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Helper function to read an audio file through ffmpeg. 1Zf32leZffmpegz-izpipe:0z-acz-arz-fz -hide_bannerz -loglevelquietzpipe:1)stdinstdoutzFffmpeg was not found but is required to load audio files from filenamerzMalformed soundfile) subprocessPopenPIPEFileNotFoundError ValueError communicatenpZ frombufferZfloat32shape) r r aracZformat_for_conversionZffmpeg_commandZffmpeg_processZ output_streamZ out_bytesZaudiorj/var/www/html/Darija-Ai-API/env/lib/python3.8/site-packages/transformers/pipelines/audio_classification.py ffmpeg_reads6 rcsbeZdZdZfddZeejee fdfdd Z ddd Z d d Z d d Z dddZZS)AudioClassificationPipelinea Audio classification pipeline using any `AutoModelForAudioClassification`. This pipeline predicts the class of a raw waveform or an audio file. In case of an audio file, ffmpeg should be installed to support multiple audio formats. Example: ```python >>> from transformers import pipeline >>> classifier = pipeline(model="superb/wav2vec2-base-superb-ks") >>> classifier("https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/1.flac") [{'score': 0.997, 'label': '_unknown_'}, {'score': 0.002, 'label': 'left'}, {'score': 0.0, 'label': 'yes'}, {'score': 0.0, 'label': 'down'}, {'score': 0.0, 'label': 'stop'}] ``` Learn more about the basics of using a pipeline in the [pipeline tutorial](../pipeline_tutorial) This pipeline can currently be loaded from [`pipeline`] using the following task identifier: `"audio-classification"`. See the list of available models on [huggingface.co/models](https://huggingface.co/models?filter=audio-classification). cs@d|d<tj|||jdkr2td|jd|tdS)Ntop_kptzThe z is only available in PyTorch.)super__init__Z frameworkr __class__Zcheck_model_typer )selfargskwargsr&rrr%]s  z$AudioClassificationPipeline.__init__)inputsc stj|f|S)a Classify the sequence(s) given as inputs. 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