




# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool


SCREAMING_SNAKE_CASE__       :      Tuple  =   {
    'Acehnese Arabic': 'ace_Arab',
    'Acehnese Latin': 'ace_Latn',
    'Mesopotamian Arabic': 'acm_Arab',
    'Ta\'izzi-Adeni Arabic': 'acq_Arab',
    'Tunisian Arabic': 'aeb_Arab',
    'Afrikaans': 'afr_Latn',
    'South Levantine Arabic': 'ajp_Arab',
    'Akan': 'aka_Latn',
    'Amharic': 'amh_Ethi',
    'North Levantine Arabic': 'apc_Arab',
    'Modern Standard Arabic': 'arb_Arab',
    'Modern Standard Arabic Romanized': 'arb_Latn',
    'Najdi Arabic': 'ars_Arab',
    'Moroccan Arabic': 'ary_Arab',
    'Egyptian Arabic': 'arz_Arab',
    'Assamese': 'asm_Beng',
    'Asturian': 'ast_Latn',
    'Awadhi': 'awa_Deva',
    'Central Aymara': 'ayr_Latn',
    'South Azerbaijani': 'azb_Arab',
    'North Azerbaijani': 'azj_Latn',
    'Bashkir': 'bak_Cyrl',
    'Bambara': 'bam_Latn',
    'Balinese': 'ban_Latn',
    'Belarusian': 'bel_Cyrl',
    'Bemba': 'bem_Latn',
    'Bengali': 'ben_Beng',
    'Bhojpuri': 'bho_Deva',
    'Banjar Arabic': 'bjn_Arab',
    'Banjar Latin': 'bjn_Latn',
    'Standard Tibetan': 'bod_Tibt',
    'Bosnian': 'bos_Latn',
    'Buginese': 'bug_Latn',
    'Bulgarian': 'bul_Cyrl',
    'Catalan': 'cat_Latn',
    'Cebuano': 'ceb_Latn',
    'Czech': 'ces_Latn',
    'Chokwe': 'cjk_Latn',
    'Central Kurdish': 'ckb_Arab',
    'Crimean Tatar': 'crh_Latn',
    'Welsh': 'cym_Latn',
    'Danish': 'dan_Latn',
    'German': 'deu_Latn',
    'Southwestern Dinka': 'dik_Latn',
    'Dyula': 'dyu_Latn',
    'Dzongkha': 'dzo_Tibt',
    'Greek': 'ell_Grek',
    'English': 'eng_Latn',
    'Esperanto': 'epo_Latn',
    'Estonian': 'est_Latn',
    'Basque': 'eus_Latn',
    'Ewe': 'ewe_Latn',
    'Faroese': 'fao_Latn',
    'Fijian': 'fij_Latn',
    'Finnish': 'fin_Latn',
    'Fon': 'fon_Latn',
    'French': 'fra_Latn',
    'Friulian': 'fur_Latn',
    'Nigerian Fulfulde': 'fuv_Latn',
    'Scottish Gaelic': 'gla_Latn',
    'Irish': 'gle_Latn',
    'Galician': 'glg_Latn',
    'Guarani': 'grn_Latn',
    'Gujarati': 'guj_Gujr',
    'Haitian Creole': 'hat_Latn',
    'Hausa': 'hau_Latn',
    'Hebrew': 'heb_Hebr',
    'Hindi': 'hin_Deva',
    'Chhattisgarhi': 'hne_Deva',
    'Croatian': 'hrv_Latn',
    'Hungarian': 'hun_Latn',
    'Armenian': 'hye_Armn',
    'Igbo': 'ibo_Latn',
    'Ilocano': 'ilo_Latn',
    'Indonesian': 'ind_Latn',
    'Icelandic': 'isl_Latn',
    'Italian': 'ita_Latn',
    'Javanese': 'jav_Latn',
    'Japanese': 'jpn_Jpan',
    'Kabyle': 'kab_Latn',
    'Jingpho': 'kac_Latn',
    'Kamba': 'kam_Latn',
    'Kannada': 'kan_Knda',
    'Kashmiri Arabic': 'kas_Arab',
    'Kashmiri Devanagari': 'kas_Deva',
    'Georgian': 'kat_Geor',
    'Central Kanuri Arabic': 'knc_Arab',
    'Central Kanuri Latin': 'knc_Latn',
    'Kazakh': 'kaz_Cyrl',
    'Kabiyè': 'kbp_Latn',
    'Kabuverdianu': 'kea_Latn',
    'Khmer': 'khm_Khmr',
    'Kikuyu': 'kik_Latn',
    'Kinyarwanda': 'kin_Latn',
    'Kyrgyz': 'kir_Cyrl',
    'Kimbundu': 'kmb_Latn',
    'Northern Kurdish': 'kmr_Latn',
    'Kikongo': 'kon_Latn',
    'Korean': 'kor_Hang',
    'Lao': 'lao_Laoo',
    'Ligurian': 'lij_Latn',
    'Limburgish': 'lim_Latn',
    'Lingala': 'lin_Latn',
    'Lithuanian': 'lit_Latn',
    'Lombard': 'lmo_Latn',
    'Latgalian': 'ltg_Latn',
    'Luxembourgish': 'ltz_Latn',
    'Luba-Kasai': 'lua_Latn',
    'Ganda': 'lug_Latn',
    'Luo': 'luo_Latn',
    'Mizo': 'lus_Latn',
    'Standard Latvian': 'lvs_Latn',
    'Magahi': 'mag_Deva',
    'Maithili': 'mai_Deva',
    'Malayalam': 'mal_Mlym',
    'Marathi': 'mar_Deva',
    'Minangkabau Arabic ': 'min_Arab',
    'Minangkabau Latin': 'min_Latn',
    'Macedonian': 'mkd_Cyrl',
    'Plateau Malagasy': 'plt_Latn',
    'Maltese': 'mlt_Latn',
    'Meitei Bengali': 'mni_Beng',
    'Halh Mongolian': 'khk_Cyrl',
    'Mossi': 'mos_Latn',
    'Maori': 'mri_Latn',
    'Burmese': 'mya_Mymr',
    'Dutch': 'nld_Latn',
    'Norwegian Nynorsk': 'nno_Latn',
    'Norwegian Bokmål': 'nob_Latn',
    'Nepali': 'npi_Deva',
    'Northern Sotho': 'nso_Latn',
    'Nuer': 'nus_Latn',
    'Nyanja': 'nya_Latn',
    'Occitan': 'oci_Latn',
    'West Central Oromo': 'gaz_Latn',
    'Odia': 'ory_Orya',
    'Pangasinan': 'pag_Latn',
    'Eastern Panjabi': 'pan_Guru',
    'Papiamento': 'pap_Latn',
    'Western Persian': 'pes_Arab',
    'Polish': 'pol_Latn',
    'Portuguese': 'por_Latn',
    'Dari': 'prs_Arab',
    'Southern Pashto': 'pbt_Arab',
    'Ayacucho Quechua': 'quy_Latn',
    'Romanian': 'ron_Latn',
    'Rundi': 'run_Latn',
    'Russian': 'rus_Cyrl',
    'Sango': 'sag_Latn',
    'Sanskrit': 'san_Deva',
    'Santali': 'sat_Olck',
    'Sicilian': 'scn_Latn',
    'Shan': 'shn_Mymr',
    'Sinhala': 'sin_Sinh',
    'Slovak': 'slk_Latn',
    'Slovenian': 'slv_Latn',
    'Samoan': 'smo_Latn',
    'Shona': 'sna_Latn',
    'Sindhi': 'snd_Arab',
    'Somali': 'som_Latn',
    'Southern Sotho': 'sot_Latn',
    'Spanish': 'spa_Latn',
    'Tosk Albanian': 'als_Latn',
    'Sardinian': 'srd_Latn',
    'Serbian': 'srp_Cyrl',
    'Swati': 'ssw_Latn',
    'Sundanese': 'sun_Latn',
    'Swedish': 'swe_Latn',
    'Swahili': 'swh_Latn',
    'Silesian': 'szl_Latn',
    'Tamil': 'tam_Taml',
    'Tatar': 'tat_Cyrl',
    'Telugu': 'tel_Telu',
    'Tajik': 'tgk_Cyrl',
    'Tagalog': 'tgl_Latn',
    'Thai': 'tha_Thai',
    'Tigrinya': 'tir_Ethi',
    'Tamasheq Latin': 'taq_Latn',
    'Tamasheq Tifinagh': 'taq_Tfng',
    'Tok Pisin': 'tpi_Latn',
    'Tswana': 'tsn_Latn',
    'Tsonga': 'tso_Latn',
    'Turkmen': 'tuk_Latn',
    'Tumbuka': 'tum_Latn',
    'Turkish': 'tur_Latn',
    'Twi': 'twi_Latn',
    'Central Atlas Tamazight': 'tzm_Tfng',
    'Uyghur': 'uig_Arab',
    'Ukrainian': 'ukr_Cyrl',
    'Umbundu': 'umb_Latn',
    'Urdu': 'urd_Arab',
    'Northern Uzbek': 'uzn_Latn',
    'Venetian': 'vec_Latn',
    'Vietnamese': 'vie_Latn',
    'Waray': 'war_Latn',
    'Wolof': 'wol_Latn',
    'Xhosa': 'xho_Latn',
    'Eastern Yiddish': 'ydd_Hebr',
    'Yoruba': 'yor_Latn',
    'Yue Chinese': 'yue_Hant',
    'Chinese Simplified': 'zho_Hans',
    'Chinese Traditional': 'zho_Hant',
    'Standard Malay': 'zsm_Latn',
    'Zulu': 'zul_Latn',
}




class 		UpperCamelCase__	(lowerCAmelCase__     ):

    '''simple docstring'''



    lowerCamelCase_      :	Union[str, Any]	     =      """facebook/nllb-200-distilled-600M"""
    lowerCamelCase_      :	List[Any]	     =      (
        """This is a tool that translates text from a language to another. It takes three inputs: `text`, which should """
        """be the text to translate, `src_lang`, which should be the language of the text to translate and `tgt_lang`, """
        """which should be the language for the desired ouput language. Both `src_lang` and `tgt_lang` are written in """
        """plain English, such as 'Romanian', or 'Albanian'. It returns the text translated in `tgt_lang`."""
    )
    lowerCamelCase_      :	Any	     =      """translator"""
    lowerCamelCase_      :	Any	     =      AutoTokenizer
    lowerCamelCase_      :	List[Any]	     =      AutoModelForSeqaSeqLM
    lowerCamelCase_      :	Optional[int]	     =      LANGUAGE_CODES

    lowerCamelCase_      :	Union[str, Any]	     =      ["""text""", """text""", """text"""]
    lowerCamelCase_      :	Dict	     =      ["""text"""]







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__     ,  UpperCamelCase__     )     ->      Union[str, Any]:
           if src_lang not in self.lang_to_code:
                  raise ValueError(F'''{src_lang} is not a supported language.'''     )
           if tgt_lang not in self.lang_to_code:
                  raise ValueError(F'''{tgt_lang} is not a supported language.'''     )
           lowerCamelCase   :      Union[str, Any]			 =					self.lang_to_code[src_lang]
           lowerCamelCase   :      List[Any]			 =					self.lang_to_code[tgt_lang]
           return self.pre_processor._build_translation_inputs(
               UpperCamelCase__     ,  return_tensors="pt"     ,  src_lang=UpperCamelCase__     ,  tgt_lang=UpperCamelCase__     )







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      Any:
           return self.model.generate(**UpperCamelCase__     )







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      Optional[Any]:
           return self.post_processor.decode(outputs[0].tolist()     ,  skip_special_tokens=UpperCamelCase__     )












import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


SCREAMING_SNAKE_CASE__       :      Optional[Any]  =   logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__       :      Tuple  =   {'vocab_file': 'spiece.model'}

SCREAMING_SNAKE_CASE__       :      int  =   {
    'vocab_file': {
        'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model',
        'xlnet-large-cased': 'https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model',
    }
}

SCREAMING_SNAKE_CASE__       :      str  =   {
    'xlnet-base-cased': None,
    'xlnet-large-cased': None,
}

# Segments (not really needed)
SCREAMING_SNAKE_CASE__       :      Dict  =   0
SCREAMING_SNAKE_CASE__       :      Tuple  =   1
SCREAMING_SNAKE_CASE__       :      Optional[int]  =   2
SCREAMING_SNAKE_CASE__       :      List[str]  =   3
SCREAMING_SNAKE_CASE__       :      Optional[int]  =   4




class 		UpperCamelCase__	(lowerCAmelCase__     ):

    '''simple docstring'''



    lowerCamelCase_      :	Dict	     =      VOCAB_FILES_NAMES
    lowerCamelCase_      :	Optional[Any]	     =      PRETRAINED_VOCAB_FILES_MAP
    lowerCamelCase_      :	Optional[int]	     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCamelCase_      :	List[str]	     =      """left"""







    def __init__(    self     ,  UpperCamelCase__     ,  UpperCamelCase__=False     ,  UpperCamelCase__=True     ,  UpperCamelCase__=False     ,  UpperCamelCase__="<s>"     ,  UpperCamelCase__="</s>"     ,  UpperCamelCase__="<unk>"     ,  UpperCamelCase__="<sep>"     ,  UpperCamelCase__="<pad>"     ,  UpperCamelCase__="<cls>"     ,  UpperCamelCase__="<mask>"     ,  UpperCamelCase__=["<eop>", "<eod>"]     ,  UpperCamelCase__ = None     ,  **UpperCamelCase__     ,  )     ->      None:
           # Mask token behave like a normal word, i.e. include the space before it
           lowerCamelCase   :      str			 =					AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__     ) if isinstance(UpperCamelCase__     ,  UpperCamelCase__     ) else mask_token

           lowerCamelCase   :      Dict			 =					{} if sp_model_kwargs is None else sp_model_kwargs

           super().__init__(
               do_lower_case=UpperCamelCase__     ,  remove_space=UpperCamelCase__     ,  keep_accents=UpperCamelCase__     ,  bos_token=UpperCamelCase__     ,  eos_token=UpperCamelCase__     ,  unk_token=UpperCamelCase__     ,  sep_token=UpperCamelCase__     ,  pad_token=UpperCamelCase__     ,  cls_token=UpperCamelCase__     ,  mask_token=UpperCamelCase__     ,  additional_special_tokens=UpperCamelCase__     ,  sp_model_kwargs=self.sp_model_kwargs     ,  **UpperCamelCase__     ,  )

           lowerCamelCase   :      Any			 =					3

           lowerCamelCase   :      Optional[Any]			 =					do_lower_case
           lowerCamelCase   :      List[Any]			 =					remove_space
           lowerCamelCase   :      str			 =					keep_accents
           lowerCamelCase   :      List[Any]			 =					vocab_file

           lowerCamelCase   :      int			 =					spm.SentencePieceProcessor(**self.sp_model_kwargs     )
           self.sp_model.Load(UpperCamelCase__     )







    @property
    def     _lowercase     (    self     )     ->      Optional[Any]:
           return len(self.sp_model     )







    def     _lowercase     (    self     )     ->      Optional[int]:
           lowerCamelCase   :      int			 =					{self.convert_ids_to_tokens(UpperCamelCase__     ): i for i in range(self.vocab_size     )}
           vocab.update(self.added_tokens_encoder     )
           return vocab







    def __getstate__(    self     )     ->      Optional[Any]:
           lowerCamelCase   :      Optional[int]			 =					self.__dict__.copy()
           lowerCamelCase   :      Union[str, Any]			 =					None
           return state







    def __setstate__(    self     ,  UpperCamelCase__     )     ->      int:
           lowerCamelCase   :      int			 =					d

           # for backward compatibility
           if not hasattr(self     ,  "sp_model_kwargs"     ):
                  lowerCamelCase   :      Any			 =					{}

           lowerCamelCase   :      Optional[int]			 =					spm.SentencePieceProcessor(**self.sp_model_kwargs     )
           self.sp_model.Load(self.vocab_file     )







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      Any:
           if self.remove_space:
                  lowerCamelCase   :      Dict			 =					" ".join(inputs.strip().split()     )
           else:
                  lowerCamelCase   :      Union[str, Any]			 =					inputs
           lowerCamelCase   :      Optional[Any]			 =					outputs.replace("``"     ,  "\""     ).replace("''"     ,  "\""     )

           if not self.keep_accents:
                  lowerCamelCase   :      Optional[int]			 =					unicodedata.normalize("NFKD"     ,  UpperCamelCase__     )
                  lowerCamelCase   :      List[Any]			 =					"".join([c for c in outputs if not unicodedata.combining(UpperCamelCase__     )]     )
           if self.do_lower_case:
                  lowerCamelCase   :      List[str]			 =					outputs.lower()

           return outputs







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      List[str]:
           lowerCamelCase   :      Optional[Any]			 =					self.preprocess_text(UpperCamelCase__     )
           lowerCamelCase   :      Dict			 =					self.sp_model.encode(UpperCamelCase__     ,  out_type=UpperCamelCase__     )
           lowerCamelCase   :      Dict			 =					[]
           for piece in pieces:
                  if len(UpperCamelCase__     ) > 1 and piece[-1] == str(","     ) and piece[-2].isdigit():
                         lowerCamelCase   :      List[Any]			 =					self.sp_model.EncodeAsPieces(piece[:-1].replace(UpperCamelCase__     ,  ""     )     )
                         if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
                                if len(cur_pieces[0]     ) == 1:
                                       lowerCamelCase   :      Union[str, Any]			 =					cur_pieces[1:]
                                else:
                                       lowerCamelCase   :      Optional[int]			 =					cur_pieces[0][1:]
                         cur_pieces.append(piece[-1]     )
                         new_pieces.extend(UpperCamelCase__     )
                  else:
                         new_pieces.append(UpperCamelCase__     )

           return new_pieces







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      int:
           return self.sp_model.PieceToId(UpperCamelCase__     )







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      Tuple:
           return self.sp_model.IdToPiece(UpperCamelCase__     )







    def     _lowercase     (    self     ,  UpperCamelCase__     )     ->      List[str]:
           lowerCamelCase   :      Union[str, Any]			 =					"".join(UpperCamelCase__     ).replace(UpperCamelCase__     ,  " "     ).strip()
           return out_string







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = False     ,  UpperCamelCase__ = None     ,  UpperCamelCase__ = True     ,  **UpperCamelCase__     ,  )     ->      str:
           lowerCamelCase   :      Optional[int]			 =					kwargs.pop("use_source_tokenizer"     ,  UpperCamelCase__     )

           lowerCamelCase   :      Optional[int]			 =					self.convert_ids_to_tokens(UpperCamelCase__     ,  skip_special_tokens=UpperCamelCase__     )

           # To avoid mixing byte-level and unicode for byte-level BPT
           # we need to build string separately for added tokens and byte-level tokens
           # cf. https://github.com/huggingface/transformers/issues/1133
           lowerCamelCase   :      Any			 =					[]
           lowerCamelCase   :      Any			 =					[]
           for token in filtered_tokens:
                  if skip_special_tokens and token in self.all_special_ids:
                         continue
                  if token in self.added_tokens_encoder:
                         if current_sub_text:
                                sub_texts.append(self.convert_tokens_to_string(UpperCamelCase__     )     )
                                lowerCamelCase   :      int			 =					[]
                         sub_texts.append(UpperCamelCase__     )
                  else:
                         current_sub_text.append(UpperCamelCase__     )
           if current_sub_text:
                  sub_texts.append(self.convert_tokens_to_string(UpperCamelCase__     )     )

           # Mimic the behavior of the Rust tokenizer:
           # By default, there are no spaces between special tokens
           lowerCamelCase   :      Union[str, Any]			 =					"".join(UpperCamelCase__     )

           lowerCamelCase   :      Tuple			 =					(
               clean_up_tokenization_spaces
               if clean_up_tokenization_spaces is not None
               else self.clean_up_tokenization_spaces
           )
           if clean_up_tokenization_spaces:
                  lowerCamelCase   :      int			 =					self.clean_up_tokenization(UpperCamelCase__     )
                  return clean_text
           else:
                  return text







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     )     ->      List[int]:
           lowerCamelCase   :      str			 =					[self.sep_token_id]
           lowerCamelCase   :      Optional[int]			 =					[self.cls_token_id]
           if token_ids_a is None:
                  return token_ids_a + sep + cls
           return token_ids_a + sep + token_ids_a + sep + cls







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     ,  UpperCamelCase__ = False     )     ->      List[int]:

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

           if token_ids_a is not None:
                  return ([0] * len(UpperCamelCase__     )) + [1] + ([0] * len(UpperCamelCase__     )) + [1, 1]
           return ([0] * len(UpperCamelCase__     )) + [1, 1]







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     )     ->      List[int]:
           lowerCamelCase   :      Any			 =					[self.sep_token_id]
           lowerCamelCase   :      List[str]			 =					[2]

           if token_ids_a is None:
                  return len(token_ids_a + sep     ) * [0] + cls_segment_id
           return len(token_ids_a + sep     ) * [0] + len(token_ids_a + sep     ) * [1] + cls_segment_id







    def     _lowercase     (    self     ,  UpperCamelCase__     ,  UpperCamelCase__ = None     )     ->      Tuple[str]:
           if not os.path.isdir(UpperCamelCase__     ):
                  logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''     )
                  return
           lowerCamelCase   :      Union[str, Any]			 =					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:
                         lowerCamelCase   :      str			 =					self.sp_model.serialized_model_proto()
                         fi.write(UpperCamelCase__     )

           return (out_vocab_file,)






