





"""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:
  lowerCamelCase__						= None


lowerCamelCase__						= logging.get_logger(__name__)


lowerCamelCase__						= {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

lowerCamelCase__						= {
    """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"""
        ),
    },
}

lowerCamelCase__						= {
    """facebook/nllb-large-en-ro""": 1024,
    """facebook/nllb-200-distilled-600M""": 1024,
}

# fmt: off
lowerCamelCase__						= ["""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     (    UpperCAmelCase_ ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__				:List[str]						  =       VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__				:Optional[Any]						  =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__				:str						  =       PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__				:Tuple						  =       ['input_ids', 'attention_mask']
  SCREAMING_SNAKE_CASE__				:List[Any]						  =       NllbTokenizer

  SCREAMING_SNAKE_CASE__				:List[int]						  =       []
  SCREAMING_SNAKE_CASE__				:List[int]						  =       []

  def __init__(		self :							Any       , __a :							List[str]=None       , __a :							Optional[Any]=None       , __a :							int="<s>"       , __a :							Union[str, Any]="</s>"       , __a :							Optional[int]="</s>"       , __a :							Dict="<s>"       , __a :							Dict="<unk>"       , __a :							Tuple="<pad>"       , __a :							Any="<mask>"       , __a :							str=None       , __a :							Union[str, Any]=None       , __a :							List[Any]=None       , __a :							Optional[int]=False       , **__a :							int       , )		->					List[str]:
        _UpperCamelCase   :						Any    =							AddedToken(SCREAMING_SNAKE_CASE_       , lstrip=SCREAMING_SNAKE_CASE_       , rstrip=SCREAMING_SNAKE_CASE_						) if isinstance(SCREAMING_SNAKE_CASE_       , SCREAMING_SNAKE_CASE_						) else mask_token
        _UpperCamelCase   :						Optional[int]    =							legacy_behaviour
        super().__init__(
            vocab_file=SCREAMING_SNAKE_CASE_       , tokenizer_file=SCREAMING_SNAKE_CASE_       , bos_token=SCREAMING_SNAKE_CASE_       , eos_token=SCREAMING_SNAKE_CASE_       , sep_token=SCREAMING_SNAKE_CASE_       , cls_token=SCREAMING_SNAKE_CASE_       , unk_token=SCREAMING_SNAKE_CASE_       , pad_token=SCREAMING_SNAKE_CASE_       , mask_token=SCREAMING_SNAKE_CASE_       , src_lang=SCREAMING_SNAKE_CASE_       , tgt_lang=SCREAMING_SNAKE_CASE_       , additional_special_tokens=SCREAMING_SNAKE_CASE_       , legacy_behaviour=SCREAMING_SNAKE_CASE_       , **SCREAMING_SNAKE_CASE_       , )

        _UpperCamelCase   :						int    =							vocab_file
        _UpperCamelCase   :						Any    =							False if not self.vocab_file else True

        _UpperCamelCase   :						Union[str, Any]    =							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}						)
        _UpperCamelCase   :						Optional[Any]    =							{
            lang_code: self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_						) for lang_code in FAIRSEQ_LANGUAGE_CODES
        }

        _UpperCamelCase   :						int    =							src_lang if src_lang is not None else """eng_Latn"""
        _UpperCamelCase   :						Tuple    =							self.convert_tokens_to_ids(self._src_lang						)
        _UpperCamelCase   :						Dict    =							tgt_lang
        self.set_src_lang_special_tokens(self._src_lang						)

  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							int						)		->					str:
        return self._src_lang

  @src_lang.setter
  def  __SCREAMING_SNAKE_CASE					(		self :							Union[str, Any]       , __a :							Tuple						)		->					List[str]:
        _UpperCamelCase   :						int    =							new_src_lang
        self.set_src_lang_special_tokens(self._src_lang						)

  def  __SCREAMING_SNAKE_CASE					(		self :							Tuple       , __a :							List[Any]       , __a :							Any = None						)		->					List[Any]:




        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  __SCREAMING_SNAKE_CASE					(		self :							List[Any]       , __a :							Dict       , __a :							Any = None						)		->					Dict:
        _UpperCamelCase   :						Optional[int]    =							[self.sep_token_id]
        _UpperCamelCase   :						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  __SCREAMING_SNAKE_CASE					(		self :							List[Any]       , __a :							List[Any]       , __a :							List[str]       , __a :							Optional[int]       , __a :							int       , **__a :							Optional[int]						)		->					Any:




        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   :						Tuple    =							src_lang
        _UpperCamelCase   :						Any    =							self(SCREAMING_SNAKE_CASE_       , add_special_tokens=SCREAMING_SNAKE_CASE_       , return_tensors=SCREAMING_SNAKE_CASE_       , **SCREAMING_SNAKE_CASE_						)
        _UpperCamelCase   :						str    =							self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_						)
        _UpperCamelCase   :						Optional[int]    =							tgt_lang_id
        return inputs

  def  __SCREAMING_SNAKE_CASE					(		self :							str       , __a :							Optional[Any]       , __a :							Optional[Any] = "eng_Latn"       , __a :							Optional[Any] = None       , __a :							str = "fra_Latn"       , **__a :							str       , )		->					Any:
        _UpperCamelCase   :						Optional[int]    =							src_lang
        _UpperCamelCase   :						List[str]    =							tgt_lang
        return super().prepare_seqaseq_batch(SCREAMING_SNAKE_CASE_       , SCREAMING_SNAKE_CASE_       , **SCREAMING_SNAKE_CASE_						)

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

  def  __SCREAMING_SNAKE_CASE					(		self :							Dict						)		->					Optional[int]:
        return self.set_tgt_lang_special_tokens(self.tgt_lang						)

  def  __SCREAMING_SNAKE_CASE					(		self :							int       , __a :							Any						)		->					Union[str, Any]:
        _UpperCamelCase   :						Optional[int]    =							self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_						)

        if self.legacy_behaviour:
              _UpperCamelCase   :						Optional[Any]    =							[]
              _UpperCamelCase   :						Union[str, Any]    =							[self.eos_token_id, self.cur_lang_code]
        else:
              _UpperCamelCase   :						Optional[Any]    =							[self.cur_lang_code]
              _UpperCamelCase   :						Tuple    =							[self.eos_token_id]

        _UpperCamelCase   :						int    =							self.convert_ids_to_tokens(self.prefix_tokens						)
        _UpperCamelCase   :						Optional[Any]    =							self.convert_ids_to_tokens(self.suffix_tokens						)

        _UpperCamelCase   :						str    =							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  __SCREAMING_SNAKE_CASE					(		self :							int       , __a :							List[Any]						)		->					Optional[Any]:
        _UpperCamelCase   :						int    =							self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_						)
        if self.legacy_behaviour:
              _UpperCamelCase   :						Dict    =							[]
              _UpperCamelCase   :						Dict    =							[self.eos_token_id, self.cur_lang_code]
        else:
              _UpperCamelCase   :						Tuple    =							[self.cur_lang_code]
              _UpperCamelCase   :						str    =							[self.eos_token_id]

        _UpperCamelCase   :						Dict    =							self.convert_ids_to_tokens(self.prefix_tokens						)
        _UpperCamelCase   :						int    =							self.convert_ids_to_tokens(self.suffix_tokens						)

        _UpperCamelCase   :						Optional[Any]    =							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  __SCREAMING_SNAKE_CASE					(		self :							Optional[int]       , __a :							Optional[Any]       , __a :							List[Any] = None						)		->					Optional[int]:




        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(SCREAMING_SNAKE_CASE_						):
              logger.error(F'''Vocabulary path ({save_directory}) should be a directory.'''						)
              return
        _UpperCamelCase   :						List[Any]    =							os.path.join(
            SCREAMING_SNAKE_CASE_       , (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)

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

        return (out_vocab_file,)


# 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


lowerCamelCase__     :		Tuple        = {
    """configuration_mgp_str""": ["""MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MgpstrConfig"""],
    """processing_mgp_str""": ["""MgpstrProcessor"""],
    """tokenization_mgp_str""": ["""MgpstrTokenizer"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__     :		Optional[int]        = [
         """MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """MgpstrModel""",
         """MgpstrPreTrainedModel""",
         """MgpstrForSceneTextRecognition""",
     ]

if TYPE_CHECKING:
     from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
     from .processing_mgp_str import MgpstrProcessor
     from .tokenization_mgp_str import MgpstrTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_mgp_str import (
              MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
              MgpstrForSceneTextRecognition,
              MgpstrModel,
              MgpstrPreTrainedModel,
          )
else:
     import sys

     lowerCamelCase__     :		List[Any]        = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






