




"""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


a							      =     logging.get_logger(__name__)

a							      =     '''▁'''

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

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

a							      =     {
    '''facebook/nllb-200-distilled-600M''': 1_024,
}

# fmt: off
a							      =     ['''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 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	List[Any]     =      VOCAB_FILES_NAMES
 UpperCAmelCase       :	Dict     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCAmelCase       :	Any     =      PRETRAINED_VOCAB_FILES_MAP
 UpperCAmelCase       :	Optional[Any]     =      ['''input_ids''', '''attention_mask''']

 UpperCAmelCase       :	List[int]     =      []
 UpperCAmelCase       :	List[int]     =      []

 def __init__(					self			:			Optional[Any]       ,				_UpperCAmelCase			:			Optional[Any]       ,				_UpperCAmelCase			:			int="<s>"       ,				_UpperCAmelCase			:			Union[str, Any]="</s>"       ,				_UpperCAmelCase			:			Any="</s>"       ,				_UpperCAmelCase			:			str="<s>"       ,				_UpperCAmelCase			:			int="<unk>"       ,				_UpperCAmelCase			:			Optional[Any]="<pad>"       ,				_UpperCAmelCase			:			Dict="<mask>"       ,				_UpperCAmelCase			:			Optional[Any]=None       ,				_UpperCAmelCase			:			List[Any]=None       ,				_UpperCAmelCase			:			Dict=None       ,				_UpperCAmelCase			:			Optional[Dict[str, Any]] = None       ,				_UpperCAmelCase			:			Any=None       ,				_UpperCAmelCase			:			Tuple=False       ,				**_UpperCAmelCase			:			Tuple       ,				):
       # Mask token behave like a normal word, i.e. include the space before it
       _A     =  AddedToken(_UpperCAmelCase       ,				lstrip=_UpperCAmelCase       ,				rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase       ,				_UpperCAmelCase						) else mask_token

       _A     =  {} if sp_model_kwargs is None else sp_model_kwargs
       _A     =  legacy_behaviour

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

       _A     =  spm.SentencePieceProcessor(**self.sp_model_kwargs						)
       self.sp_model.Load(str(_UpperCAmelCase						)						)
       _A     =  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
       _A     =  {'<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
       _A     =  1

       _A     =  len(self.sp_model						)
       _A     =  {
           code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(_UpperCAmelCase						)
       }
       _A     =  {v: k for k, v in self.lang_code_to_id.items()}
       _A     =  len(self.sp_model						) + len(self.lang_code_to_id						) + self.fairseq_offset

       self.fairseq_tokens_to_ids.update(self.lang_code_to_id						)
       _A     =  {v: k for k, v in self.fairseq_tokens_to_ids.items()}
       _A     =  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]						)

       _A     =  src_lang if src_lang is not None else 'eng_Latn'
       _A     =  self.lang_code_to_id[self._src_lang]
       _A     =  tgt_lang
       self.set_src_lang_special_tokens(self._src_lang						)

 def __getstate__(					self			:			List[Any]						):
       _A     =  self.__dict__.copy()
       _A     =  None
       _A     =  self.sp_model.serialized_model_proto()
       return state

 def __setstate__(					self			:			Optional[Any]       ,				_UpperCAmelCase			:			Union[str, Any]						):
       _A     =  d

       # for backward compatibility
       if not hasattr(self       ,				'sp_model_kwargs'						):
             _A     =  {}

       _A     =  spm.SentencePieceProcessor(**self.sp_model_kwargs						)
       self.sp_model.LoadFromSerializedProto(self.sp_model_proto						)

 @property
 def      lowerCAmelCase_				(					self			:			Optional[int]						):
       return len(self.sp_model						) + len(self.lang_code_to_id						) + self.fairseq_offset + 1  # Plus 1 for the mask token

 @property
 def      lowerCAmelCase_				(					self			:			Union[str, Any]						):
       return self._src_lang

 @src_lang.setter
 def      lowerCAmelCase_				(					self			:			List[str]       ,				_UpperCAmelCase			:			str						):
       _A     =  new_src_lang
       self.set_src_lang_special_tokens(self._src_lang						)

 def      lowerCAmelCase_				(					self			:			List[Any]       ,				_UpperCAmelCase			:			List[int]       ,				_UpperCAmelCase			:			Optional[List[int]] = None       ,				_UpperCAmelCase			:			bool = False						):

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

       _A     =  [1] * len(self.prefix_tokens						)
       _A     =  [1] * len(self.suffix_tokens						)
       if token_ids_a is None:
             return prefix_ones + ([0] * len(_UpperCAmelCase						)) + suffix_ones
       return prefix_ones + ([0] * len(_UpperCAmelCase						)) + ([0] * len(_UpperCAmelCase						)) + suffix_ones

 def      lowerCAmelCase_				(					self			:			List[Any]       ,				_UpperCAmelCase			:			List[int]       ,				_UpperCAmelCase			:			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      lowerCAmelCase_				(					self			:			Dict       ,				_UpperCAmelCase			:			List[int]       ,				_UpperCAmelCase			:			Optional[List[int]] = None						):
       _A     =  [self.sep_token_id]
       _A     =  [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      lowerCAmelCase_				(					self			:			List[str]       ,				_UpperCAmelCase			:			List[Any]       ,				_UpperCAmelCase			:			str       ,				_UpperCAmelCase			:			Optional[str]       ,				_UpperCAmelCase			:			Optional[str]       ,				**_UpperCAmelCase			:			Union[str, 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'						)
       _A     =  src_lang
       _A     =  self(_UpperCAmelCase       ,				add_special_tokens=_UpperCAmelCase       ,				return_tensors=_UpperCAmelCase       ,				**_UpperCAmelCase						)
       _A     =  self.convert_tokens_to_ids(_UpperCAmelCase						)
       _A     =  tgt_lang_id
       return inputs

 def      lowerCAmelCase_				(					self			:			List[Any]						):
       _A     =  {self.convert_ids_to_tokens(_UpperCAmelCase						): i for i in range(self.vocab_size						)}
       vocab.update(self.added_tokens_encoder						)
       return vocab

 def      lowerCAmelCase_				(					self			:			Optional[Any]       ,				_UpperCAmelCase			:			str						):
       return self.sp_model.encode(_UpperCAmelCase       ,				out_type=_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			Union[str, Any]       ,				_UpperCAmelCase			:			Union[str, Any]						):
       if token in self.fairseq_tokens_to_ids:
             return self.fairseq_tokens_to_ids[token]
       _A     =  self.sp_model.PieceToId(_UpperCAmelCase						)

       # 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      lowerCAmelCase_				(					self			:			Union[str, Any]       ,				_UpperCAmelCase			:			List[Any]						):
       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      lowerCAmelCase_				(					self			:			Dict       ,				_UpperCAmelCase			:			Dict						):
       _A     =  ''.join(_UpperCAmelCase						).replace(_UpperCAmelCase       ,				' '						).strip()
       return out_string

 def      lowerCAmelCase_				(					self			:			Any       ,				_UpperCAmelCase			:			str       ,				_UpperCAmelCase			:			Optional[str] = None						):
       if not os.path.isdir(_UpperCAmelCase						):
             logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''						)
             return
       _A     =  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						) and os.path.isfile(self.vocab_file						):
             copyfile(self.vocab_file       ,				_UpperCAmelCase						)
       elif not os.path.isfile(self.vocab_file						):
             with open(_UpperCAmelCase       ,				'wb'						) as fi:
                   _A     =  self.sp_model.serialized_model_proto()
                   fi.write(_UpperCAmelCase						)

       return (out_vocab_file,)

 def      lowerCAmelCase_				(					self			:			Tuple       ,				_UpperCAmelCase			:			List[str]       ,				_UpperCAmelCase			:			str = "eng_Latn"       ,				_UpperCAmelCase			:			Optional[List[str]] = None       ,				_UpperCAmelCase			:			str = "fra_Latn"       ,				**_UpperCAmelCase			:			str       ,				):
       _A     =  src_lang
       _A     =  tgt_lang
       return super().prepare_seqaseq_batch(_UpperCAmelCase       ,				_UpperCAmelCase       ,				**_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			Optional[Any]						):
       return self.set_src_lang_special_tokens(self.src_lang						)

 def      lowerCAmelCase_				(					self			:			int						):
       return self.set_tgt_lang_special_tokens(self.tgt_lang						)

 def      lowerCAmelCase_				(					self			:			Optional[int]       ,				_UpperCAmelCase			:			Tuple						):
       _A     =  self.lang_code_to_id[src_lang]
       if self.legacy_behaviour:
             _A     =  []
             _A     =  [self.eos_token_id, self.cur_lang_code]
       else:
             _A     =  [self.cur_lang_code]
             _A     =  [self.eos_token_id]



 def      lowerCAmelCase_				(					self			:			List[str]       ,				_UpperCAmelCase			:			str						):
       _A     =  self.lang_code_to_id[lang]
       if self.legacy_behaviour:
             _A     =  []
             _A     =  [self.eos_token_id, self.cur_lang_code]
       else:
             _A     =  [self.cur_lang_code]
             _A     =  [self.eos_token_id]







"""simple docstring"""

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a							      =     logging.get_logger(__name__)

a							      =     {
    '''facebook/xmod-base''': '''https://huggingface.co/facebook/xmod-base/resolve/main/config.json''',
    '''facebook/xmod-large-prenorm''': '''https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json''',
    '''facebook/xmod-base-13-125k''': '''https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json''',
    '''facebook/xmod-base-30-125k''': '''https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json''',
    '''facebook/xmod-base-30-195k''': '''https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json''',
    '''facebook/xmod-base-60-125k''': '''https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json''',
    '''facebook/xmod-base-60-265k''': '''https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json''',
    '''facebook/xmod-base-75-125k''': '''https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json''',
    '''facebook/xmod-base-75-269k''': '''https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json''',
}





class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	Optional[Any]     =      '''xmod'''

 def __init__(					self			:			str       ,				_UpperCAmelCase			:			Optional[Any]=30_522       ,				_UpperCAmelCase			:			Any=768       ,				_UpperCAmelCase			:			int=12       ,				_UpperCAmelCase			:			List[str]=12       ,				_UpperCAmelCase			:			Dict=3_072       ,				_UpperCAmelCase			:			Union[str, Any]="gelu"       ,				_UpperCAmelCase			:			Optional[int]=0.1       ,				_UpperCAmelCase			:			Tuple=0.1       ,				_UpperCAmelCase			:			List[str]=512       ,				_UpperCAmelCase			:			Dict=2       ,				_UpperCAmelCase			:			Optional[int]=0.02       ,				_UpperCAmelCase			:			Any=1E-1_2       ,				_UpperCAmelCase			:			Tuple=1       ,				_UpperCAmelCase			:			int=0       ,				_UpperCAmelCase			:			List[Any]=2       ,				_UpperCAmelCase			:			List[str]="absolute"       ,				_UpperCAmelCase			:			Tuple=True       ,				_UpperCAmelCase			:			Tuple=None       ,				_UpperCAmelCase			:			int=False       ,				_UpperCAmelCase			:			Union[str, Any]=2       ,				_UpperCAmelCase			:			List[Any]=False       ,				_UpperCAmelCase			:			Dict=True       ,				_UpperCAmelCase			:			List[str]=True       ,				_UpperCAmelCase			:			Tuple=("en_XX",)       ,				_UpperCAmelCase			:			List[str]=None       ,				**_UpperCAmelCase			:			Optional[Any]       ,				):
       super().__init__(pad_token_id=_UpperCAmelCase       ,				bos_token_id=_UpperCAmelCase       ,				eos_token_id=_UpperCAmelCase       ,				**_UpperCAmelCase						)

       _A     =  vocab_size
       _A     =  hidden_size
       _A     =  num_hidden_layers
       _A     =  num_attention_heads
       _A     =  hidden_act
       _A     =  intermediate_size
       _A     =  hidden_dropout_prob
       _A     =  attention_probs_dropout_prob
       _A     =  max_position_embeddings
       _A     =  type_vocab_size
       _A     =  initializer_range
       _A     =  layer_norm_eps
       _A     =  position_embedding_type
       _A     =  use_cache
       _A     =  classifier_dropout
       _A     =  pre_norm
       _A     =  adapter_reduction_factor
       _A     =  adapter_layer_norm
       _A     =  adapter_reuse_layer_norm
       _A     =  ln_before_adapter
       _A     =  list(_UpperCAmelCase						)
       _A     =  default_language





class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''

 @property
 def      lowerCAmelCase_				(					self			:			Dict						):
       if self.task == "multiple-choice":
             _A     =  {0: 'batch', 1: 'choice', 2: 'sequence'}
       else:
             _A     =  {0: 'batch', 1: 'sequence'}
       return OrderedDict(
           [
               ('input_ids', dynamic_axis),
               ('attention_mask', dynamic_axis),
           ]						)

