o pi @sdZddlmZddlZddlmmZddejdeejfddZ ddejdejdeejd ejfd d Z ddejdejdeejd ejfd d Z  ddejdejdeejdeejd ejf ddZ dS)z0Frame-weighted versions of common loss functions)OptionalNtargetweightcCsF|jd}|dur!|jd|kr!tj|dd|ddddd}|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). NlinearF)sizemode align_corners)shapeF interpolate transpose)rr num_framesrM/home/ubuntu/.local/lib/python3.10/site-packages/pyannote/audio/utils/loss.pyr s  r predictionreturncCsZt|jdkr |jdd}|durt||St||d}tj||||jdS)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 rdimNr)lenr unsqueezer binary_cross_entropyfloatr expand)rrrrrrr;s  rcCslt|jdkr |jdd}tj||dd}|dur t|St||d |j}t ||t |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) reductionNr) rr rr mse_lossrtorchmeanr rsum)rrrlossesrrrras  r class_weightcCsp|jd}tj|d||d|dd|j}|dur"t|St||djdd}t||t|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)rrNrr) r r nll_lossviewrr r squeezer!)rrr#r num_classesr"rrrr%s   r%)N)NN) __doc__typingrrtorch.nn.functionalnn functionalr Tensorr rrr%rrrrsL  ) +