







      '''simple docstring'''






      create_state_space_tree(lowerCamelCase					,				[]					,				0					,				[0 for i in range(len(lowerCamelCase ) )] )



def _a				(	lowerCamelCase:   list[int | str]					,				lowerCamelCase:   list[int | str]					,				lowerCamelCase:   int					,				lowerCamelCase:   list[int]					,				)	->						None:







      '''simple docstring'''






      if index == len(lowerCamelCase ):
            print(lowerCamelCase )
            return

      for i in range(len(lowerCamelCase ) ):
            if not index_used[i]:
                  current_sequence.append(sequence[i] )
                  __A          =				True
                  create_state_space_tree(lowerCamelCase					,				lowerCamelCase					,				index + 1					,				lowerCamelCase )
                  current_sequence.pop()
                  __A          =				False
snake_case__					:							list[int | str]													=     [3, 1, 2, 4]
generate_all_permutations(sequence)

snake_case__					:							list[int | str]													=     ["A", "B", "C"]







generate_all_permutations(sequence_a)





