
"""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__ :       List[Any]				= logging.get_logger(__name__)

A__ :       Tuple				= '▁'

A__ :       Dict				= {'vocab_file': 'sentencepiece.bpe.model'}

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

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

# fmt: off
A__ :       Union[str, Any]				= ['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       __magic_name__							(							SCREAMING_SNAKE_CASE__			):
       UpperCamelCase_ =		VOCAB_FILES_NAMES
       UpperCamelCase_ =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCamelCase_ =		PRETRAINED_VOCAB_FILES_MAP
       UpperCamelCase_ =		['''input_ids''', '''attention_mask''']

       UpperCamelCase_ =		[]
       UpperCamelCase_ =		[]
       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_			,					)  ->						Union[str, Any]:





         """simple docstring"""




         _lowercase:      Tuple   			=  AddedToken(A_			,					lstrip=A_			,					rstrip=A_							) if isinstance(A_			,					A_							) else mask_token

         _lowercase:      Optional[int]   			=  {} if sp_model_kwargs is None else sp_model_kwargs
         _lowercase:      str   			=  legacy_behaviour

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

         _lowercase:      List[Any]   			=  spm.SentencePieceProcessor(**self.sp_model_kwargs							)
         self.sp_model.Load(str(A_							)							)
         _lowercase:      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:      Tuple   			=  {'''<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:      List[str]   			=  1

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

         _lowercase:      Tuple   			=  src_lang if src_lang is not None else '''eng_Latn'''
         _lowercase:      int   			=  self.lang_code_to_id[self._src_lang]
         _lowercase:      Union[str, Any]   			=  tgt_lang
         self.set_src_lang_special_tokens(self._src_lang							)
       def __getstate__(  self							)  ->						int:





         """simple docstring"""




         _lowercase:      Tuple   			=  self.__dict__.copy()
         _lowercase:      Optional[int]   			=  None
         _lowercase:      int   			=  self.sp_model.serialized_model_proto()
         return state
       def __setstate__(  self			,					A_							)  ->						int:





         """simple docstring"""




         _lowercase:      Tuple   			=  d

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

         _lowercase:      Tuple   			=  spm.SentencePieceProcessor(**self.sp_model_kwargs							)
         self.sp_model.LoadFromSerializedProto(self.sp_model_proto							)
       @property
       def 				lowercase_				(  self							)  ->						Dict:





         """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 				lowercase_				(  self							)  ->						str:





         """simple docstring"""




         return self._src_lang
       @src_lang.setter
       def 				lowercase_				(  self			,					A_							)  ->						None:





         """simple docstring"""




         _lowercase:      Optional[Any]   			=  new_src_lang
         self.set_src_lang_special_tokens(self._src_lang							)
       def 				lowercase_				(  self			,					A_			,					A_ = None			,					A_ = False							)  ->						List[int]:





         """simple docstring"""




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

         _lowercase:      List[str]   			=  [1] * len(self.prefix_tokens							)
         _lowercase:      int   			=  [1] * len(self.suffix_tokens							)
         if token_ids_a is None:
           return prefix_ones + ([0] * len(A_							)) + suffix_ones
         return prefix_ones + ([0] * len(A_							)) + ([0] * len(A_							)) + suffix_ones
       def 				lowercase_				(  self			,					A_			,					A_ = None							)  ->						List[int]:





         """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 				lowercase_				(  self			,					A_			,					A_ = None							)  ->						List[int]:





         """simple docstring"""




         _lowercase:      Any   			=  [self.sep_token_id]
         _lowercase:      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 				lowercase_				(  self			,					A_			,					A_			,					A_			,					A_			,					**A_							)  ->						int:





         """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'''							)
         _lowercase:      str   			=  src_lang
         _lowercase:      int   			=  self(A_			,					add_special_tokens=A_			,					return_tensors=A_			,					**A_							)
         _lowercase:      Any   			=  self.convert_tokens_to_ids(A_							)
         _lowercase:      Optional[Any]   			=  tgt_lang_id
         return inputs
       def 				lowercase_				(  self							)  ->						Optional[int]:





         """simple docstring"""




         _lowercase:      int   			=  {self.convert_ids_to_tokens(A_							): i for i in range(self.vocab_size							)}
         vocab.update(self.added_tokens_encoder							)
         return vocab
       def 				lowercase_				(  self			,					A_							)  ->						List[str]:





         """simple docstring"""




         return self.sp_model.encode(A_			,					out_type=A_							)
       def 				lowercase_				(  self			,					A_							)  ->						Tuple:





         """simple docstring"""




         if token in self.fairseq_tokens_to_ids:
           return self.fairseq_tokens_to_ids[token]
         _lowercase:      Union[str, Any]   			=  self.sp_model.PieceToId(A_							)

         # 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 				lowercase_				(  self			,					A_							)  ->						str:





         """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 				lowercase_				(  self			,					A_							)  ->						int:





         """simple docstring"""




         _lowercase:      Tuple   			=  ''''''.join(A_							).replace(A_			,					''' '''							).strip()
         return out_string
       def 				lowercase_				(  self			,					A_			,					A_ = None							)  ->						Tuple[str]:





         """simple docstring"""




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

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

         return (out_vocab_file,)
       def 				lowercase_				(  self			,					A_			,					A_ = "eng_Latn"			,					A_ = None			,					A_ = "fra_Latn"			,					**A_			,					)  ->						BatchEncoding:





         """simple docstring"""




         _lowercase:      List[str]   			=  src_lang
         _lowercase:      str   			=  tgt_lang
         return super().prepare_seqaseq_batch(A_			,					A_			,					**A_							)
       def 				lowercase_				(  self							)  ->						str:





         """simple docstring"""




         return self.set_src_lang_special_tokens(self.src_lang							)
       def 				lowercase_				(  self							)  ->						List[Any]:





         """simple docstring"""




         return self.set_tgt_lang_special_tokens(self.tgt_lang							)
       def 				lowercase_				(  self			,					A_							)  ->						None:





         """simple docstring"""




         _lowercase:      Optional[int]   			=  self.lang_code_to_id[src_lang]
         if self.legacy_behaviour:
           _lowercase:      Any   			=  []
           _lowercase:      Optional[Any]   			=  [self.eos_token_id, self.cur_lang_code]
         else:
           _lowercase:      Optional[int]   			=  [self.cur_lang_code]
           _lowercase:      Optional[int]   			=  [self.eos_token_id]



       def 				lowercase_				(  self			,					A_							)  ->						None:





         """simple docstring"""




         _lowercase:      Optional[Any]   			=  self.lang_code_to_id[lang]
         if self.legacy_behaviour:
           _lowercase:      List[str]   			=  []
           _lowercase:      Optional[int]   			=  [self.eos_token_id, self.cur_lang_code]
         else:
           _lowercase:      Any   			=  [self.cur_lang_code]
           _lowercase:      List[str]   			=  [self.eos_token_id]


"""simple docstring"""




import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


A__ :       List[Any]				= logging.get_logger(__name__)


class       __magic_name__							(							SCREAMING_SNAKE_CASE__			):
       def __init__(  self			,					*A_			,					**A_							)  ->						None:





         """simple docstring"""




         warnings.warn(
             '''The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
             ''' Please use SegformerImageProcessor instead.'''			,					A_			,					)
         super().__init__(*A_			,					**A_							)
