:j dZddlmZddlZddlmcmZd dejdeejfdZ d dejdejdeejdejfd Z d dejdejdeejdejfd Z ddejdejd eejdeejdejf d Z y)z0Frame-weighted versions of common loss functions)OptionalNtargetweightc|jd}|K|jd|k7r9tj|jdd|ddjdd}|S)aInterpolate weight to match target frame resolution Parameters ---------- target : torch.Tensor Target with shape (batch_size, num_frames) or (batch_size, num_frames, num_classes) weight : torch.Tensor, optional Frame weight with shape (batch_size, num_frames_weight, 1). Returns ------- weight : torch.Tensor Interpolated frame weight with shape (batch_size, num_frames, 1). linearF)sizemode align_corners)shapeF interpolate transpose)rr num_framess n/home/mcse/projects/srt_converter/srt-converter-venv/lib/python3.12/site-packages/pyannote/audio/utils/loss.pyrr sd aJ fll1o;   Q "  )Aq/  M predictionreturnc:t|jdk(r|jd}|$tj||j St ||}tj||j |j|jS)a Frame-weighted binary cross entropy Parameters ---------- prediction : torch.Tensor Prediction with shape (batch_size, num_frames, num_classes). target : torch.Tensor Target with shape (batch_size, num_frames) for binary or multi-class classification, or (batch_size, num_frames, num_classes) for multi-label classification. weight : (batch_size, num_frames, 1) torch.Tensor, optional Frame weight with shape (batch_size, num_frames, 1). Returns ------- loss : torch.Tensor rdimr)lenr unsqueezerbinary_cross_entropyfloatrexpand)rrrs rrr;s. 6<<A!!a!( ~%%j&,,.AAVF3%%  v}}V\\/J  rcxt|jdk(r|jd}tj||j d}|t j|St||j|j}t j||zt j|z S)a#Frame-weighted mean-squared error loss Parameters ---------- prediction : torch.Tensor Prediction with shape (batch_size, num_frames, num_classes). target : torch.Tensor Target with shape (batch_size, num_frames) for binary or multi-class classification, or (batch_size, num_frames, num_classes) for multi-label classification. weight : (batch_size, num_frames, 1) torch.Tensor, optional Frame weight with shape (batch_size, num_frames, 1). Returns ------- loss : torch.Tensor rrnone) reductionr) rr rrmse_lossrtorchmeanrrsum)rrrlossess rr"r"as. 6<<A!!a!( ZZ FLLNf EF~zz&!!VF3::6<<Hyy&)EIIf,===r class_weightc|jd}tj|jd||jd|dj|j}|t j |St ||jd}t j||zt j|z S)aFrame-weighted negative log-likelihood loss Parameters ---------- prediction : torch.Tensor Prediction with shape (batch_size, num_frames, num_classes). target : torch.Tensor Target with shape (batch_size, num_frames) class_weight : (num_classes, ) torch.Tensor, optional Class weight with shape (num_classes, ) weight : (batch_size, num_frames, 1) torch.Tensor, optional Frame weight with shape (batch_size, num_frames, 1). Returns ------- loss : torch.Tensor rr )rr!rr) r rnll_lossviewr#r$rsqueezer%)rrr'r num_classesr&s rr*r*s0""1%K ZZK( B d6<< ~zz&!!VF3;;;Byy&)EIIf,===r)N)NN) __doc__typingrr#torch.nn.functionalnn functionalrTensorrrr"r*rrr5s07  hu||.D<&*#  # LL#  U\\ "#  \\ # R&*%> %> LL%> U\\ "%> \\ %>V,0%) -> -> LL->5<<(-> U\\ " ->  \\ ->r