o ei@s.dZddlZddlZedjZdddZdS)z # Authors: * Szu-Wei, Fu 2021 * Mirco Ravanelli 2020 * Samuele Cornell 2020 * Hwidong Na 2020 * Yan Gao 2020 * Titouan Parcollet 2020 NfloatmeancCstj|dd}tj|dd}|jd}t|}td|D]c}||dt|||jdf}||dt|||jdf}tj||ddd} tj|ddddt} | || } || } tj| dddtj| dddt} dt| t||<q|d kr| S| S) aCompute the si_snr score and return -1 * that score. This function can be used as a loss function for training with SGD-based updates. Arguments --------- y_pred_batch : torch.Tensor The degraded (enhanced) waveforms. y_true_batch : torch.Tensor The clean (reference) waveforms. lens : torch.Tensor The relative lengths of the waveforms within the batch. reduction : str The type of reduction ("mean" or "batch") to use. Returns ------- Computed si_snr loss. )dimrT)rkeepdim r) torchsqueezeshapezerosrangeintsumsmallVallog10r) y_pred_batch y_true_batchlens reduction batch_sizeSI_SNRis_target s_estimatedots_target_energyproje_noisesi_snr_beforelogr!_/home/ubuntu/transcripts/venv/lib/python3.10/site-packages/speechbrain/nnet/loss/si_snr_loss.py si_snr_losss$  ""  r#)r)__doc__numpynpr finfoepsrr#r!r!r!r"s