+ œ°³j ãó~€Rt^RIHtHtHt^RIHtHtHt^RI H t !RR]RR7t ] !RR ]44t R .t R #) z% Speech processor class for Wav2Vec2 )ÚProcessingKwargsÚProcessorMixinÚUnpack)Ú AudioInputÚPreTokenizedInputÚ TextInput)Úauto_docstringcó€]tRt^t/tRtR#)ÚWav2Vec2ProcessorKwargs©N)Ú__name__Ú __module__Ú __qualname__Ú__firstlineno__Ú _defaultsÚ__static_attributes__r óÚq/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/wav2vec2/processing_wav2vec2.pyr r s†Ø„Irr F)Útotalcóhaa€]tRt^toV3Rlt]RV3RlRll4tRt]R4t Rt Vt V;t #)ÚWav2Vec2Processorcó&<€\SV`W4R#)N)ÚsuperÚ__init__)ÚselfÚfeature_extractorÚ tokenizerÚ __class__s&&&€rrÚWav2Vec2Processor.__init__sø€Ü ‰ÑÐ*Ö6rcó˜<€V^8„dQhRS[R,RS[S[S[,,S[,S[,R,RS[S[,/#)éÚaudioNÚtextÚkwargs)rÚstrÚlistrrrr )ÚformatÚ __classdict__s"€rÚ __annotate__ÚWav2Vec2Processor.__annotate__!sLø€÷ñá˜DÕ ðñ‘D™•Io¡ Õ)Ñ,=Õ=ÀÕDðñÑ0Õ1ñ rc ó.€VfVf \R4hVP!\3RVPP/VBpVeVP !V3/VR,BpVeVP!V3/VR,BpVfX#VfX#XR,XR&V#)z’ Returns: This method returns the results of each `call` method. If both are used, the output is a dictionary containing the results of both. zAYou need to specify either an `audio` or `text` input to process.Útokenizer_init_kwargsÚ audio_kwargsÚ text_kwargsÚ input_idsÚlabels)Ú ValueErrorÚ _merge_kwargsr rÚ init_kwargsr)rr!r"r#Ú output_kwargsÚinputsÚ encodingss&&&, rÚ__call__ÚWav2Vec2Processor.__call__ s±€ð Š=˜Tš\ÜÐ`ÓaÐ aà×*Ò*Ü #ñ à"&§.¡.×"<Ñ"<ð ðñ ˆ ð Ò Ø×+Ò+¨EÑS°]À>Õ5RÑSˆFØ Ò ØŸš tÑL¨}¸]Õ/KÑLˆIà Š<؈MØ Š]ØÐ à(¨Õ5ˆF8Ñ ØˆMrc óL€VPRR4pVPRR4p\V4^8”dV^,pVR,pVe!VPP!V.VO5/VBpVeVPP!V3/VBpVfV#VfV#VR,VR&V#)a This method operates on batches of extracted features and/or tokenized text. It forwards all arguments to [`Wav2Vec2FeatureExtractor.pad`] and/or [`PreTrainedTokenizer.pad`] depending on the input modality and returns their outputs. If both modalities are passed, [`Wav2Vec2FeatureExtractor.pad`] and [`PreTrainedTokenizer.pad`] are called. Args: input_features: When the first argument is a dictionary containing a batch of tensors, or the `input_features` argument is present, it is passed to [`Wav2Vec2FeatureExtractor.pad`]. labels: When the `label` argument is present, it is passed to [`PreTrainedTokenizer.pad`]. Returns: This method returns the results of each `pad` method. If both are used, the output is a dictionary containing the results of both. Úinput_featuresNr/:éNNr.)ÚpopÚlenrÚpadr)rÚargsr#r9r/s&*, rr=ÚWav2Vec2Processor.padAs³€ð Ÿ™Ð$4°dÓ;ˆØ—‘˜H dÓ+ˆÜ ˆt‹9qŒ=Ø! !WˆNؘ•8ˆDà Ò %Ø!×3Ñ3×7Ò7¸ÐXÈÒXÐQWÑXˆNØ Ò Ø—^‘^×'Ò'¨Ñ9°&Ñ9ˆFà Š>Ø!Ð !Ø Ò #؈Mà'-¨kÕ':ˆN˜8Ñ $Ø!Ð !rcóB€VPPpVR.,#)r/)rÚmodel_input_names)rÚfeature_extractor_input_namess& rrAÚ#Wav2Vec2Processor.model_input_namesbs#€ð)-×(>Ñ(>×(PÑ(PÐ%Ø,°¨zÕ9Ð9rr )NN) r r rrrrr6r=ÚpropertyrArÚ__classdictcell__Ú __classcell__)rr's@@rrrsCù‡€õ7ð÷ñóðò@"ðBñ:ó÷:ð:rrN)Ú__doc__Úprocessing_utilsrrrÚtokenization_utils_baserrrÚutilsrr rÚ__all__r rrÚrLsTðñ÷IÑHßOÑOÝ#ôÐ.°eõðôJ:˜óJ:óðJ:ðZ Ð ‚r