Zj'SSKrSSKrSSKJrJr SSKJr SSKJ r J r J r SSK J r SSKJrJr \"5(aSSKr\R$"\5r"SS \ S S 9r"S S \ 5rS /rg)N) AudioInputmake_list_of_audio) BatchFeature)ProcessingKwargsProcessorMixinUnpack) TextInput)is_torch_availableloggingc2\rSrSrSS0SSSS.SSS .S .rS rg ) MusicFlamingoProcessorKwargs(paddingTi> max_length) sampling_ratereturn_attention_maskrptleft)return_tensors padding_side) text_kwargs audio_kwargs common_kwargsN)__name__ __module__ __qualname____firstlineno__ _defaults__static_attributes__rڋ/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/musicflamingo/processing_musicflamingo.pyrr(s2 t #%)# #"  Ir"rF)totalc ^\rSrSrSrSU4SjjrSrSrSrSS\ \ \ -S \ S-S \ S-S \ \S \4 S jjr\S \ \4Sj5rSrU=r$)MusicFlamingoProcessor9a Constructs an MusicFlamingo processor which wraps an MusicFlamingo feature extractor and an MusicFlamingo tokenizer into a single processor. [`MusicFlamingoProcessor`] offers all the functionalities of [`WhisperFeatureExtractor`] and [`Qwen2TokenizerFast`]. See the [`~MusicFlamingoProcessor.__call__`] for more information. Args: feature_extractor ([`WhisperFeatureExtractor`]): The feature extractor is a required input. tokenizer ([`Qwen2TokenizerFast`]): The tokenizer is a required input. chat_template (`Optional[str]`, *optional*): The Jinja template to use for formatting the conversation. If not provided, the tokenizer's default chat template will be used. audio_token (`Optional[str]`, *optional*, defaults to `""`): Special token used to represent audio inputs in the chat template. audio_bos_token (`Optional[str]`, *optional*, defaults to `"<|sound_bos|>"`): Special token used to represent the beginning of audio. audio_eos_token (`Optional[str]`, *optional*, defaults to `"<|sound_eos|>"`): Special token used to represent the end of audio. max_audio_len (`int`, *optional*, defaults to 1200): Maximum length of audio sequences in seconds. Audio longer than this will be truncated. Nc>X@lURU5UlXpl[TU]XUS9 XPlX`lURU5UlURU5Ul g)N) chat_template) audio_tokenconvert_tokens_to_idsaudio_token_id max_audio_lensuper__init__audio_bos_tokenaudio_eos_tokenaudio_bos_token_idaudio_eos_token_id) selffeature_extractor tokenizerr)r*r0r1r- __class__s r#r/MusicFlamingoProcessor.__init__Ssi''==kJ* *]S.."+"A"A/"R"+"A"A/"Rr"c2US- S-S-nUS- S-S-nU$)Nr)r4 audio_lengthsconv_output_lengthsaudio_tokens_lengthss r#_get_audio_token_length.MusicFlamingoProcessor._get_audio_token_lengthfs2,q0Q6: 3a 7A=A##r"c[R"[R"URS5U5Vs/sHoDR5PM sn5nUR U5n[ R "[ R"UR55n[U5HBupURURURU --UR-X5X'MD U$s snf)N) torchstacksplitsumr?recompileescaper* enumeratesubr0r1) r4text padding_maskper_sample_windowssr<r>audio_token_patterni audio_lengths r#_expand_audio_tokens+MusicFlamingoProcessor._expand_audio_tokensks ekk,BRBRSUBVXj6k$l6kUUW6k$lm #;;MJ jj43C3C)DE()=>OA)--$$t'7'7,'FFI]I]]DG ?  %msC1cZXR:HXR:H-XR:H-$N)r,r2r3)r4 input_idss r#_get_audio_tokens_mask-MusicFlamingoProcessor._get_audio_tokens_maskvs5 -- -333 5333 5 r"rLaudio output_labelskwargsreturnc UR"[4SURR0UD6nUSnUSnUR S5nUS:wa"[ UR RS35e[U[5(aU/nO=[U[[45(a[SU55(d [ S5e0n UGb[U5n[U5[U5:wa$[ S [U5S [U5S 35e[US UR R"-5n [UR$UR R"-5n /n /n UHn[UR&S 5n[)SX-S- U -5nUU :a;[*R-SXS - SSUR$SUR$S35 U nU R/U5 [1UUU -5n[3U5H.nUU -n[1US-U -U5nU R/UUU5 M0 M UR "U 40UD6n U R5S5nUU S'UR7UUU 5nUR"U40UD6n0UEU EnU(aHUSR95nSUUR;U5'SUUURR<:H'UUS'[?UUS9$)a Main method to prepare one or several text sequence(s) and audio waveform(s) for the model. This method expands `` placeholders in the text based on the post-pool frame counts of the audio windows, then tokenizes the provided strings as-is, and extracts log-mel features with [`WhisperFeatureExtractor`]. If `audio` is `None`, no audio processing is performed and the text is tokenized as-is (LM-only behavior). Args: text (`str` or `list[str]`): Input sequence or batch of sequences. audio (`np.ndarray` or `list[np.ndarray]`): Input audio or batch of audios as NumPy arrays. If provided, there must be as many `text` inputs as `audio` inputs. output_labels (bool, *optional*, default=False): Whether to return labels for training. Returns: [`BatchFeature`]: A dictionary with tokenized text (`input_ids`, `attention_mask`) and audio features (`input_features`, `input_features_mask`). tokenizer_init_kwargsrrrrz% only supports `return_tensors='pt'`.c3B# UHn[U[5v M g7frV) isinstancestr).0ts r# 2MusicFlamingoProcessor.__call__..s9[VZQR*Q:L:LVZszAInvalid input text. Please provide a string, or a list of stringszGot z text but z audios; they must match 1:1.rrr:zAudio duration (z.1fz s) exceeds zs; truncating to first zs.attention_maskinput_features_maskrWilabels)data tensor_type) _merge_kwargsrr6 init_kwargsget ValueErrorr7rrarblisttupleallrlenintr5 chunk_lengthr-shapemaxloggerwarningappendminrangepoprSclonerX pad_token_idr)r4rLrZr[r\ call_kwargsrrr audio_inputs window_size max_windowsrN flat_chunksaudio_el n_samplesn_wintime_caprQstartendrM text_inputsrjris r#__call__MusicFlamingoProcessor.__call__}s!:(( ( "&.."<"<  "-0 ">2 $)9: T ! 7 788]^_ _ dC 6DTD%=11c9[VZ9[6[6[`a a  &u-E4yCJ& 4D {*SZLHe!fggl?;d>T>T>a>aabKd00D4J4J4W4WWXK,. ,.K!q 12 A 7! ; KL;&NN*9O7T+TUX*YYdeiewewdxyPQUQcQcPddfg(E"))%0y%+*=>uA OEq1u 3X>C&&xc':;&"" 11+NNL'++,<=L2>L. /,,TF4..v6 7<@F6T^^888 9#DN>BBr"cURRnURRn[[R X-S/-55$)Nrh)r6model_input_namesr5rpdictfromkeys)r4 tok_names fea_namess r#r(MusicFlamingoProcessor.model_input_namessBNN44 **<< DMM)"7;P:Q"QRSSr")r0r2r1r3r*r,r-)Nzz <|sound_bos|>z <|sound_eos|>i)NF)rrrr__doc__r/r?rSrXr rprboolr rrrpropertyrbrr! __classcell__)r7s@r#r&r&9s:''S&$  $(%* ]C$y/)]CD ]Cd{ ]C 56 ]C  ]C~T49TTr"r&)rGnumpynp audio_utilsrrfeature_extraction_utilsrprocessing_utilsrrr tokenization_utils_baser utilsr r rC get_loggerrrxrr&__all__rr"r#rsi, 94HH00   H %#35"gT^gTT $ $r"