
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__     :		str        = None


lowerCamelCase__     :		int        = logging.get_logger(__name__)


lowerCamelCase__     :		Optional[int]        = {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

lowerCamelCase__     :		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"""
        ),
    },
}

lowerCamelCase__     :		Union[str, Any]        = {
    """facebook/nllb-large-en-ro""": 1_0_2_4,
    """facebook/nllb-200-distilled-600M""": 1_0_2_4,
}

# fmt: off
lowerCamelCase__     :		Tuple        = ["""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    _snake_case (						UpperCAmelCase_				):
 __lowerCAmelCase	:  List[str]	   =      VOCAB_FILES_NAMES
 __lowerCAmelCase	:  Optional[Any]	   =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCAmelCase	:  str	   =      PRETRAINED_VOCAB_FILES_MAP
 __lowerCAmelCase	:  Tuple	   =      ['input_ids', 'attention_mask']
 __lowerCAmelCase	:  List[Any]	   =      NllbTokenizer

 __lowerCAmelCase	:  List[int]	   =      []
 __lowerCAmelCase	:  List[int]	   =      []


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


   '''simple docstring'''




   lowercase__	: Any     		=   AddedToken(SCREAMING_SNAKE_CASE_       ,	lstrip=SCREAMING_SNAKE_CASE_       ,	rstrip=SCREAMING_SNAKE_CASE_) if isinstance(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_) else mask_token
   lowercase__	: 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_       ,	)

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

   lowercase__	: 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})
   lowercase__	: Optional[Any]     		=   {
       lang_code: self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_) for lang_code in FAIRSEQ_LANGUAGE_CODES
   }

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


 @property
 def   lowercase__  (       self):


   '''simple docstring'''




   return self._src_lang


 @src_lang.setter
 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__	: int     		=   new_src_lang
   self.set_src_lang_special_tokens(self._src_lang)


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_ = None):


   '''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       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   lowercase__	: Optional[int]     		=   [self.sep_token_id]
   lowercase__	: 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   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_):


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


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_ = "eng_Latn"       ,	SCREAMING_SNAKE_CASE_ = None       ,	SCREAMING_SNAKE_CASE_ = "fra_Latn"       ,	**SCREAMING_SNAKE_CASE_       ,	):


   '''simple docstring'''




   lowercase__	: Optional[int]     		=   src_lang
   lowercase__	: List[str]     		=   tgt_lang
   return super().prepare_seqaseq_batch(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_)


 def   lowercase__  (       self):


   '''simple docstring'''




   return self.set_src_lang_special_tokens(self.src_lang)


 def   lowercase__  (       self):


   '''simple docstring'''




   return self.set_tgt_lang_special_tokens(self.tgt_lang)


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__	: Optional[int]     		=   self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_)

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

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

   lowercase__	: 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   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__	: int     		=   self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_)
   if self.legacy_behaviour:
     lowercase__	: Dict     		=   []
     lowercase__	: Dict     		=   [self.eos_token_id, self.cur_lang_code]
   else:
     lowercase__	: Tuple     		=   [self.cur_lang_code]
     lowercase__	: str     		=   [self.eos_token_id]

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

   lowercase__	: 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   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_ = None):


   '''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(SCREAMING_SNAKE_CASE_):
     logger.error(f'Vocabulary path ({save_directory}) should be a directory.')
     return
   lowercase__	: 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,)










from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_lowerCAmelCase:						Optional[Any]   				=       {
    'configuration_swiftformer': [
        'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SwiftFormerConfig',
        'SwiftFormerOnnxConfig',
    ]
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowerCAmelCase:						List[str]   				=       [
	    'SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'SwiftFormerForImageClassification',
	    'SwiftFormerModel',
	    'SwiftFormerPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_swiftformer import (
	    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    SwiftFormerConfig,
	    SwiftFormerOnnxConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_swiftformer import (
		    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    SwiftFormerForImageClassification,
		    SwiftFormerModel,
		    SwiftFormerPreTrainedModel,
		)

else:
	import sys

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

