






# 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__   :      Optional[Any]				=		{
    """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     lowerCamelCase_					(   lowerCAmelCase__			):
				a__       							=	'''facebook/nllb-200-distilled-600M'''
				a__       							=	(
				    '''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`.'''
				)
				a__       							=	'''translator'''
				a__       							=	AutoTokenizer
				a__       							=	AutoModelForSeqaSeqLM
				a__       							=	LANGUAGE_CODES

				a__       							=	['''text''', '''text''', '''text''']
				a__       							=	['''text''']







				def       A						(    self							,       __lowerCAmelCase							,       __lowerCAmelCase							,       __lowerCAmelCase  ):
								"""simple docstring"""
								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.'''  )
								__magic_name__		:int   =   self.lang_to_code[src_lang]
								__magic_name__		:Dict   =   self.lang_to_code[tgt_lang]
								return self.pre_processor._build_translation_inputs(
								    __UpperCAmelCase							,       return_tensors='''pt'''							,       src_lang=__UpperCAmelCase							,       tgt_lang=__UpperCAmelCase  )







				def       A						(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								return self.model.generate(**__UpperCAmelCase  )







				def       A						(    self							,       __lowerCAmelCase  ):
								"""simple docstring"""
								return self.post_processor.decode(outputs[0].tolist()							,       skip_special_tokens=__UpperCAmelCase  )











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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging


if is_torch_available():
  import torch


if TYPE_CHECKING:
  from transformers.pipelines.conversational import Conversation


a_								=       logging.get_logger(__name__)
a_								=       {"""vocab_file""": """spiece.model"""}

a_								=       {
    """vocab_file""": {
        """AI-Sweden/gpt-sw3-126m""": """https://huggingface.co/AI-Sweden/gpt-sw3-126m/resolve/main/spiece.model""",
        """AI-Sweden/gpt-sw3-350m""": """https://huggingface.co/AI-Sweden/gpt-sw3-350m/resolve/main/spiece.model""",
        """AI-Sweden/gpt-sw3-1.6b""": """https://huggingface.co/AI-Sweden/gpt-sw3-1.6b/resolve/main/spiece.model""",
        """AI-Sweden/gpt-sw3-6.7b""": """https://huggingface.co/AI-Sweden/gpt-sw3-6.7b/resolve/main/spiece.model""",
        """AI-Sweden/gpt-sw3-20b""": """https://huggingface.co/AI-Sweden/gpt-sw3-20b/resolve/main/spiece.model""",
    }
}

a_								=       {
    """AI-Sweden/gpt-sw3-126m""": 2_048,
    """AI-Sweden/gpt-sw3-350m""": 2_048,
    """AI-Sweden/gpt-sw3-1.6b""": 2_048,
    """AI-Sweden/gpt-sw3-6.7b""": 2_048,
    """AI-Sweden/gpt-sw3-20b""": 2_048,
}



class 			__lowerCAmelCase  (						lowerCAmelCase__ ):
 lowerCAmelCase__							       =	VOCAB_FILES_NAMES
 lowerCAmelCase__							       =	PRETRAINED_VOCAB_FILES_MAP
 lowerCAmelCase__							       =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowerCAmelCase__							       =	["""input_ids""", """attention_mask"""]




 def __init__(    self						,					__UpperCAmelCase						,					__UpperCAmelCase=False						,					__UpperCAmelCase=False						,					__UpperCAmelCase=False						,					__UpperCAmelCase=None						,					__UpperCAmelCase=None						,					__UpperCAmelCase=None						,					__UpperCAmelCase=None						,					__UpperCAmelCase = None						,					**__UpperCAmelCase						,					):



    '''simple docstring'''
    __lowerCamelCase    				=     {} if sp_model_kwargs is None else sp_model_kwargs

    __lowerCamelCase    				=     kwargs.get('''name_or_path'''					)
    if name_or_path is None:
       logger.warning(
           '''name_or_path not provided, will work for all GPTSw3 models except gpt-sw3-7b,'''
           ''' you are testing the model, this can safely be ignored'''					)
       __lowerCamelCase    				=     '''None'''

    # Default definitions for our 2 tokenizer versions, with None-checks to enable proper testing
    __lowerCamelCase    				=     '''<|endoftext|>''' if eos_token is None else eos_token
    __lowerCamelCase    				=     '''<unk>''' if unk_token is None else unk_token
    if "gpt-sw3-7b" in name_or_path:
       __lowerCamelCase    				=     unk_token if pad_token is None else pad_token
       __lowerCamelCase    				=     eos_token if bos_token is None else bos_token
    else:
       __lowerCamelCase    				=     '''<pad>''' if pad_token is None else pad_token
       __lowerCamelCase    				=     '''<s>''' if bos_token is None else bos_token

    super().__init__(
        do_lower_case=__UpperCAmelCase						,					remove_space=__UpperCAmelCase						,					keep_accents=__UpperCAmelCase						,					bos_token=__UpperCAmelCase						,					eos_token=__UpperCAmelCase						,					unk_token=__UpperCAmelCase						,					pad_token=__UpperCAmelCase						,					sp_model_kwargs=self.sp_model_kwargs						,					**__UpperCAmelCase						,					)

    __lowerCamelCase    				=     do_lower_case
    __lowerCamelCase    				=     remove_space
    __lowerCamelCase    				=     keep_accents
    __lowerCamelCase    				=     vocab_file

    __lowerCamelCase    				=     spm.SentencePieceProcessor(**self.sp_model_kwargs					)
    self.sp_model.Load(__UpperCAmelCase					)

    # Used for whitespace normalization in input texts
    # fmt : off
    __lowerCamelCase    				=     {''' ''', ''' ''', ''' ''', ''' ''', ''' ''', '''　''', ''' ''', ''' ''', ''' ''', ''' ''', '''￼''', ''''''}
    # fmt : on

    # Regular expression to remove non-printing characters (e.g. some unicode control chars) in preprocessing
    __lowerCamelCase    				=     re.compile(
        F"""[{"".join(map(__UpperCAmelCase						,					list(range(0						,					9					)					) + list(range(11						,					32					)					) + list(range(127						,					160					)					) + [160, 173, 8203]					)					)}]"""					)




 def __getstate__(    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     self.__dict__.copy()
    __lowerCamelCase    				=     None
    return state




 def __setstate__(    self						,					__UpperCAmelCase					):



    '''simple docstring'''
    __lowerCamelCase    				=     d

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

    __lowerCamelCase    				=     spm.SentencePieceProcessor(**self.sp_model_kwargs					)
    self.sp_model.Load(self.vocab_file					)




 @property
 # Copied from transformers.models.albert.tokenization_albert.AlbertTokenizer.vocab_size
 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    return len(self.sp_model					)




 def 							lowerCamelCase   (    self						,					__UpperCAmelCase					):



    '''simple docstring'''
    __lowerCamelCase    				=     self.non_printing_characters_re.sub(''''''						,					__UpperCAmelCase					)

    # Normalize whitespaces
    __lowerCamelCase    				=     ''''''.join([char if char not in self.whitespaces else ''' ''' for char in text]					)

    # NFC Unicode normalization
    __lowerCamelCase    				=     unicodedata.normalize('''NFC'''						,					__UpperCAmelCase					)
    return text




 def 							lowerCamelCase   (    self						,					__UpperCAmelCase						,					**__UpperCAmelCase					):



    '''simple docstring'''
    __lowerCamelCase    				=     self.preprocess_text(__UpperCAmelCase					)
    return self.sp_model.encode(__UpperCAmelCase						,					out_type=__UpperCAmelCase					)




 def 							lowerCamelCase   (    self						,					__UpperCAmelCase					):



    '''simple docstring'''
    return self.sp_model.PieceToId(__UpperCAmelCase					)




 def 							lowerCamelCase   (    self						,					__UpperCAmelCase					):



    '''simple docstring'''
    return self.sp_model.IdToPiece(__UpperCAmelCase					)




 @staticmethod
 def 							lowerCamelCase   (    __UpperCAmelCase					):



    '''simple docstring'''
    return out_string




 def 							lowerCamelCase   (    self						,					__UpperCAmelCase					):



    '''simple docstring'''
    __lowerCamelCase    				=     []
    __lowerCamelCase    				=     ''''''
    __lowerCamelCase    				=     False
    for token in tokens:
       # make sure that special tokens are not decoded using sentencepiece model
       if token in self.all_special_tokens:
          # TODO: Check if this is needed, as it ensures that decode(encode(doc)) != doc by adding extra whitespace in the decoded document
          if not prev_is_special:
             out_string += " "

          out_string += self.sp_model.decode(__UpperCAmelCase					) + token
          __lowerCamelCase    				=     True
          __lowerCamelCase    				=     []
       else:
          current_sub_tokens.append(__UpperCAmelCase					)
          __lowerCamelCase    				=     False
    out_string += self.sp_model.decode(__UpperCAmelCase					)

    return out_string




 def 							lowerCamelCase   (    self					):



    '''simple docstring'''
    __lowerCamelCase    				=     {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						,					__UpperCAmelCase						,					__UpperCAmelCase = None					):



    '''simple docstring'''
    if not os.path.isdir(__UpperCAmelCase					):
       logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""					)
       return
    __lowerCamelCase    				=     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    				=     self.sp_model.serialized_model_proto()
          fi.write(__UpperCAmelCase					)

    return (out_vocab_file,)




 def 							lowerCamelCase   (    self						,					__UpperCAmelCase						,					__UpperCAmelCase = False					):



    '''simple docstring'''

    if isinstance(__UpperCAmelCase						,					__UpperCAmelCase					):
       __lowerCamelCase    				=     self.preprocess_text(__UpperCAmelCase					)
       __lowerCamelCase    				=     self.sp_model.encode(__UpperCAmelCase					)
    else:
       __lowerCamelCase    				=     [self.preprocess_text(__UpperCAmelCase					) for t in text]
       __lowerCamelCase    				=     self.sp_model.encode(__UpperCAmelCase					)

    if return_tensors is True or return_tensors == "pt":
       __lowerCamelCase    				=     torch.tensor(__UpperCAmelCase					)

    return token_ids




 def 							lowerCamelCase   (    self						,					__UpperCAmelCase					):



    '''simple docstring'''
    return self.sp_model.decode(__UpperCAmelCase					)




 def 							lowerCamelCase   (    self						,					__UpperCAmelCase					):



    '''simple docstring'''
    __lowerCamelCase    				=     [F"""User: {text}""" if is_user else F"""Bot: {text}""" for is_user, text in conversation.iter_texts()]
    __lowerCamelCase    				=     (
        F"""{self.eos_token}{self.bos_token}""" + F"""{self.bos_token}""".join(__UpperCAmelCase					) + F"""{self.bos_token}Bot:"""
    )
    return self.encode(text=__UpperCAmelCase					)






