eThvSrSSKrSSKrSSKrSSKrSSKJr SSKJrJ r J r J r SSK r SSKJr SSKJrJrJrJrJrJrJrJrJrJrJrJrJrJrJrJ r J!r!J"r"J#r# \(a\"5(aSSK$r$\"RJ"\&5r'\ Sr("S S \5r)"S S \5r*\"\*RV5\*l+\*RVRb5\*RVRRYS SSS9\*RVlgg)zH Feature extraction saving/loading class for common feature extractors. N)UserDict) TYPE_CHECKINGAnyOptionalUnion)custom_object_save)FEATURE_EXTRACTOR_NAMEPushToHubMixin TensorTypeadd_model_info_to_auto_map"add_model_info_to_custom_pipelines cached_file copy_func download_urlis_flax_available is_jax_tensoris_numpy_arrayis_offline_mode is_remote_urlis_tf_availableis_torch_availableis_torch_deviceis_torch_dtypeloggingrequires_backendsSequenceFeatureExtractorc^\rSrSrSrSS\\\\4S\ S\\ 44U4Sjjjr S\S\ \4S jr S\4S jr S rS rS rSrSrSS\\ \\ 44SjjrSS\\ \\ 44SjjrSSjrSrU=r$) BatchFeature=a- Holds the output of the [`~SequenceFeatureExtractor.pad`] and feature extractor specific `__call__` methods. This class is derived from a python dictionary and can be used as a dictionary. Args: data (`dict`, *optional*): Dictionary of lists/arrays/tensors returned by the __call__/pad methods ('input_values', 'attention_mask', etc.). tensor_type (`Union[None, str, TensorType]`, *optional*): You can give a tensor_type here to convert the lists of integers in PyTorch/TensorFlow/Numpy Tensors at initialization. Ndata tensor_typecB>[TU]U5 URUS9 g)N)r")super__init__convert_to_tensors)selfr!r" __class__s ]/var/www/auris/envauris/lib/python3.13/site-packages/transformers/feature_extraction_utils.pyr%BatchFeature.__init__Ls!  K8itemreturnc`[U[5(aURU$[S5e)zu If the key is a string, returns the value of the dict associated to `key` ('input_values', 'attention_mask', etc.). zRIndexing with integers is not available when using Python based feature extractors) isinstancestrr!KeyErrorr'r,s r) __getitem__BatchFeature.__getitem__Ps+ dC 99T? "op pr+cJURU$![a [ef=fN)r!r1AttributeErrorr2s r) __getattr__BatchFeature.__getattr__Zs* !99T? " !  !s"cSUR0$Nr!r!r's r) __getstate__BatchFeature.__getstate__`s ""r+c&SU;a USUlggr;r<)r'states r) __setstate__BatchFeature.__setstate__cs U?f DI r+c6URR5$r6)r!keysr=s r)rEBatchFeature.keyshsyy~~r+c6URR5$r6)r!valuesr=s r)rHBatchFeature.valueslsyy!!r+c6URR5$r6)r!itemsr=s r)rKBatchFeature.itemspsyy  r+c2^^Ucg[U[5(d [U5nU[R:Xa:[5(d [ S5eSSKnUR mURnUT4$U[R:Xa4[5(d [ S5eSSK mU4SjmTRnUT4$U[R:Xa6[5(d [ S5eSSK Jn URm[ nUT4$SU4Sjjm["nUT4$) NNNzSUnable to convert output to TensorFlow tensors format, TensorFlow is not installed.rzMUnable to convert output to PyTorch tensors format, PyTorch is not installed.c&>[U[[45(a[U5S:a[US[R 5(a[R "U5nOk[US[[45(aM[US5S:a;[USS[R 5(a[R "U5n[U[R 5(aTR"U5$TR"U5$)Nr) r/listtuplelennpndarrayarray from_numpytensor)valuetorchs r) as_tensor5BatchFeature._get_is_as_tensor_fns..as_tensorsedE]33E Q!%(BJJ77 ""58dE];;aMA-&uQx{BJJ?? "eRZZ00 ++E22 <<..r+zEUnable to convert output to JAX tensors format, JAX is not installed.c>[U[[45(a[US[[[R45(afUVs/sHn[ U5PM nn[ [ U55S:a3Uc0T"UVs/sHn[R"U5PM sn[S9n[R"XS9$s snfs snf)Nrr)dtype) r/rPrQrSrTrRsetasarrayobject)rXr]val value_lensrZs r)rZr[sedE]33 58dTY[][e[eMf8g8g6;!c$i!mq'Cc""C%%)=)=CQTAUAU!#McRUhZWo!pqqJJLDA!\\**u/F/Fq/I/IddD3F3 A||,,1Cdd&dL  !  r+r<rNr6)r-r)__name__ __module__ __qualname____firstlineno____doc__rdictr0rrr r%r3r8r>rBrErHrKrnr&r|__static_attributes__ __classcell__)r(s@r)rr=s 9Xd38n595QUWZ\fQfKg99qqc q!! #&  "!9$%Z:P1Q9$vhuS*_7M.N>,,r+rc\rSrSrSrSrSrS\4Sjr\ SS\ \\ R4S\ \ \\ R4S \S \S \ \ \\4S \4 S jj5rSS\ \\ R4S\4Sjjr\ S\ \\ R4S\\\\4\\\444Sj5r\ S\\\4S\4Sj5rS\\\44Sjr\ S\ \\ R4S\4Sj5rS\4SjrS\ \\ R44SjrSr\ S Sj5rSrg)!FeatureExtractionMixinz~ This is a feature extraction mixin used to provide saving/loading functionality for sequential and image feature extractors. Nc URSS5UlUR5Hup#[XU5 M g![a%n[ R SUSUSU35 UeSnAff=f)z'Set elements of `kwargs` as attributes.processor_classNz Can't set z with value z for )pop_processor_classrKsetattrr7loggererror)r'r~rsrXerrs r)r%FeatureExtractionMixin.__init__so!' + To test a pull request you made on the Hub, you can pass `revision="refs/pr/"`. return_unused_kwargs (`bool`, *optional*, defaults to `False`): If `False`, then this function returns just the final feature extractor object. If `True`, then this functions returns a `Tuple(feature_extractor, unused_kwargs)` where *unused_kwargs* is a dictionary consisting of the key/value pairs whose keys are not feature extractor attributes: i.e., the part of `kwargs` which has not been used to update `feature_extractor` and is otherwise ignored. kwargs (`Dict[str, Any]`, *optional*): The values in kwargs of any keys which are feature extractor attributes will be used to override the loaded values. Behavior concerning key/value pairs whose keys are *not* feature extractor attributes is controlled by the `return_unused_kwargs` keyword parameter. Returns: A feature extractor of type [`~feature_extraction_utils.FeatureExtractionMixin`]. Examples: ```python # We can't instantiate directly the base class *FeatureExtractionMixin* nor *SequenceFeatureExtractor* so let's show the examples on a # derived class: *Wav2Vec2FeatureExtractor* feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained( "facebook/wav2vec2-base-960h" ) # Download feature_extraction_config from huggingface.co and cache. feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained( "./test/saved_model/" ) # E.g. feature_extractor (or model) was saved using *save_pretrained('./test/saved_model/')* feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("./test/saved_model/preprocessor_config.json") feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained( "facebook/wav2vec2-base-960h", return_attention_mask=False, foo=False ) assert feature_extractor.return_attention_mask is False feature_extractor, unused_kwargs = Wav2Vec2FeatureExtractor.from_pretrained( "facebook/wav2vec2-base-960h", return_attention_mask=False, foo=False, return_unused_kwargs=True ) assert feature_extractor.return_attention_mask is False assert unused_kwargs == {"foo": False} ```rrrruse_auth_tokenNrThe `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.V`token` and `use_auth_token` are both specified. Please set only the argument `token`.r)rwarningswarn FutureWarningrrget_feature_extractor_dict from_dict) clsrrrrrrr~rfeature_extractor_dicts r)from_pretrained&FeatureExtractionMixin.from_pretrainedsp({#1 %5!"%z$4d;  % MME   l#E  #7O),)G)GHe)pio)p&}}3>v>>r+save_directory push_to_hubc HURSS5nUb=[R"S[5 UR SS5b [ S5eXCS'[ RRU5(a[SUS35e[ R"USS 9 U(arURS S5nURS UR[ RR5S 5nUR"U40UD6nURU5nURb [!XUS 9 [ RR#U[$5nUR'U5 [(R+SU35 U(a"UR-UWWWUR S5S9 U/$)a Save a feature_extractor object to the directory `save_directory`, so that it can be re-loaded using the [`~feature_extraction_utils.FeatureExtractionMixin.from_pretrained`] class method. Args: save_directory (`str` or `os.PathLike`): Directory where the feature extractor JSON file will be saved (will be created if it does not exist). 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 (`Dict[str, Any]`, *optional*): Additional key word arguments passed along to the [`~utils.PushToHubMixin.push_to_hub`] method. rNrrrzProvided path (z#) should be a directory, not a fileT)exist_okcommit_messagerepo_id)configzFeature extractor saved in )rr)rrrrrxrrospathisfileAssertionErrormakedirssplitsep _create_repo_get_files_timestamps _auto_classr joinr to_json_filerinfo_upload_modified_files) r'rrr~rrrfiles_timestampsoutput_feature_extractor_files r)save_pretrained&FeatureExtractionMixin.save_pretraineds $4d;  % MME zz'4(4 l-7O 77>>. ) ) ?>2BBe!fg g NT2 #ZZ(8$?NjjN,@,@,Mb,QRG'':6:G#99.I     ' tD A)+ ^E[(\% 78 12O1PQR   ' ' -jj) ( ...r+r-c 4URSS5nURSS5nURSS5nURSS5nURSS5nURSS5nURS S5n URS S5n URS S5n U b+[R"S [5 Ub [ S 5eU nURSS5n URSS5n SU S.nU bXS'[ 5(aU (d[ RS5 Sn [U5n[RRU5n[RRU5(a$[RRU[5n[RRU5(aUnSnO8[U5(aUn[!U5nO[n[#UUUUUUU UUUU S9 n[)USS9nUR+5nSSS5 [,R."W5nU(a[ RSU35 O[ RSWSU35 U(d0S U;a[3US U5US 'S!U;a[5US!U5US!'UU4$![$a e[&a [%SUSUS[S35ef=f!,(df  N=f![,R0a [%SUS35ef=f)"a From a `pretrained_model_name_or_path`, resolve to a dictionary of parameters, to be used for instantiating a feature extractor of type [`~feature_extraction_utils.FeatureExtractionMixin`] using `from_dict`. Parameters: pretrained_model_name_or_path (`str` or `os.PathLike`): The identifier of the pre-trained checkpoint from which we want the dictionary of parameters. Returns: `Tuple[Dict, Dict]`: The dictionary(ies) that will be used to instantiate the feature extractor object. rNrFresume_downloadproxies subfolderrrrrrr_from_pipeline _from_autofeature extractor) file_typefrom_auto_classusing_pipelinez+Offline mode: forcing local_files_only=TrueT) rrrrrrr user_agentrz"Can't load feature extractor for 'z'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'z2' is the correct path to a directory containing a z fileutf-8encodingz"It looks like the config file at 'z' is not a valid JSON file.zloading configuration file z from cache at auto_mapcustom_pipelines)rrrrrrrrrr0rrisdirrr rrrrOSError ExceptionopenreadjsonloadsJSONDecodeErrorr r)rrr~rrrrrrrrr from_pipelinerris_localfeature_extractor_fileresolved_feature_extractor_filereadertextrs r)r1FeatureExtractionMixin.get_feature_extractor_dictsFJJ{D1 $4e< **%6=**Y-JJ{D1  7D)$4d;!::&8%@::j$/  % MME   l#E #3T:  **\59#6?[  $+8' (   %5 KKE F# (+,I(J%77==!>? 77==6 7 7%'WW\\2OQg%h " 77>>7 8 8.K +H 8 9 9%B ".:;X.Y +%; " 2=1*'#1#$3%5')% 3/4 5HF{{}I%)ZZ%5 "  KK56U5VW X KK-.D-E_UtTuv 335O*:68U6&z2"%;;=_*+=>@]>&'9:&v--S  89V8WX99V8WX//E.FeM IH## 45T4UUpq  s0.J1 K3 K"K31.K" K0,K33$Lrc "URSS5n/nUR5H!upVXQ;dM XaU'URU5 M# UHnURUS5 M U"S0UD6n[R SU35 U(aXr4$U$)a Instantiates a type of [`~feature_extraction_utils.FeatureExtractionMixin`] from a Python dictionary of parameters. Args: feature_extractor_dict (`Dict[str, Any]`): Dictionary that will be used to instantiate the feature extractor object. Such a dictionary can be retrieved from a pretrained checkpoint by leveraging the [`~feature_extraction_utils.FeatureExtractionMixin.to_dict`] method. kwargs (`Dict[str, Any]`): Additional parameters from which to initialize the feature extractor object. Returns: [`~feature_extraction_utils.FeatureExtractionMixin`]: The feature extractor object instantiated from those parameters. return_unused_kwargsFNzFeature extractor )rrKappendrr)rrr~r to_removersrXfeature_extractors r)r FeatureExtractionMixin.from_dict6s$ &zz*@%H  ,,.JC,.3s+  %)C JJsD ! 9"89 ():(;<= $, ,$ $r+c[R"UR5nURRUS'SU;aUS SU;aUS U$)z Serializes this instance to a Python dictionary. Returns: `Dict[str, Any]`: Dictionary of all the attributes that make up this configuration instance. feature_extractor_type mel_filterswindow)copydeepcopy__dict__r(r)r'outputs r)to_dictFeatureExtractionMixin.to_dict[sP t}}-+/>>+B+B'( F "}% v x  r+ json_filec[USS9nUR5nSSS5 [R"W5nU"S0UD6$!,(df  N,=f)a Instantiates a feature extractor of type [`~feature_extraction_utils.FeatureExtractionMixin`] from the path to a JSON file of parameters. Args: json_file (`str` or `os.PathLike`): Path to the JSON file containing the parameters. Returns: A feature extractor of type [`~feature_extraction_utils.FeatureExtractionMixin`]: The feature_extractor object instantiated from that JSON file. rrNr)rrrr)rrrrrs r)from_json_file%FeatureExtractionMixin.from_json_filehsG)g .&;;=D/!%D!1,+,,/ .s A AcUR5nUR5H8up#[U[R5(dM&UR 5X'M: UR SS5nUbXAS'[R"USSS9S-$)z Serializes this instance to a JSON string. Returns: `str`: String containing all the attributes that make up this feature_extractor instance in JSON format. rNrT)indent sort_keys ) rrKr/rSrTtolistrrdumps)r' dictionaryrsrXrs r)to_json_string%FeatureExtractionMixin.to_json_string{s}\\^ $**,JC%,,"',,. - &>>* This API is experimental and may have some slight breaking changes in the next releases. Args: auto_class (`str` or `type`, *optional*, defaults to `"AutoFeatureExtractor"`): The auto class to register this new feature extractor with. rNz is not a valid auto class.) r/r0rtransformers.models.automodelsautohasattrrrr)r auto_class auto_modules r)register_for_auto_class.FeatureExtractionMixin.register_for_auto_classsE *c**#,,J66{// |+FGH H$r+r)NFFNmain)F)AutoFeatureExtractor)rrrrrrr%r0r classmethodrrPathLikerboolrrrQrrrPreTrainedFeatureExtractorrrrrrrrrrr+r)rrs K 0C08<$!&,0m?',S"++-='>m?E#r{{"234m? m?  m? c4i() m?m?m?^;/eC4D.E;/TX;/zr.,1#r{{2B,Cr. tCH~tCH~- .r.r.h"%tCH~"%Lf"%"%H c3h -uS"++-='>-C]--$GG* 05bkk1A+B 0D%%r+rrrzfeature extractor file)r` object_class object_files)-rrrrr collectionsrtypingrrrrrkrSdynamic_module_utilsr utilsr r r r rrrrrrrrrrrrrrrrY get_loggerrrrrrrformatrr+r)r(s  664.   H %"#=>|8|~z%^z%z &//E/Q/Q%R"%%--91G1S1S1[1[1b1b"1GVn2c2&&.:r+