o ziB@sHddlZddlmZddlmZGdddejZGdddejZdS) N)nn) AudioSignalcsBeZdZdZd dedeffdd Zded effd d ZZ S) L1LossaML1 Loss between AudioSignals. Defaults to comparing ``audio_data``, but any attribute of an AudioSignal can be used. Parameters ---------- attribute : str, optional Attribute of signal to compare, defaults to ``audio_data``. weight : float, optional Weight of this loss, defaults to 1.0. audio_data? attributeweightc s"||_||_tjdi|dS)N)rr super__init__)selfrr kwargs __class__r O/home/ubuntu/.local/lib/python3.10/site-packages/audiotools/metrics/distance.pyr szL1Loss.__init__xycs0t|trt||j}t||j}t||S)a  Parameters ---------- x : AudioSignal Estimate AudioSignal y : AudioSignal Reference AudioSignal Returns ------- torch.Tensor L1 loss between AudioSignal attributes. ) isinstancergetattrrr forward)r rrrr rrs   zL1Loss.forward)rr) __name__ __module__ __qualname____doc__strfloatr rr __classcell__r r rrrs rc sTeZdZdZ     ddededed ed ef fd d Zd edefddZ Z S) SISDRLossa% Computes the Scale-Invariant Source-to-Distortion Ratio between a batch of estimated and reference audio signals or aligned features. Parameters ---------- scaling : int, optional Whether to use scale-invariant (True) or signal-to-noise ratio (False), by default True reduction : str, optional How to reduce across the batch (either 'mean', 'sum', or none).], by default ' mean' zero_mean : int, optional Zero mean the references and estimates before computing the loss, by default True clip_min : int, optional The minimum possible loss value. Helps network to not focus on making already good examples better, by default None weight : float, optional Weight of this loss, defaults to 1.0. TmeanNrscaling reduction zero_meanclip_minr cs,||_||_||_||_||_tdS)N)r r!r"r#r r r )r r r!r"r#r rr rr Ds zSISDRLoss.__init__rrcCsfd}t|tr|j}|j}n|}|}|jd}||ddddd}||ddddd}|jrA|jddd}|jddd}nd}d}||} ||} | djdd |} | | jdd |} |j rk| |  dnd} | | }| |}|djdd }|djdd }d t |||}|j durt j||j d }|jd kr|}|S|jd kr|}|S)Ng:0yE>rrT)dimkeepdim)r&i)minrsum)rrrshapereshapepermuter"rr*r unsqueezetorchlog10r#clampr!)r rreps references estimatesnbmean_reference mean_estimate _references _estimatesreferences_projectionreferences_on_estimatesscalee_truee_ressignalnoisesdrr r rrSsF     zSISDRLoss.forward)TrTNr) rrrrintrrr rrrr r rrr-s&r)r/rrrModulerr r r rs   &