





'''simple docstring'''

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

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
   from .tokenization_nllb import NllbTokenizer
else:
   UpperCAmelCase					:		Any		=							None


UpperCAmelCase					:		List[str]		=							logging.get_logger(__name__)


UpperCAmelCase					:		List[Any]		=							{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

UpperCAmelCase					:		List[str]		=							{
    'vocab_file': {
        'facebook/nllb-200-distilled-600M': (
            'https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/sentencepiece.bpe.model'
        ),
    },
    'tokenizer_file': {
        'facebook/nllb-200-distilled-600M': (
            'https://huggingface.co/facebook/nllb-200-distilled-600M/resolve/main/tokenizer.json'
        ),
    },
}

UpperCAmelCase					:		int		=							{
    'facebook/nllb-large-en-ro': 1_0_2_4,
    'facebook/nllb-200-distilled-600M': 1_0_2_4,
}

# fmt: off
UpperCAmelCase					:		Optional[int]		=							['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						(a__					):
  _lowercase  :	Dict       					=				VOCAB_FILES_NAMES
  _lowercase  :	List[str]       					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _lowercase  :	List[str]       					=				PRETRAINED_VOCAB_FILES_MAP
  _lowercase  :	Optional[Any]       					=				["""input_ids""", """attention_mask"""]
  _lowercase  :	List[Any]       					=				NllbTokenizer

  _lowercase  :	List[int]       					=				[]
  _lowercase  :	List[int]       					=				[]







  def __init__(		self     ,     lowercase__=None     ,     lowercase__=None     ,     lowercase__="<s>"     ,     lowercase__="</s>"     ,     lowercase__="</s>"     ,     lowercase__="<s>"     ,     lowercase__="<unk>"     ,     lowercase__="<pad>"     ,     lowercase__="<mask>"     ,     lowercase__=None     ,     lowercase__=None     ,     lowercase__=None     ,     lowercase__=False     ,     **lowercase__     ,     )		->						Tuple:






        """simple docstring"""





        _snake_case		:	List[Any]					     =     AddedToken(lowercase__     ,     lstrip=lowercase__     ,     rstrip=lowercase__		) if isinstance(lowercase__     ,     lowercase__		) else mask_token
        _snake_case		:	Union[str, Any]					     =     legacy_behaviour
        super().__init__(
            vocab_file=lowercase__     ,     tokenizer_file=lowercase__     ,     bos_token=lowercase__     ,     eos_token=lowercase__     ,     sep_token=lowercase__     ,     cls_token=lowercase__     ,     unk_token=lowercase__     ,     pad_token=lowercase__     ,     mask_token=lowercase__     ,     src_lang=lowercase__     ,     tgt_lang=lowercase__     ,     additional_special_tokens=lowercase__     ,     legacy_behaviour=lowercase__     ,     **lowercase__     ,     )

        _snake_case		:	Tuple					     =     vocab_file
        _snake_case		:	int					     =     False if not self.vocab_file else True

        _snake_case		:	Tuple					     =     FAIRSEQ_LANGUAGE_CODES.copy()

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

        self.add_special_tokens({'''additional_special_tokens''': _additional_special_tokens}		)
        _snake_case		:	Union[str, Any]					     =     {
            lang_code: self.convert_tokens_to_ids(lowercase__		) for lang_code in FAIRSEQ_LANGUAGE_CODES
        }

        _snake_case		:	List[str]					     =     src_lang if src_lang is not None else '''eng_Latn'''
        _snake_case		:	List[str]					     =     self.convert_tokens_to_ids(self._src_lang		)
        _snake_case		:	Union[str, Any]					     =     tgt_lang
        self.set_src_lang_special_tokens(self._src_lang		)







  @property
  def 				UpperCAmelCase_				(		self		)		->						str:






        """simple docstring"""





        return self._src_lang







  @src_lang.setter
  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						None:






        """simple docstring"""





        _snake_case		:	str					     =     new_src_lang
        self.set_src_lang_special_tokens(self._src_lang		)







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = 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 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = None		)		->						List[int]:






        """simple docstring"""





        _snake_case		:	List[str]					     =     [self.sep_token_id]
        _snake_case		:	Optional[Any]					     =     [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 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__     ,     lowercase__     ,     lowercase__     ,     **lowercase__		)		->						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'''		)
        _snake_case		:	List[str]					     =     src_lang
        _snake_case		:	Optional[Any]					     =     self(lowercase__     ,     add_special_tokens=lowercase__     ,     return_tensors=lowercase__     ,     **lowercase__		)
        _snake_case		:	str					     =     self.convert_tokens_to_ids(lowercase__		)
        _snake_case		:	str					     =     tgt_lang_id
        return inputs







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = "eng_Latn"     ,     lowercase__ = None     ,     lowercase__ = "fra_Latn"     ,     **lowercase__     ,     )		->						BatchEncoding:






        """simple docstring"""





        _snake_case		:	Optional[Any]					     =     src_lang
        _snake_case		:	Tuple					     =     tgt_lang
        return super().prepare_seqaseq_batch(lowercase__     ,     lowercase__     ,     **lowercase__		)







  def 				UpperCAmelCase_				(		self		)		->						Optional[Any]:






        """simple docstring"""





        return self.set_src_lang_special_tokens(self.src_lang		)







  def 				UpperCAmelCase_				(		self		)		->						int:






        """simple docstring"""





        return self.set_tgt_lang_special_tokens(self.tgt_lang		)







  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						None:






        """simple docstring"""





        _snake_case		:	List[Any]					     =     self.convert_tokens_to_ids(lowercase__		)

        if self.legacy_behaviour:
              _snake_case		:	Any					     =     []
              _snake_case		:	Optional[int]					     =     [self.eos_token_id, self.cur_lang_code]
        else:
              _snake_case		:	int					     =     [self.cur_lang_code]
              _snake_case		:	List[Any]					     =     [self.eos_token_id]

        _snake_case		:	List[Any]					     =     self.convert_ids_to_tokens(self.prefix_tokens		)
        _snake_case		:	List[Any]					     =     self.convert_ids_to_tokens(self.suffix_tokens		)

        _snake_case		:	Dict					     =     processors.TemplateProcessing(
            single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str     ,     pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str     ,     special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str     ,     self.prefix_tokens + self.suffix_tokens		)		)     ,     )







  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						None:






        """simple docstring"""





        _snake_case		:	str					     =     self.convert_tokens_to_ids(lowercase__		)
        if self.legacy_behaviour:
              _snake_case		:	List[str]					     =     []
              _snake_case		:	Optional[int]					     =     [self.eos_token_id, self.cur_lang_code]
        else:
              _snake_case		:	int					     =     [self.cur_lang_code]
              _snake_case		:	str					     =     [self.eos_token_id]

        _snake_case		:	Any					     =     self.convert_ids_to_tokens(self.prefix_tokens		)
        _snake_case		:	int					     =     self.convert_ids_to_tokens(self.suffix_tokens		)

        _snake_case		:	Dict					     =     processors.TemplateProcessing(
            single=prefix_tokens_str + ['''$A'''] + suffix_tokens_str     ,     pair=prefix_tokens_str + ['''$A''', '''$B'''] + suffix_tokens_str     ,     special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str     ,     self.prefix_tokens + self.suffix_tokens		)		)     ,     )







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = None		)		->						Tuple[str]:






        """simple docstring"""





        if not self.can_save_slow_tokenizer:
              raise ValueError(
                  '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
                  '''tokenizer.'''		)

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

        if os.path.abspath(self.vocab_file		) != os.path.abspath(lowercase__		):
              copyfile(self.vocab_file     ,     lowercase__		)

        return (out_vocab_file,)









'''simple docstring'''

# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase					:		Dict		=							{'configuration_timm_backbone': ['TimmBackboneConfig']}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase					:		Union[str, Any]		=							['TimmBackbone']


if TYPE_CHECKING:
   from .configuration_timm_backbone import TimmBackboneConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_timm_backbone import TimmBackbone

else:
   import sys

   UpperCAmelCase					:		Dict		=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


