tj<dZddlZddlZddlZddlmZddlmZddl m Z ddl m Z m Z ddlmZd d lmZe jeZe Gd d eZd gZdS) z Processor class for Bark N) BatchFeature)ProcessorMixin) BatchEncoding)auto_docstringlogging) cached_file) AutoTokenizerceZdZddddZdfd Ze ddZ dd effd Ze d e d e de fdZ dde dzfdZ dde dzfdZedefdZddefdZe ddefdZxZS) BarkProcessorr semantic_prompt coarse_prompt fine_promptNcXt|||_dS)a* speaker_embeddings (`dict[dict[str]]`, *optional*): Optional nested speaker embeddings dictionary. The first level contains voice preset names (e.g `"en_speaker_4"`). The second level contains `"semantic_prompt"`, `"coarse_prompt"` and `"fine_prompt"` embeddings. The values correspond to the path of the corresponding `np.ndarray`. See [here](https://suno-ai.notion.site/8b8e8749ed514b0cbf3f699013548683?v=bc67cff786b04b50b3ceb756fd05f68c) for a list of `voice_preset_names`. N)super__init__speaker_embeddings)self tokenizerr __class__s f/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/transformers/models/bark/processing_bark.pyrzBarkProcessor.__init__*s+ ###"4speaker_embeddings_path.jsonc |d}|t|||dd|dd|dd|dd|dd||d dddd }|?td t j||d d}n>t|5}tj |}dddn #1swxYwYnd}| d |vr||d <tj |fi|}|||S)a Instantiate a Bark processor associated with a pretrained model. Args: pretrained_model_name_or_path (`str` or `os.PathLike`): This can be either: - a string, the *model id* of a pretrained [`BarkProcessor`] hosted inside a model repo on huggingface.co. - a path to a *directory* containing a processor saved using the [`~BarkProcessor.save_pretrained`] method, e.g., `./my_model_directory/`. speaker_embeddings_dict_path (`str`, *optional*, defaults to `"speaker_embeddings_path.json"`): The name of the `.json` file containing the speaker_embeddings dictionary located in `pretrained_model_name_or_path`. If `None`, no speaker_embeddings is loaded. **kwargs Additional keyword arguments passed along to both [`~tokenization_utils_base.PreTrainedTokenizer.from_pretrained`]. tokenN subfolder cache_dirforce_downloadFproxieslocal_files_onlyrevision rr r!r"r#rr$ _raise_exceptions_for_gated_repo%_raise_exceptions_for_missing_entries'_raise_exceptions_for_connection_errors`z` does not exists , no preloaded speaker embeddings will be used - Make sure to provide a correct path to the json dictionary if wanted, otherwise set `speaker_embeddings_dict_path=None`. repo_or_path)rr) getr poploggerwarningospathjoinopenjsonloadr from_pretrained) cls!pretrained_processor_name_or_pathspeaker_embeddings_dict_pathkwargsrspeaker_embeddings_pathrspeaker_embeddings_jsonrs rr5zBarkProcessor.from_pretrained7s, 7## ' 3&11, **[$77 **[$77%zz*:EBB 9d33!',>!F!FJ55166;8= ' ' ' #'.`"',,'HJfgg``` &*""122L6M)-3J)K)K&LLLLLLLLLLLLLLL"&   )!3335V">2!12S^^W]^^ sY;MNNNNs<DD!$D!rF push_to_hubc ,|jotjtj||ddi}||d<tj||}|jD]}||} i} |j|D]} tj||d| } ||| |tj | | | dtj||d| d | | <| ||<ttj||d 5} tj || dddn #1swxYwYtj||fi|dS) a| Saves the attributes of this processor (tokenizer...) in the specified directory so that it can be reloaded using the [`~BarkProcessor.from_pretrained`] method. Args: save_directory (`str` or `os.PathLike`): Directory where the tokenizer files and the speaker embeddings will be saved (directory will be created if it does not exist). speaker_embeddings_dict_path (`str`, *optional*, defaults to `"speaker_embeddings_path.json"`): The name of the `.json` file that will contains the speaker_embeddings nested path dictionary, if it exists, and that will be located in `pretrained_model_name_or_path/speaker_embeddings_directory`. speaker_embeddings_directory (`str`, *optional*, defaults to `"speaker_embeddings/"`): The name of the folder in which the speaker_embeddings arrays will be saved. push_to_hub (`bool`, *optional*, defaults to `False`): Whether or not to push your model to the Hugging Face model hub after saving it. You can specify the repository you want to push to with `repo_id` (will default to the name of `save_directory` in your namespace). kwargs: Additional key word arguments passed along to the [`~utils.PushToHubMixin.push_to_hub`] method. Nv2T)exist_okr*_F) allow_picklez.npyw)rr/makedirsr0r1available_voice_presets_load_voice_preset_reject_path_traversalnpsaver2r3dumprsave_pretrained)rsave_directoryr8speaker_embeddings_directoryr<r9embeddings_dictembeddings_subdir prompt_key voice_presettmp_dictkeytarget_filepathfprs rrJzBarkProcessor.save_pretrainedqs8  " . K ^5QSWXXcg h h h h O.jjC&(gll3DF[F[VYF[F[&\&\O//0A?T^___GO\#->USSSS$&GLL1MR\OhOh_bOhOhOh$i$iHSMM.6 ++bgll>3OPPRUVV /Z\ /2... / / / / / / / / / / / / / / /  FFvFFFFFs E..E25E2base_dir target_pathoffending_valuectj|}tj|} tj||g|k}n#t$rd}YnwxYw|st d|dS)NFzInvalid voice preset path: )r/r0abspath commonpath ValueError)rUrVrWbasetarget containeds rrFz$BarkProcessor._reject_path_traversalswx((-- **D&>::dBII   III  PN?NNOO O P Ps%A&& A54A5rPc |j|}i}|d}|jdd}dD]|}||vrtd|d|d||tj|||||t|jdd|||dd|d d|d d |d d|d d ||ddd d d  }|Stdtj|jdd||d|dtj |||<~|S)Nrr*/r#Voice preset unrecognized, missing z% as a key in self.speaker_embeddings[z].rr r!Fr"r#r$r%r)z{` does not exists , no preloaded voice preset will be used - Make sure to provide correct paths to the z embeddings.) rr+r[rFr/r0r1r r,rGr4) rrPr9voice_preset_pathsvoice_preset_dictrr*rRr0s rrEz BarkProcessor._load_voice_presets!4\B 7##.22>3GG F 3 3C,,, t#ttdpttt  ' 'bgll<9KC9PQQSefiSj   '++NC@@"3' **[$77 **[$77%zz*:EBB 9d33!',>!F!FJ55166;8=   D| #"',,t'>'B'B>SV'W'WYkloYpqq##jv### &(WT]] c " "  rc dD]}||vrtd|dt||tjs-t |dt |j|dt||j|j|kr-t|dt |j|ddS)Nrraz as a key.z voice preset must be a z D ndarray.) r[ isinstancerGndarray TypeErrorstr preset_shapelenshape)rrPrRs r_validate_voice_preset_dictz)BarkProcessor._validate_voice_preset_dictsF j jC,&& !Vs!V!V!VWWWl3/<< i3 g gDDUVYDZ@[@[ g g ghhh<$*++t/@/EEE C!h!hTEVWZE[A\A\!h!h!hiiiF j jrreturnc|jgSt|j}d|vr|d|S)z Returns a list of available voice presets. Returns: `list[str]`: A list of voice preset names. Nr*)rlistkeysremove)r voice_presetss rrDz%BarkProcessor.available_voice_presetssS  " *IT499;;<< ] * *   0 0 0rTremove_unavailablecTg}|j|jD]S} ||}n%#t$r||Y:wxYw||T|r.t dt|d|d|r|D]}|j|= dSdSdS)NzThe following z' speaker embeddings are not available: zU If you would like to use them, please check the paths or try downloading them again.) rrDrEr[appendrlr-r.rj)rrsunavailable_keysrPrcs r_verify_speaker_embeddingsz(BarkProcessor._verify_speaker_embeddingss"  " . $ < D D (,(?(? (M(M%%!$++L999H001BCCCC kS)9%:%:kkcskkk " >$4>>L/ ==% / .  > >>>s*A  A ptc |t|ts~t|tr&|j||jvr||}nCt|tr|ds|dz}t j|}||j|fi|t||}|j |f|d||||d|} ||| d<| S)a voice_preset (`str`, `dict[np.ndarray]`): The voice preset, i.e the speaker embeddings. It can either be a valid voice_preset name, e.g `"en_speaker_1"`, or directly a dictionary of `np.ndarray` embeddings for each submodel of `Bark`. Or it can be a valid file name of a local `.npz` single voice preset containing the keys `"semantic_prompt"`, `"coarse_prompt"` and `"fine_prompt"`. Returns: [`BatchEncoding`]: A [`BatchEncoding`] object containing the output of the `tokenizer`. If a voice preset is provided, the returned object will include a `"history_prompt"` key containing a [`BatchFeature`], i.e the voice preset with the right tensors type. Nz.npz)data tensor_type max_length)return_tensorspaddingr}return_attention_maskreturn_token_type_idsadd_special_tokenshistory_prompt) redictrhrrEendswithrGr4rlrr) rtextrPr~r}rrrr9 encoded_texts r__call__zBarkProcessor.__call__s!0  #J|T,J,J #<-- 5+7 D$;;;#66|DD lC0099N9Nv9V9V9#/L!w|44  # ,D ,\ D DV D D D'\~VVVL%t~   ) !"7"71        #-9L) *r)N)r)rrF)T)NNrxryFTF)__name__ __module__ __qualname__rir classmethodr5boolrJ staticmethodrhrFrErrlpropertyrorDrwrrr __classcell__)rs@rr r "sL 5 5 5 5 5 5Mk7O7O7O[7Ox&D%9! 3G3G  3G3G3G3G3G3GjPP3PQTPPP\P$&!&!sTz&!&!&!&!P j jt j j j j    X >>T>>>>. "#77 777^77777rr )__doc__r3r/numpyrGfeature_extraction_utilsrprocessing_utilsrtokenization_utils_baserutilsrr utils.hubr autor get_loggerrr-r __all__rrrs 444444......444444,,,,,,,,$$$$$$   H % %hhhhhNhhhV  r