

'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


_lowerCamelCase      					=     logging.get_logger(__name__)

_lowerCamelCase      					=     '''▁'''

_lowerCamelCase      					=     {'''vocab_file''': '''sentencepiece.bpe.model'''}

_lowerCamelCase      					=     {
    '''vocab_file''': {
        '''facebook/nllb-200-distilled-600M''': (
            '''https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model'''
        ),
    }
}

_lowerCamelCase      					=     {
    '''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 					_snake_case		(_lowercase):
			__A  :	Optional[Any]        =VOCAB_FILES_NAMES
			__A  :	List[str]        =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__A  :	Union[str, Any]        =PRETRAINED_VOCAB_FILES_MAP
			__A  :	str        =["input_ids", "attention_mask"]

			__A  :	Dict        =[]
			__A  :	List[str]        =[]






			def __init__(  self			,_snake_case			,_snake_case="<s>"			,_snake_case="</s>"			,_snake_case="</s>"			,_snake_case="<s>"			,_snake_case="<unk>"			,_snake_case="<pad>"			,_snake_case="<mask>"			,_snake_case=None			,_snake_case=None			,_snake_case=None			,_snake_case = None			,_snake_case=None			,_snake_case=False			,**_snake_case			,):
				UpperCAmelCase_     :      str						=  AddedToken(_snake_case			,lstrip=_snake_case			,rstrip=_snake_case     ) if isinstance(_snake_case			,_snake_case     ) else mask_token

				UpperCAmelCase_     :      Optional[int]						=  {} if sp_model_kwargs is None else sp_model_kwargs
				UpperCAmelCase_     :      Optional[int]						=  legacy_behaviour

				super().__init__(
				    bos_token=_snake_case			,eos_token=_snake_case			,unk_token=_snake_case			,sep_token=_snake_case			,cls_token=_snake_case			,pad_token=_snake_case			,mask_token=_snake_case			,tokenizer_file=_snake_case			,src_lang=_snake_case			,tgt_lang=_snake_case			,additional_special_tokens=_snake_case			,sp_model_kwargs=self.sp_model_kwargs			,legacy_behaviour=_snake_case			,**_snake_case			,)

				UpperCAmelCase_     :      Optional[int]						=  spm.SentencePieceProcessor(**self.sp_model_kwargs     )
				self.sp_model.Load(str(_snake_case     )     )
				UpperCAmelCase_     :      int						=  vocab_file
				# Original fairseq vocab and spm vocab must be "aligned":
				# Vocab    |    0    |    1    |   2    |    3    |  4   |  5   |  6   |   7  |   8  |  9
				# -------- | ------- | ------- | ------ | ------- | ---- | ---- | ---- | ---- | ---- | ----
				# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
				# spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

				# Mimic fairseq token-to-id alignment for the first 4 token
				UpperCAmelCase_     :      Any						=  {"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

				# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
				UpperCAmelCase_     :      str						=  1

				UpperCAmelCase_     :      Union[str, Any]						=  len(self.sp_model     )
				UpperCAmelCase_     :      Optional[Any]						=  {
				    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(_snake_case     )
				}
				UpperCAmelCase_     :      str						=  {v: k for k, v in self.lang_code_to_id.items()}
				UpperCAmelCase_     :      Dict						=  len(self.sp_model     ) + len(self.lang_code_to_id     ) + self.fairseq_offset

				self.fairseq_tokens_to_ids.update(self.lang_code_to_id     )
				UpperCAmelCase_     :      Tuple						=  {v: k for k, v in self.fairseq_tokens_to_ids.items()}
				UpperCAmelCase_     :      Any						=  list(self.lang_code_to_id.keys()     )

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

				UpperCAmelCase_     :      Any						=  src_lang if src_lang is not None else "eng_Latn"
				UpperCAmelCase_     :      List[str]						=  self.lang_code_to_id[self._src_lang]
				UpperCAmelCase_     :      List[str]						=  tgt_lang
				self.set_src_lang_special_tokens(self._src_lang     )






			def __getstate__(  self     ):
				UpperCAmelCase_     :      Union[str, Any]						=  self.__dict__.copy()
				UpperCAmelCase_     :      Optional[int]						=  None
				UpperCAmelCase_     :      int						=  self.sp_model.serialized_model_proto()
				return state






			def __setstate__(  self			,_snake_case     ):
				UpperCAmelCase_     :      List[Any]						=  d

				# for backward compatibility
				if not hasattr(self			,"sp_model_kwargs"     ):
					UpperCAmelCase_     :      List[str]						=  {}

				UpperCAmelCase_     :      List[str]						=  spm.SentencePieceProcessor(**self.sp_model_kwargs     )
				self.sp_model.LoadFromSerializedProto(self.sp_model_proto     )






			@property
			def 		UpperCamelCase__							(  self     ):
				return len(self.sp_model     ) + len(self.lang_code_to_id     ) + self.fairseq_offset + 1  # Plus 1 for the mask token






			@property
			def 		UpperCamelCase__							(  self     ):
				return self._src_lang






			@src_lang.setter
			def 		UpperCamelCase__							(  self			,_snake_case     ):
				UpperCAmelCase_     :      Optional[Any]						=  new_src_lang
				self.set_src_lang_special_tokens(self._src_lang     )






			def 		UpperCamelCase__							(  self			,_snake_case			,_snake_case = None			,_snake_case = False     ):

				if already_has_special_tokens:
					return super().get_special_tokens_mask(
					    token_ids_a=_snake_case			,token_ids_a=_snake_case			,already_has_special_tokens=_snake_case     )

				UpperCAmelCase_     :      Dict						=  [1] * len(self.prefix_tokens     )
				UpperCAmelCase_     :      Union[str, Any]						=  [1] * len(self.suffix_tokens     )
				if token_ids_a is None:
					return prefix_ones + ([0] * len(_snake_case     )) + suffix_ones
				return prefix_ones + ([0] * len(_snake_case     )) + ([0] * len(_snake_case     )) + suffix_ones






			def 		UpperCamelCase__							(  self			,_snake_case			,_snake_case = 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 		UpperCamelCase__							(  self			,_snake_case			,_snake_case = None     ):
				UpperCAmelCase_     :      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 		UpperCamelCase__							(  self			,_snake_case			,_snake_case			,_snake_case			,_snake_case			,**_snake_case     ):
				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_     :      Optional[int]						=  src_lang
				UpperCAmelCase_     :      int						=  self(_snake_case			,add_special_tokens=_snake_case			,return_tensors=_snake_case			,**_snake_case     )
				UpperCAmelCase_     :      Dict						=  self.convert_tokens_to_ids(_snake_case     )
				UpperCAmelCase_     :      List[Any]						=  tgt_lang_id
				return inputs






			def 		UpperCamelCase__							(  self     ):
				UpperCAmelCase_     :      int						=  {self.convert_ids_to_tokens(_snake_case     ): i for i in range(self.vocab_size     )}
				vocab.update(self.added_tokens_encoder     )
				return vocab






			def 		UpperCamelCase__							(  self			,_snake_case     ):
				return self.sp_model.encode(_snake_case			,out_type=_snake_case     )






			def 		UpperCamelCase__							(  self			,_snake_case     ):
				if token in self.fairseq_tokens_to_ids:
					return self.fairseq_tokens_to_ids[token]
				UpperCAmelCase_     :      str						=  self.sp_model.PieceToId(_snake_case     )

				# Need to return unknown token if the SP model returned 0
				return spm_id + self.fairseq_offset if spm_id else self.unk_token_id






			def 		UpperCamelCase__							(  self			,_snake_case     ):
				if index in self.fairseq_ids_to_tokens:
					return self.fairseq_ids_to_tokens[index]
				return self.sp_model.IdToPiece(index - self.fairseq_offset     )






			def 		UpperCamelCase__							(  self			,_snake_case     ):
				UpperCAmelCase_     :      Dict						=  "".join(_snake_case     ).replace(_snake_case			," "     ).strip()
				return out_string






			def 		UpperCamelCase__							(  self			,_snake_case			,_snake_case = None     ):
				if not os.path.isdir(_snake_case     ):
					logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''     )
					return
				UpperCAmelCase_     :      Any						=  os.path.join(
				    _snake_case			,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]     )

				if os.path.abspath(self.vocab_file     ) != os.path.abspath(_snake_case     ) and os.path.isfile(self.vocab_file     ):
					copyfile(self.vocab_file			,_snake_case     )
				elif not os.path.isfile(self.vocab_file     ):
					with open(_snake_case			,"wb"     ) as fi:
						UpperCAmelCase_     :      Any						=  self.sp_model.serialized_model_proto()
						fi.write(_snake_case     )

				return (out_vocab_file,)






			def 		UpperCamelCase__							(  self			,_snake_case			,_snake_case = "eng_Latn"			,_snake_case = None			,_snake_case = "fra_Latn"			,**_snake_case			,):
				UpperCAmelCase_     :      Optional[Any]						=  src_lang
				UpperCAmelCase_     :      List[Any]						=  tgt_lang
				return super().prepare_seqaseq_batch(_snake_case			,_snake_case			,**_snake_case     )






			def 		UpperCamelCase__							(  self     ):
				return self.set_src_lang_special_tokens(self.src_lang     )






			def 		UpperCamelCase__							(  self     ):
				return self.set_tgt_lang_special_tokens(self.tgt_lang     )






			def 		UpperCamelCase__							(  self			,_snake_case     ):
				UpperCAmelCase_     :      List[str]						=  self.lang_code_to_id[src_lang]
				if self.legacy_behaviour:
					UpperCAmelCase_     :      Tuple						=  []
					UpperCAmelCase_     :      Tuple						=  [self.eos_token_id, self.cur_lang_code]
				else:
					UpperCAmelCase_     :      Optional[int]						=  [self.cur_lang_code]
					UpperCAmelCase_     :      Optional[Any]						=  [self.eos_token_id]






			def 		UpperCamelCase__							(  self			,_snake_case     ):
				UpperCAmelCase_     :      Tuple						=  self.lang_code_to_id[lang]
				if self.legacy_behaviour:
					UpperCAmelCase_     :      int						=  []
					UpperCAmelCase_     :      Optional[Any]						=  [self.eos_token_id, self.cur_lang_code]
				else:
					UpperCAmelCase_     :      Optional[Any]						=  [self.cur_lang_code]
					UpperCAmelCase_     :      Optional[int]						=  [self.eos_token_id]






"""simple docstring"""





from typing import TYPE_CHECKING

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


UpperCamelCase_       :    Any						      =			{'''configuration_van''': ['''VAN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VanConfig''']}


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCamelCase_       :    str						      =			[
		    '''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_       :    Optional[Any]						      =			_LazyModule(__name__, globals()['''__file__'''], _import_structure)




