






from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase__      			=						{'''configuration_van''': ['''VAN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VanConfig''']}


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCAmelCase__      			=						[
			    '''VAN_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''VanForImageClassification''',
			    '''VanModel''',
			    '''VanPreTrainedModel''',
			]

if TYPE_CHECKING:
			from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_van import (
						    VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    VanForImageClassification,
						    VanModel,
						    VanPreTrainedModel,
						)

else:
			import sys

			UpperCAmelCase__      			=						_LazyModule(__name__, globals()['''__file__'''], _import_structure)













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__      			=						None


UpperCAmelCase__      			=						logging.get_logger(__name__)


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

UpperCAmelCase__      			=						{
    '''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__      			=						{
    '''facebook/nllb-large-en-ro''': 1024,
    '''facebook/nllb-200-distilled-600M''': 1024,
}

# fmt: off
UpperCAmelCase__      			=						['''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      ):

						"""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] ,					__UpperCAmelCase:					Union[str, Any]=None ,					__UpperCAmelCase:					List[Any]=None ,					__UpperCAmelCase:					Union[str, Any]="<s>" ,					__UpperCAmelCase:					Tuple="</s>" ,					__UpperCAmelCase:					Optional[Any]="</s>" ,					__UpperCAmelCase:					Tuple="<s>" ,					__UpperCAmelCase:					Optional[Any]="<unk>" ,					__UpperCAmelCase:					Dict="<pad>" ,					__UpperCAmelCase:					Any="<mask>" ,					__UpperCAmelCase:					Dict=None ,					__UpperCAmelCase:					Optional[Any]=None ,					__UpperCAmelCase:					List[str]=None ,					__UpperCAmelCase:					List[str]=False ,					**__UpperCAmelCase:					Tuple ,					)    ->     Tuple:




											'''simple docstring'''



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

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

											__a					:						Dict      =					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}   )
											__a					:						Optional[Any]      =					{
											    lang_code: self.convert_tokens_to_ids(__UpperCAmelCase   ) for lang_code in FAIRSEQ_LANGUAGE_CODES
											}

											__a					:						Dict      =					src_lang if src_lang is not None else "eng_Latn"
											__a					:						str      =					self.convert_tokens_to_ids(self._src_lang   )
											__a					:						Any      =					tgt_lang
											self.set_src_lang_special_tokens(self._src_lang   )



						@property
						def        UpperCAmelCase__					(self:					List[str]   )    ->     str:




											'''simple docstring'''



											return self._src_lang



						@src_lang.setter
						def        UpperCAmelCase__					(self:					List[str] ,					__UpperCAmelCase:					str   )    ->     None:




											'''simple docstring'''



											__a					:						Dict      =					new_src_lang
											self.set_src_lang_special_tokens(self._src_lang   )



						def        UpperCAmelCase__					(self:					Any ,					__UpperCAmelCase:					List[int] ,					__UpperCAmelCase:					Optional[List[int]] = 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:					List[str] ,					__UpperCAmelCase:					List[int] ,					__UpperCAmelCase:					Optional[List[int]] = None   )    ->     List[int]:




											'''simple docstring'''



											__a					:						int      =					[self.sep_token_id]
											__a					:						str      =					[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:					str ,					__UpperCAmelCase:					Dict ,					__UpperCAmelCase:					str ,					__UpperCAmelCase:					Optional[str] ,					__UpperCAmelCase:					Optional[str] ,					**__UpperCAmelCase:					Optional[int]   )    ->     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"   )
											__a					:						Tuple      =					src_lang
											__a					:						Optional[Any]      =					self(__UpperCAmelCase ,					add_special_tokens=__UpperCAmelCase ,					return_tensors=__UpperCAmelCase ,					**__UpperCAmelCase   )
											__a					:						List[Any]      =					self.convert_tokens_to_ids(__UpperCAmelCase   )
											__a					:						List[Any]      =					tgt_lang_id
											return inputs



						def        UpperCAmelCase__					(self:					Optional[int] ,					__UpperCAmelCase:					List[str] ,					__UpperCAmelCase:					str = "eng_Latn" ,					__UpperCAmelCase:					Optional[List[str]] = None ,					__UpperCAmelCase:					str = "fra_Latn" ,					**__UpperCAmelCase:					Dict ,					)    ->     BatchEncoding:




											'''simple docstring'''



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



						def        UpperCAmelCase__					(self:					List[Any]   )    ->     int:




											'''simple docstring'''



											return self.set_src_lang_special_tokens(self.src_lang   )



						def        UpperCAmelCase__					(self:					Union[str, Any]   )    ->     Union[str, Any]:




											'''simple docstring'''



											return self.set_tgt_lang_special_tokens(self.tgt_lang   )



						def        UpperCAmelCase__					(self:					Optional[int] ,					__UpperCAmelCase:					Union[str, Any]   )    ->     None:




											'''simple docstring'''



											__a					:						Optional[Any]      =					self.convert_tokens_to_ids(__UpperCAmelCase   )

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

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

											__a					:						int      =					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:					str ,					__UpperCAmelCase:					str   )    ->     None:




											'''simple docstring'''



											__a					:						List[Any]      =					self.convert_tokens_to_ids(__UpperCAmelCase   )
											if self.legacy_behaviour:
																__a					:						Any      =					[]
																__a					:						Union[str, Any]      =					[self.eos_token_id, self.cur_lang_code]
											else:
																__a					:						Union[str, Any]      =					[self.cur_lang_code]
																__a					:						List[str]      =					[self.eos_token_id]

											__a					:						str      =					self.convert_ids_to_tokens(self.prefix_tokens   )
											__a					:						str      =					self.convert_ids_to_tokens(self.suffix_tokens   )

											__a					:						int      =					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:					str ,					__UpperCAmelCase:					str ,					__UpperCAmelCase:					Optional[str] = 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(__UpperCAmelCase   ):
																logger.error(f'Vocabulary path ({save_directory}) should be a directory.'   )
																return
											__a					:						Tuple      =					os.path.join(
											    __UpperCAmelCase ,					(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]   )

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

											return (out_vocab_file,)





