Ë
    ÛÓ^j1É  ã                   ó  — U d Z ddlZddlZddlZddlZddlZddlmZ ddlm	Z	 ddl
mZ ddlmZ ddlmZmZ dd	lmZ dd
lmZ ddlmZmZmZmZmZ ddlmZmZ ddlmZ ddl m!Z! ddl"m#Z#m$Z$m%Z%m&Z&m'Z'  e«       rddl(m)Z) ndZ) e«       rddl*m+Z+ ndZ+ ejX                  e-«      Z.i Z/e0e1e2e	   f   e3d<   i Z4e0e1e2e	   f   e3d<    ee1e1dz  f   g d e«       rdndf‘d e«       rdndf‘d e«       rdndf‘d e«       rdndf‘d e«       rdndf‘d e«       rd ndf‘d! e«       rd"ndf‘d# e«       rdndf‘d$ e«       rd%ndf‘d& e«       rd'ndf‘d(‘d) e«       rdndf‘d* e«       rd+ndf‘d,‘d-‘d. e«       rd/ndf‘d0 e«       rdndf‘d1‘d2 e«       rd3ndf‘d4‘d5 e«       rdndf‘d6 e«       rd7ndf‘d8‘d9 e«       rdndf‘d:‘d; e«       rd<ndf‘d=‘d> e«       rdndf‘d?‘d@ e«       rdndf‘dA e«       rdndf‘dB‘dC e«       rdDndf‘dE e«       rd7ndf‘dF e«       rd"ndf‘dG e«       rd"ndf‘dH e«       rd ndf‘dI e«       rdndf‘dJ e«       rd ndf‘dK e«       rdLndf‘dM‘dN‘dO‘dP‘dQ e«       rd7ndf‘dR e«       rdSndf‘dT e«       rdUndf‘dV‘dW e«       rdXndf‘dY e«       rdndf‘dZ e«       rd[ndf‘d\ e«       rdndf‘d] e«       rd7ndf‘d^ e«       rdndf‘d_‘d` e«       rdandf‘db e«       rdcndf‘dd‘de e«       rdndf‘df e«       rdndf‘dg e«       rdhndf‘di e«       rdjndf‘dk‘dl e«       rdmndf‘dn e«       rdXndf‘do e«       rdXndf‘dp e«       rdXndf‘dq e«       rdXndf‘dr e«       rdXndf‘ds e«       rdXndf‘dt e«       rdndf‘du e«       rdndf‘dv e«       rdndf‘dw e«       rdndf‘dx e«       rdndf‘dy e«       rdndf‘dz e«       rdndf‘d{ e«       rdndf‘d| e«       rdndf‘d} e«       rdndf‘d~ e«       rdndf‘d€ e«       rd7ndf‘d� e«       rdndf‘d‚ e«       rd7ndf‘dƒ e«       rdandf‘d„‘d… e«       rd7ndf‘d† e«       rdndf‘d‡ e«       rdndf‘dˆ e«       rdndf‘d‰ e«       rdndf‘dŠ e«       rdndf‘d‹ e«       rdndf‘dŒ e«       rd�ndf‘dŽ‘d� e«       rd ndf‘d�‘d‘ e«       rd’ndf‘d“ e«       rd’ndf‘d” e«       rd7ndf‘d• e«       rd7ndf‘d– e«       rd ndf‘d— e«       rd7ndf‘d˜ e«       rd™ndf‘dš e«       rdndf‘d› e«       rdndf‘dœ e«       rd�ndf‘dž e«       rd�ndf‘dŸ e«       rdndf‘d  e«       rd¡ndf‘d¢ e«       rd£ndf‘d¤ e«       rd¥ndf‘d¦ e«       rd§ndf‘d¨ e«       rd©ndf‘dª e«       rd%ndf‘d« e«       rd%ndf‘d¬‘d­ e«       rd®ndf‘d¯ e«       rd°ndf‘d± e«       rdandf‘d² e«       rdandf‘d³ e«       rd´ndf‘dµ e«       rd¶ndf‘d· e«       rd¸ndf‘d¹ e«       rdºndf‘d»‘d¼ e«       rdndf‘d½ e«       rd™ndf‘d¾‘d¿ e«       rdndf‘dÀ e«       rdndf‘dÁ e«       rdÂn
 e«       rdndf‘dÃ e«       rdÂn
 e«       rdndf‘dÄ e«       rdÂn
 e«       rdndf‘dÅ e«       rdÂn
 e«       rdndf‘dÆ e«       rdÂn
 e«       rdndf‘dÇ e«       rdÈndf‘dÉ e«       rdndf‘dÊ e«       rdËndf‘dÌ e«       rdÍndf‘dÎ e«       rdandf‘dÏ‘dÐ e«       rdÑndf‘dÒ e«       rdÑndf‘dÓ e«       rdÑndf‘dÔ e«       rdÕndf‘dÖ‘d× e«       rdØndf‘dÙ e«       rdØndf‘dÚ e«       rdndf‘dÛ e«       rdÜndf‘dÝ e«       rdÜndf‘dÞ e«       rdndf‘dß e«       rdàndf‘dá e«       rdndf‘dâ e«       rdandf‘dã e«       rdndf‘dä e«       rdndf‘då e«       rdndf‘dæ e«       rdandf‘dç e«       rdndf‘dè e«       rdndf‘dé e«       rdêndf‘dë e«       rd7ndf‘dì e«       rd ndf‘dí e«       rdndf‘dî e«       rdndf‘dï e«       rdØndf‘dð e«       rdØndf‘dñ e«       rdØndf‘dò e«       rdóndf‘dô e«       rdndf‘dõ‘dö e«       rdndf‘d÷ e«       rd7ndf‘dø‘dù e«       rdndf‘dú e«       rdÂn
 e«       rdndf‘dû e«       rdündf‘dý e«       rdàndf‘dþ‘dÿ e«       rdndf‘�d  e«       rd ndf‘�d e«       rd ndf‘�d e«       rd ndf‘�d e«       rd ndf‘�d e«       rd ndf‘�d e«       rd ndf‘�d e«       rd ndf‘�d e«       rd ndf‘�d e«       r�d	ndf‘�d
 e«       r�d	ndf‘�d e«       rd ndf‘�d e«       rd ndf‘�d e«       rd ndf‘�d e«       rd ndf‘�d e«       rd ndf‘�d e«       rd ndf‘�d‘�d e«       rdndf‘�d e«       rdXndf‘�d e«       r�dndf‘�d e«       r�dndf‘�d e«       rdndf‘�d‘�d‘�d‘�d e«       r�dndf‘�d e«       rdandf‘�d e«       rdndf‘�d  e«       rdndf‘�d! e«       r�d"ndf‘�d# e«       r�d"ndf‘�d$ e«       rdXndf‘�d% e«       r�d&ndf‘�d' e«       r�d(ndf‘�d) e«       r�d*ndf‘�d+ e«       r�d,ndf‘�d-‘�d. e«       rdndf‘�d/ e«       rdndf‘�d0 e«       rd7ndf‘�d1 e«       rdÑndf‘�d2 e«       rdÑndf‘�d3 e«       rdXndf‘�d4‘�d5 e«       r�d6ndf‘�d7 e«       rd™ndf‘�d8 e«       rdndf‘�d9 e«       r�d:ndf‘�d; e«       rdndf‘�d<‘�d=‘�d> e«       r�d?ndf‘�d@ e«       rdndf‘�dA e«       rdndf‘�dB‘�dC e«       rdÂn
 e«       rdndf‘�dD e«       rdÂn
 e«       rdndf‘�dE‘�dF‘�dG‘�dH‘�dI e«       r�dJndf‘�dK e«       rdndf‘�dL e«       r�dMndf‘�dN‘�dO e«       rd™ndf‘�dP e«       rdndf‘�dQ e«       r�dRndf‘�dS e«       rdandf‘�dT e«       rd™ndf‘�dU e«       rdndf‘�dV e«       rdXndf‘«      Z5h �dW£Z6e7e1   e3�dX<   e6D ]  Z8e8e5vsŒ e«       rdnde5e8<   Œ  e!e#e5«      Z9 e#jt                  «       D � �ci c]  \  } }|| “Œ
 c}} Z;g �dY¢Z<�dZ„ Z=�d[„ Z>�d\e1ej~                  e1   z  �d]e@f�d^„ZA�d_e1�d]e2e	   dz  f�d`„ZB	 	 	 	 	 	 	 �dl�d\e1ej~                  e1   z  �dae1ej~                  e1   z  dz  �dbe@�dce0e1e1f   dz  �dde@e1z  dz  �dee1dz  �dfe@�dge1�d]e0e1e	f   f�dh„ZC G �di„ �dj«      ZD�dk�djgZEyc c}} w (m  zAuto Tokenizer class.é    N)ÚOrderedDict)ÚAny)Úis_mistral_common_availableé   )ÚPreTrainedConfig)Úget_class_from_dynamic_moduleÚresolve_trust_remote_code)Úload_gguf_checkpoint)ÚTOKENIZER_CONFIG_FILE)Úextract_commit_hashÚis_g2p_en_availableÚis_sentencepiece_availableÚis_tokenizers_availableÚlogging)Úcached_fileÚhas_fileé   )ÚEncoderDecoderConfigé   )Ú_LazyAutoMapping)ÚCONFIG_MAPPING_NAMESÚ
AutoConfigÚconfig_class_to_model_typeÚmodel_type_to_module_nameÚ!replace_list_option_in_docstrings)ÚTokenizersBackend)ÚSentencePieceBackendÚREGISTERED_TOKENIZER_CLASSESÚREGISTERED_FAST_ALIASESÚEvollaModelr   Úaimv2ÚCLIPTokenizerÚalbertÚAlbertTokenizerÚalignÚBertTokenizerÚariaÚaudioflamingo3ÚQwen2TokenizerÚ
aya_visionÚCohereTokenizerÚbarkÚbartÚRobertaTokenizerÚbarthezÚBarthezTokenizer)ÚbartphoÚBartphoTokenizerÚbertzbert-generationÚBertGenerationTokenizer)zbert-japaneseÚBertJapaneseTokenizer)ÚbertweetÚBertweetTokenizerÚbig_birdÚBigBirdTokenizerÚbigbird_pegasus)ÚbiogptÚBioGptTokenizerÚ
blenderbotÚBlenderbotTokenizer)zblenderbot-smallÚBlenderbotSmallTokenizerÚblipzblip-2ÚGPT2Tokenizer)Úbridgetowerr.   Úbros)Úbyt5ÚByT5TokenizerÚ	camembertÚCamembertTokenizer)ÚcanineÚCanineTokenizerÚchinese_clip)Úclapr.   ÚclipÚclipseg)ÚclvpÚClvpTokenizerÚ
code_llamaÚCodeLlamaTokenizerÚcodegenÚcohereÚcohere2Úcolqwen2ÚconvbertÚcosmos3_omniÚcpmÚCpmTokenizer)ÚcpmantÚCpmAntTokenizer)ÚctrlÚCTRLTokenizer)zdata2vec-audioÚWav2Vec2CTCTokenizer)zdata2vec-textr.   ÚdbrxÚdebertaÚDebertaTokenizerz
deberta-v2ÚDebertaV2Tokenizer)ÚdiaÚDiaTokenizerÚdiffusion_gemmaÚGemmaTokenizerÚ
distilbertÚdprÚDPRQuestionEncoderTokenizerÚelectraÚemu3Úernie)ÚesmÚEsmTokenizerÚfalcon_mambaÚGPTNeoXTokenizerÚfastspeech2_conformerÚFastSpeech2ConformerTokenizer)ÚflaubertÚFlaubertTokenizerÚflavaÚ	flex_olmoÚ	florence2ÚBartTokenizerÚfnetÚFNetTokenizer)ÚfsmtÚFSMTTokenizerÚfunnelÚFunnelTokenizerÚgemmaÚgemma2Úgemma3Úgemma3_textÚgemma3nÚgemma3n_textÚgitÚglmÚglm4Úglm4_moeÚglm4_moe_liteÚglm4vÚ	glm4v_moeÚ	glm_imageÚglmasrÚgot_ocr2zgpt-sw3ÚGPTSw3TokenizerÚgpt2Úgpt_bigcodeÚgpt_neoÚgpt_neox)Úgpt_neox_japaneseÚGPTNeoXJapaneseTokenizerÚgptjÚgraniteÚ
granitemoeÚgranitemoehybridÚgranitemoesharedzgrounding-dinoÚgroupvitÚherbertÚHerbertTokenizer)Úhubertr^   Ú
hunyuan_vl)Úibertr.   ÚideficsÚLlamaTokenizerÚidefics2ÚinstructblipÚinstructblipvideoÚinternvlÚjais2Újina_embeddings_v3ÚXLMRobertaTokenizerÚkimi_k25zkosmos-2Úlasr_ctcÚLasrTokenizerÚlasr_encoderÚlayoutlmÚ
layoutlmv2ÚLayoutLMv2TokenizerÚ
layoutlmv3ÚLayoutLMv3TokenizerÚ	layoutxlmÚLayoutXLMTokenizerÚledÚLEDTokenizerÚlighton_ocrÚQwen2TokenizerFastÚliltÚ
longformer)ÚlukeÚLukeTokenizerÚlxmertÚLxmertTokenizerÚm2m_100ÚM2M100TokenizerÚmambaÚmamba2ÚmarianÚMarianTokenizerÚmarkuplmÚMarkupLMTokenizerÚmbartÚMBartTokenizerÚmbart50ÚMBart50Tokenizer)Úmegar.   zmegatron-bertÚ
metaclip_2)zmgp-strÚMgpstrTokenizerÚmimo_v2_flashÚminicpmv4_6Ú	ministralÚMistralCommonBackendÚ
ministral3ÚmistralÚmistral3ÚmixtralÚmlukeÚMLukeTokenizerzmm-grounding-dinoÚ
mobilebertÚMobileBertTokenizerÚmpnetÚMPNetTokenizerÚmpt)Úmrar.   Úmt5ÚT5TokenizerÚmusicgenÚmusicgen_melodyÚmvpÚMvpTokenizer)Úmyt5ÚMyT5TokenizerÚnemotron3_5_asrÚParakeetTokenizerÚnemotron_asr_streamingÚnezhaÚnllbÚNllbTokenizerznllb-moeÚ
nomic_bertÚnougatÚNougatTokenizerÚnystromformerÚolmoÚolmo2Úolmo3Úolmo_hybridÚolmoezomdet-turboÚ	oneformerz
openai-gptÚOpenAIGPTTokenizerÚoptÚovis2Úowlv2ÚowlvitÚparakeet_ctcÚparakeet_rnntÚparakeet_tdtÚpegasusÚPegasusTokenizerÚ	pegasus_x)Ú	perceiverÚPerceiverTokenizerÚ	persimmonÚphi)ÚphobertÚPhobertTokenizerÚ
pix2structÚpixtralÚplbartÚPLBartTokenizerÚpp_formulanet)Ú
prophetnetÚProphetNetTokenizerÚqdqbertÚqianfan_ocrÚqwen2Úqwen2_5_omniÚ
qwen2_5_vlÚqwen2_audioÚ	qwen2_moeÚqwen2_vlÚqwen3Úqwen3_5ÚQwen3_5TokenizerÚqwen3_5_moeÚ	qwen3_asrÚ	qwen3_moeÚ
qwen3_nextÚqwen3_omni_moeÚqwen3_vlÚqwen3_vl_moe)ÚragÚRagTokenizerÚrealmÚrecurrent_gemmaÚreformerÚReformerTokenizerÚrembertÚRemBertTokenizerÚ	retribert)Úrobertar.   )zroberta-prelayernormr.   )Úroc_bertÚRoCBertTokenizerÚroformerÚRoFormerTokenizerÚrwkvÚsam3Ú
sam3_videoÚseamless_m4tÚSeamlessM4TTokenizerÚseamless_m4t_v2Úshieldgemma2ÚsiglipÚSiglipTokenizerÚsiglip2ÚSiglip2TokenizerÚspeech_to_textÚSpeech2TextTokenizerÚspeecht5ÚSpeechT5Tokenizer)ÚsplinterÚSplinterTokenizerÚsqueezebertÚstablelmÚ
starcoder2Úswitch_transformersÚt5Út5gemma)ÚtapasÚTapasTokenizerÚtipsv2ÚTipsv2TokenizerÚtrocrÚtvpÚudopÚUdopTokenizerÚumt5)Ú	unispeechr^   )zunispeech-satr^   Ú
videoprismÚVideoPrismTokenizerÚviltÚvisual_bert)ÚvitsÚVitsTokenizerÚvoxtralÚvoxtral_realtime)Úwav2vec2r^   )zwav2vec2-bertr^   )zwav2vec2-conformerr^   )Úwav2vec2_phonemeÚWav2Vec2PhonemeCTCTokenizerÚwhisperÚWhisperTokenizerÚxclipÚxglmÚXGLMTokenizer)ÚxlmÚXLMTokenizerzxlm-robertazxlm-roberta-xlÚxlnetÚXLNetTokenizerÚxlstmÚxmodÚyosoÚzaya>-   úcamembertv2-baseúvision-encoder-decoderÚfuyuÚphi3ÚjambaÚjanusÚllavaÚmolmoÚnvfp4r  ÚarcticÚchatlmÚmolmo2Úphi3_vÚphimoeÚopencuaÚopenvlaÚsmolvlmÚstep3p5Úernie4_5Úminicpm3ÚminicpmvÚnemotronÚstep3_vlÚvipllavaÚ	chameleonÚ	internlm2Ú
cohere_asrÚ
h2ovl_chatÚ
llava_nextÚ
minimax_m2Ú
modernbertÚdeepseek_v2Údeepseek_v3Údeepseek_v4Údeepseek_vlÚhyperclovaxÚdeepseek_ocrÚdeepseek_v32Úernie4_5_moeÚpaddleocr_vlÚdeepseek_ocr2Údeepseek_vl_v2Úhyperclovax_vlmÚdeepseek_vl_hybridÚ)MODELS_WITH_INCORRECT_HUB_TOKENIZER_CLASS)z!deepseek-ai/deepseek-r1-distill-*zdeepseek-ai/deepseek-coder-*zallenai/dolma2-tokenizerzgoogle/umt5-smallzsalesforce/blip2-opt-*zsalesforce/blip2-flan-t5-*z!salesforce/instructblip-flan-t5-*c                 ót   — t        | dd¬«      5 }t        j                  |«      cddd«       S # 1 sw Y   yxY w)z*Loads a vocabulary file into a dictionary.Úrúutf-8©ÚencodingN)ÚopenÚjsonÚload)Ú
vocab_fileÚreaders     úu/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/transformers/models/auto/tokenization_auto.pyÚ
load_vocabrŸ  ±  s1   € ä	ˆj˜#¨Ô	0ð !°FÜ�y‰y˜Ó ÷!÷ !ò !ús   �.®7c                 óü   — g }t        | dd¬«      5 }|D ]O  }|j                  «       }|sŒ|j                  d«      rŒ(|j                  t	        |j                  «       «      «       ŒQ 	 ddd«       |S # 1 sw Y   |S xY w)z Loads a merges file into a list.r•  r–  r—  ú#N)r™  ÚstripÚ
startswithÚappendÚtupleÚsplit)Úmerges_fileÚmergesr�  Úlines       rž  Úload_mergesrª  ·  sr   € à€FÜ	ˆk˜3¨Ô	1ð 3°VØò 	3ˆDØ—:‘:“<ˆDÚ˜DŸO™O¨CÕ0Ø—‘œe D§J¡J£LÓ1Õ2ñ	3÷3ð
 €M÷3ð
 €Mús   ‘A1ªA1¼*A1Á1A;Úpretrained_model_name_or_pathÚreturnc                 ó*  — |j                  dd«      }|r t        j                  j                  |d«      nd}	 t	        | ||j                  d«      |j                  d«      |j                  d«      |j                  dd«      ¬	«      S # t
        $ r Y yw xY w)
NÚ	subfolderÚ ztekken.jsonÚrevisionÚtokenÚ	cache_dirÚlocal_files_onlyF)r°  r±  r²  r³  )ÚgetÚosÚpathÚjoinr   ÚOSError)r«  Úkwargsr®  Útekken_filenames       rž  Ú_has_tekken_tokenizer_filer»  Â  s‹   € ð —
‘
˜;¨Ó+€IÙ@I”b—g‘g—l‘l 9¨mÔ<È}€Oð
ÜØ)ØØ—Z‘Z 
Ó+Ø—*‘*˜WÓ%Ø—j‘j Ó-Ø#ŸZ™ZÐ(:¸EÓBô
ð 	
øô ò Ùðús   ¸AB Â	BÂBÚ
class_namec                 óf  — | dv rt         S | t        v r	t        |    S | t        v r	t        |    S | dk(  rt         S t        j	                  «       D ]Ð  \  }}|| k(  sŒt        |«      }|dv r| dk(  rt        j                  dd«      }nt        j                  d|› �d«      }	 t        || «      }t        |d	d «      x}rb|t        j                  v rPt        j                  |   }t        ||j                  d
z   |«       t        j                  j                  |dz   |«       |c S  t        j                   j#                  «       D ]  }t        |dd «      | k(  sŒ|c S  t        j                  d«      }t%        || «      rt        || «      S | j'                  d
«      rt)        | d d «      S y # t        $ r Y �Œcw xY w)N>   ÚBloomTokenizerÚBloomTokenizerFastr   )rÓ   rÔ   rÕ   rÐ   rÒ   r  rU  rÑ   z.tokenization_mistral_commonÚtransformersú.ztransformers.modelsÚ
__module__ÚFastÚ_fastÚ__name__éüÿÿÿ)r   r   r   ÚTOKENIZER_MAPPING_NAMESÚitemsr   Ú	importlibÚimport_moduleÚgetattrÚsysÚmodulesÚsetattrrÅ  Ú
setdefaultÚAttributeErrorÚTOKENIZER_MAPPINGÚ_extra_contentÚvaluesÚhasattrÚendswithÚtokenizer_class_from_name)	r¼  Úmodule_nameÚtokenizer_classÚmoduleÚresultÚsubmodÚbase_modÚ	tokenizerÚmain_modules	            rž  rÖ  rÖ  Õ  sÆ  € àÐ=Ñ=Ü Ð àÔ,Ñ,Ü& zÑ2Ð2àÔ1Ñ1Ü+¨JÑ7Ð7àÐ(Ò(Ü Ð ô )@×(EÑ(EÓ(Gò Ñ$ˆ�_Ø˜jÓ(Ü3°KÓ@ˆKàÐrÑrØÐ"8Ò8ä"×0Ñ0Ð1OÐQ_Ó`‘ä"×0Ñ0°1°[°MÐ1BÐDYÓZ�ð	Ü  ¨Ó4�ä% f¨l¸DÓAÐA�FÐAÀvÔQT×Q\ÑQ\ÑG\Ü"Ÿ{™{¨6Ñ2�HÜ˜H f§o¡o¸Ñ&>ÀÔGÜ—K‘K×*Ñ*¨6°GÑ+;¸XÔFØ’ð#ô* '×5Ñ5×<Ñ<Ó>ò ˆ	Ü�9˜j¨$Ó/°:Ó=ØÒðô ×)Ñ)¨.Ó9€KÜˆ{˜JÔ'Ü�{ JÓ/Ð/ð ×Ñ˜6Ô"Ü(¨°C°R¨Ó9Ð9àøô% "ò Úðús   ÂA>F#Æ#	F0Æ/F0r²  Úforce_downloadÚproxiesr±  r°  r³  r®  c                 ó"  — |j                  d«      }	t        | t        |||||||ddd|	¬«      }
|
€t        j	                  d«       i S t        |
|	«      }	t        |
d¬«      5 }t        j                  |«      }ddd«       |	d<   |S # 1 sw Y   ŒxY w)aY  
    Loads the tokenizer configuration from a pretrained model tokenizer configuration.

    Args:
        pretrained_model_name_or_path (`str` or `os.PathLike`):
            This can be either:

            - a string, the *model id* of a pretrained model configuration hosted inside a model repo on
              huggingface.co.
            - a path to a *directory* containing a configuration file saved using the
              [`~PreTrainedTokenizer.save_pretrained`] method, e.g., `./my_model_directory/`.

        cache_dir (`str` or `os.PathLike`, *optional*):
            Path to a directory in which a downloaded pretrained model configuration should be cached if the standard
            cache should not be used.
        force_download (`bool`, *optional*, defaults to `False`):
            Whether or not to force to (re-)download the configuration files and override the cached versions if they
            exist.
        proxies (`dict[str, str]`, *optional*):
            A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128',
            'http://hostname': 'foo.bar:4012'}.` The proxies are used on each request.
        token (`str` or *bool*, *optional*):
            The token to use as HTTP bearer authorization for remote files. If `True`, will use the token generated
            when running `hf auth login` (stored in `~/.huggingface`).
        revision (`str`, *optional*, defaults to `"main"`):
            The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
            git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any
            identifier allowed by git.
        local_files_only (`bool`, *optional*, defaults to `False`):
            If `True`, will only try to load the tokenizer configuration from local files.
        subfolder (`str`, *optional*, defaults to `""`):
            In case the tokenizer config is located inside a subfolder of the model repo on huggingface.co, you can
            specify the folder name here.

    <Tip>

    Passing `token=True` is required when you want to use a private model.

    </Tip>

    Returns:
        `dict`: The configuration of the tokenizer.

    Examples:

    ```python
    # Download configuration from huggingface.co and cache.
    tokenizer_config = get_tokenizer_config("google-bert/bert-base-uncased")
    # This model does not have a tokenizer config so the result will be an empty dict.
    tokenizer_config = get_tokenizer_config("FacebookAI/xlm-roberta-base")

    # Save a pretrained tokenizer locally and you can reload its config
    from transformers import AutoTokenizer

    tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-cased")
    tokenizer.save_pretrained("tokenizer-test")
    tokenizer_config = get_tokenizer_config("tokenizer-test")
    ```Ú_commit_hashF)r²  rß  rà  r±  r°  r³  r®  Ú _raise_exceptions_for_gated_repoÚ%_raise_exceptions_for_missing_entriesÚ'_raise_exceptions_for_connection_errorsrâ  Nz\Could not locate the tokenizer configuration file, will try to use the model config instead.r–  r—  )	r´  r   r   ÚloggerÚinfor   r™  rš  r›  )r«  r²  rß  rà  r±  r°  r³  r®  r¹  Úcommit_hashÚresolved_config_filer�  rÚ  s                rž  Úget_tokenizer_configrê    s«   € ðJ —*‘*˜^Ó,€KÜ&Ø%ÜØØ%ØØØØ)ØØ).Ø.3Ø05Ø ôÐð Ð#Ü�‰ÐrÔsØˆ	Ü%Ð&:¸KÓH€Kä	Ð"¨WÔ	5ð #¸Ü—‘˜6Ó"ˆ÷#à(€Fˆ>ÑØ€M÷#ð #ús   Á BÂBc                   ó\   — e Zd ZdZd„ Ze ee«      dee	z  fd„«       «       Z
e	 dd„«       Zy)ÚAutoTokenizera  
    This is a generic tokenizer class that will be instantiated as one of the tokenizer classes of the library when
    created with the [`AutoTokenizer.from_pretrained`] class method.

    This class cannot be instantiated directly using `__init__()` (throws an error).
    c                 ó   — t        d«      ‚)Nz}AutoTokenizer is designed to be instantiated using the `AutoTokenizer.from_pretrained(pretrained_model_name_or_path)` method.)r¸  )Úselfs    rž  Ú__init__zAutoTokenizer.__init__s  s   € Üð_ó
ð 	
ó    r¬  c           	      ó  ‡— |j                  dd«      }d|d<   |j                  dd«      }|j                  dd«      }|j                  dd«      }|j                  d«      }|�vt        j                  |d«      }	|	€,t        d	|› d
dj	                  d„ t        D «       «      › d�«      ‚t        |	«      }
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€t        d|	› d�«      ‚ |
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        Instantiate one of the tokenizer classes of the library from a pretrained model vocabulary.

        The tokenizer class to instantiate is selected based on the `model_type` property of the config object (either
        passed as an argument or loaded from `pretrained_model_name_or_path` if possible), or when it's missing, by
        falling back to using pattern matching on `pretrained_model_name_or_path`:

        List options

        Params:
            pretrained_model_name_or_path (`str` or `os.PathLike`):
                Can be either:

                    - A string, the *model id* of a predefined tokenizer hosted inside a model repo on huggingface.co.
                    - A path to a *directory* containing vocabulary files required by the tokenizer, for instance saved
                      using the [`~PreTrainedTokenizer.save_pretrained`] method, e.g., `./my_model_directory/`.
                    - a path to a single saved vocabulary file if and only if the tokenizer only requires a
                      single vocabulary file (like Bert or XLNet), e.g.: `./my_model_directory/vocab.txt`. (Not
                      applicable to all derived classes)
            inputs (additional positional arguments, *optional*):
                Will be passed along to the Tokenizer `__init__()` method.
            config ([`PreTrainedConfig`], *optional*)
                The configuration object used to determine the tokenizer class to instantiate.
            cache_dir (`str` or `os.PathLike`, *optional*):
                Path to a directory in which a downloaded pretrained model configuration should be cached if the
                standard cache should not be used.
            force_download (`bool`, *optional*, defaults to `False`):
                Whether or not to force the (re-)download the model weights and configuration files and override the
                cached versions if they exist.
            proxies (`dict[str, str]`, *optional*):
                A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128',
                'http://hostname': 'foo.bar:4012'}`. The proxies are used on each request.
            revision (`str`, *optional*, defaults to `"main"`):
                The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a
                git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any
                identifier allowed by git.
            subfolder (`str`, *optional*):
                In case the relevant files are located inside a subfolder of the model repo on huggingface.co (e.g. for
                facebook/rag-token-base), specify it here.
            tokenizer_type (`str`, *optional*):
                Tokenizer type to be loaded.
            backend (`str`, *optional*, defaults to `"tokenizers"`):
                Backend to use for tokenization. Valid options are:
                - `"tokenizers"`: Use the HuggingFace tokenizers library backend (default)
                - `"sentencepiece"`: Use the SentencePiece backend
            trust_remote_code (`bool`, *optional*, defaults to `False`):
                Whether or not to allow for custom models defined on the Hub in their own modeling files. This option
                should only be set to `True` for repositories you trust and in which you have read the code, as it will
                execute code present on the Hub on your local machine.
            kwargs (additional keyword arguments, *optional*):
                Will be passed to the Tokenizer `__init__()` method. Can be used to set special tokens like
                `bos_token`, `eos_token`, `unk_token`, `sep_token`, `pad_token`, `cls_token`, `mask_token`,
                `additional_special_tokens`. See parameters in the `__init__()` for more details.

        Examples:

        ```python
        >>> from transformers import AutoTokenizer

        >>> # Download vocabulary from huggingface.co and cache.
        >>> tokenizer = AutoTokenizer.from_pretrained("google-bert/bert-base-uncased")

        >>> # Download vocabulary from huggingface.co (user-uploaded) and cache.
        >>> tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-german-cased")

        >>> # If vocabulary files are in a directory (e.g. tokenizer was saved using *save_pretrained('./test/saved_model/')*)
        >>> # tokenizer = AutoTokenizer.from_pretrained("./test/bert_saved_model/")

        >>> # Download vocabulary from huggingface.co and define model-specific arguments
        >>> tokenizer = AutoTokenizer.from_pretrained("FacebookAI/roberta-base", add_prefix_space=True)

        >>> # Explicitly use the tokenizers backend
        >>> tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/llama-tokenizer", backend="tokenizers")

        >>> # Explicitly use the sentencepiece backend
        >>> tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/llama-tokenizer", backend="sentencepiece")
        ```ÚconfigNTÚ
_from_autoÚuse_fastÚtokenizer_typeÚtrust_remote_codeÚ	gguf_filezPassed `tokenizer_type` z3 does not exist. `tokenizer_type` should be one of z, c              3   ó    K  — | ]  }|–— Œ y ­w©N© ©Ú.0Úcs     rž  ú	<genexpr>z0AutoTokenizer.from_pretrained.<locals>.<genexpr>Û  s   è ø€ Ò D q¤Ñ Dùs   ‚rÁ  zTokenizer class z is not currently imported.F)Úreturn_tensorsÚ
model_namerØ  Úauto_maprì  Ú_name_or_pathr¯  c              3   óJ   •K  — | ]  }t        j                   ‰|«      –— Œ y ­wrù  )Úfnmatch)rü  ÚpÚ_config_name_or_paths     €rž  rþ  z0AutoTokenizer.from_pretrained.<locals>.<genexpr>  s   øè ø€ ÒfÀ”G—O‘OÐ$8¸!×<Ñfùs   ƒ #rÃ  )r   ÚPythonBackendÚPreTrainedTokenizerFastrÑ   )r   r  r  rÑ   Úfix_mistral_regexzTokenizer class 'zf' specified in the tokenizer config was not found. The tokenizer may need to be converted or re-saved.râ  rÆ  ztransformers.r   r   z--Úcode_revisionr  r  z The encoder model config class: z3 is different from the decoder model config class: z˜. It is not recommended to use the `AutoTokenizer.from_pretrained()` method in this case. Please use the encoder and decoder specific tokenizer classes.Ú
model_typerÅ  r   z!Unrecognized configuration class z8 to build an AutoTokenizer.
Model type should be one of c              3   ó4   K  — | ]  }|j                   –— Œ y ­wrù  )rÅ  rû  s     rž  rþ  z0AutoTokenizer.from_pretrained.<locals>.<genexpr>¸  s   è ø€ Ò4[ÀA°Q·ZµZÑ4[ùs   ‚rú  )0Úpopr´  rÇ  Ú
ValueErrorr·  rÖ  Úfrom_pretrainedr   r
   r   Ú	for_modelr¸  r   r  rÔ  r   rê  Ú
isinstancer¥  ÚlistrË  ÚstrÚlowerr   ÚanyÚMODEL_IDS_TO_TOKENIZERS_BACKENDÚremovesuffixr“  rÅ  r   r»  rÕ  ÚtyperÑ  rÂ  r£  r¦  r	   r   Úregister_for_auto_classrØ  r   ÚdecoderÚencoderræ  ÚwarningÚ	__class__r   )Úclsr«  Úinputsr¹  rò  Ú_rõ  rö  r÷  Útokenizer_class_namerØ  Ú	gguf_pathÚconfig_dictÚconfig_model_typeÚconfig_model_nameÚtokenizer_configÚtokenizer_config_classÚtokenizer_auto_mapÚnameÚ
_hub_classÚregistered_class_namer¼  Úhas_remote_codeÚhas_local_codeÚexplicit_local_codeÚ	class_refÚupstream_repoÚtokenizer_class_candidateÚ_classr  r  s                                 @rž  r  zAutoTokenizer.from_pretrainedy  s
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 ,ÒW¬w°vÐ?PÐRVÓ/Wˆ
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 $ð ô #<¸JÓ"G�Ø"Ð.°?×3KÑ3Kð Tñ 4ð
 ;˜?×:Ñ:Ð;XÐlÐ[aÒlÐekÑlÐlð &Ð)?Ò?Ü/Ô1Ø'¨vÑ5Ü.Ð/LÑWÐPVÒWä";Ð<RÓ"S�Ø"Ð.Ø:˜?×:Ñ:Ð;XÐlÐ[aÒlÐekÑlÐlä Ð,Ü(×8Ñ8Ð9VÐjÐY_ÒjÐciÑjÐjäØ# J <ð 0Fð Góð ð
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ð 	
øôQ ¤Ð(ò cÜ)×9Ñ9Ð:WÑbÐ[aÑb“ðcús   Ä] Ý%^Þ^Nc                 óÐ   — |€|�|}n|�|}nt        d«      ‚|||fD ]  }|€Œ|t        |j                  <   Œ |�|�|t        |j                  <   t        j                  | ||¬«       y)a¼  
        Register a new tokenizer in this mapping.

        Args:
            config_class ([`PreTrainedConfig`]):
                The configuration corresponding to the model to register.
            tokenizer_class: The tokenizer class to register (V5 - preferred parameter).
            slow_tokenizer_class: (Deprecated) The slow tokenizer to register.
            fast_tokenizer_class: (Deprecated) The fast tokenizer to register.
        Nz$You need to pass a `tokenizer_class`)Úexist_ok)r  r   rÅ  r   rÑ  Úregister)Úconfig_classrØ  Úslow_tokenizer_classÚfast_tokenizer_classr4  Ú	candidates         rž  r5  zAutoTokenizer.register»  s‘   € ð Ð"à#Ð/Ø"6‘Ø%Ð1Ø"6‘ä Ð!GÓHÐHà.Ð0DÀoÐVò 	MˆIØÑ$ØCLÔ,¨Y×-?Ñ-?Ò@ð	Mð  Ð+Ð0DÐ0PØEYÔ#Ð$8×$AÑ$AÑBä×"Ñ" <°È8Ð"ÕTrð  )NNNF)rÅ  rÂ  Ú__qualname__Ú__doc__rï  Úclassmethodr   rÇ  r   r   r  Ústaticmethodr5  rú  rð  rž  rì  rì  k  sZ   „ ñò
ð Ù&Ð'>Ó?ð~
à	Ð1Ñ	1ò~
ó @ó ð~
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   Útokenization_utils_baser   Úutilsr   r   r   r   r   Ú	utils.hubr   r   Úencoder_decoderr   Úauto_factoryr   Úconfiguration_autor   r   r   r   r   Útokenization_utils_tokenizersr   Ú tokenization_utils_sentencepiecer   Ú
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