o ¡¿¯i;ã@s,ddlmZddlmZGdd„deƒZdS)é)Ú AbsEnhLoss)ÚAbsLossWrappercs0eZdZddef‡fdd„ Zifdd„Z‡ZS)Ú DPCLSolverçð?Ú criterioncstƒ ¡||_||_dS)N)ÚsuperÚ__init__rÚweight)Úselfrr ©Ú __class__©úY/home/ubuntu/.local/lib/python3.10/site-packages/espnet2/enh/loss/wrappers/dpcl_solver.pyrs  zDPCLSolver.__init__cCsDd|vsJ‚| ||d¡ ¡}tƒ}| ¡||jj<| ¡|ifS)aëA naive DPCL solver Args: ref (List[torch.Tensor]): [(batch, ...), ...] x n_spk inf (List[torch.Tensor]): [(batch, ...), ...] others (List): other data included in this solver e.g. "tf_embedding" learned embedding of all T-F bins (B, T * F, D) Returns: loss: (torch.Tensor): minimum loss with the best permutation stats: (dict), for collecting training status others: reserved Ú tf_embedding)rÚmeanÚdictÚdetachÚname)r ÚrefÚinfÚothersÚlossÚstatsr r rÚforward s zDPCLSolver.forward)r)Ú__name__Ú __module__Ú __qualname__rrrÚ __classcell__r r r rrsrN)Ú$espnet2.enh.loss.criterions.abs_lossrÚ%espnet2.enh.loss.wrappers.abs_wrapperrrr r r rÚs