


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:
       lowercase_	   =     None


lowercase_	   =     logging.get_logger(__name__)


lowercase_	   =     {'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

lowercase_	   =     {
    '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'
        ),
    },
}

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

# fmt: off
lowercase_	   =     ['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_ (	__UpperCamelCase   ):




      '''simple docstring'''


      __snake_case 	=       VOCAB_FILES_NAMES
      __snake_case 	=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __snake_case 	=       PRETRAINED_VOCAB_FILES_MAP
      __snake_case 	=       ["""input_ids""", """attention_mask"""]
      __snake_case 	=       NllbTokenizer

      __snake_case 	=       []
      __snake_case 	=       []




      def __init__(    self:	Optional[Any]						,				a:	List[str]=None						,				a:	Tuple=None						,				a:	List[str]="<s>"						,				a:	str="</s>"						,				a:	Any="</s>"						,				a:	Optional[int]="<s>"						,				a:	Any="<unk>"						,				a:	Tuple="<pad>"						,				a:	str="<mask>"						,				a:	Any=None						,				a:	Optional[Any]=None						,				a:	Union[str, Any]=None						,				a:	Optional[Any]=False						,				**a:	Dict						,				):
       # Mask token behave like a normal word, i.e. include the space before it
       __lowerCamelCase		:							List[str]		 =						AddedToken(a						,				lstrip=a						,				rstrip=a    ) if isinstance(a						,				a    ) else mask_token
       __lowerCamelCase		:							List[str]		 =						legacy_behaviour
       super().__init__(
           vocab_file=a						,				tokenizer_file=a						,				bos_token=a						,				eos_token=a						,				sep_token=a						,				cls_token=a						,				unk_token=a						,				pad_token=a						,				mask_token=a						,				src_lang=a						,				tgt_lang=a						,				additional_special_tokens=a						,				legacy_behaviour=a						,				**a						,				)

       __lowerCamelCase		:							Union[str, Any]		 =						vocab_file
       __lowerCamelCase		:							Tuple		 =						False if not self.vocab_file else True

       __lowerCamelCase		:							Optional[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}    )
       __lowerCamelCase		:							Any		 =						{
           lang_code: self.convert_tokens_to_ids(a    ) for lang_code in FAIRSEQ_LANGUAGE_CODES
       }

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




      @property
      def 					_snake_case     (    self:	Optional[int]    ):
       return self._src_lang




      @src_lang.setter
      def 					_snake_case     (    self:	Union[str, Any]						,				a:	str    ):
       __lowerCamelCase		:							Optional[int]		 =						new_src_lang
       self.set_src_lang_special_tokens(self._src_lang    )




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




      def 					_snake_case     (    self:	Optional[int]						,				a:	List[str]						,				a:	str = "eng_Latn"						,				a:	Optional[List[str]] = None						,				a:	str = "fra_Latn"						,				**a:	Union[str, Any]						,				):
       __lowerCamelCase		:							Union[str, Any]		 =						src_lang
       __lowerCamelCase		:							List[Any]		 =						tgt_lang
       return super().prepare_seqaseq_batch(a						,				a						,				**a    )




      def 					_snake_case     (    self:	List[str]    ):
       return self.set_src_lang_special_tokens(self.src_lang    )




      def 					_snake_case     (    self:	Union[str, Any]    ):
       return self.set_tgt_lang_special_tokens(self.tgt_lang    )




      def 					_snake_case     (    self:	Dict						,				a:	Optional[int]    ):
       __lowerCamelCase		:							Any		 =						self.convert_tokens_to_ids(a    )

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

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

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

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

       __lowerCamelCase		:							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 					_snake_case     (    self:	Any						,				a:	str						,				a:	Optional[str] = None    ):
       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(a    ):
        logger.error(F'Vocabulary path ({save_directory}) should be a directory.'    )
        return
       __lowerCamelCase		:							Optional[Any]		 =						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    ):
        copyfile(self.vocab_file						,				a    )

       return (out_vocab_file,)





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase_	   =     {'configuration_mbart': ['MBART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MBartConfig', 'MBartOnnxConfig']}

try:
       if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     ['MBartTokenizer']

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     ['MBartTokenizerFast']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     [
           'MBART_PRETRAINED_MODEL_ARCHIVE_LIST',
           'MBartForCausalLM',
           'MBartForConditionalGeneration',
           'MBartForQuestionAnswering',
           'MBartForSequenceClassification',
           'MBartModel',
           'MBartPreTrainedModel',
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     [
           'TFMBartForConditionalGeneration',
           'TFMBartModel',
           'TFMBartPreTrainedModel',
       ]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_	   =     [
           'FlaxMBartForConditionalGeneration',
           'FlaxMBartForQuestionAnswering',
           'FlaxMBartForSequenceClassification',
           'FlaxMBartModel',
           'FlaxMBartPreTrainedModel',
       ]


if TYPE_CHECKING:
       from .configuration_mbart import MBART_PRETRAINED_CONFIG_ARCHIVE_MAP, MBartConfig, MBartOnnxConfig

       try:
              if not is_sentencepiece_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_mbart import MBartTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_mbart_fast import MBartTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_mbart import (
                  MBART_PRETRAINED_MODEL_ARCHIVE_LIST,
                  MBartForCausalLM,
                  MBartForConditionalGeneration,
                  MBartForQuestionAnswering,
                  MBartForSequenceClassification,
                  MBartModel,
                  MBartPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_mbart import TFMBartForConditionalGeneration, TFMBartModel, TFMBartPreTrainedModel

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_mbart import (
                  FlaxMBartForConditionalGeneration,
                  FlaxMBartForQuestionAnswering,
                  FlaxMBartForSequenceClassification,
                  FlaxMBartModel,
                  FlaxMBartPreTrainedModel,
              )

else:
       import sys

       lowercase_	   =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

