Open dengyuanjie opened 1 year ago
Hello, could you please explain the meaning of the weights here?
This coefficient is not included in the paper, and I have found that it is not necessary to calculate this weight in the test.py.
# calculate loss weighting coefficient if self.opt.weighted_loss: weight1 = torch.log1p(torch.norm(audio_mix_spec1[:,:,:-1,:], p=2, dim=1)).unsqueeze(1).repeat(1,2,1,1) weight1 = torch.clamp(weight1, 1e-3, 10) weight2 = torch.log1p(torch.norm(audio_mix_spec2[:,:,:-1,:], p=2, dim=1)).unsqueeze(1).repeat(1,2,1,1) weight2 = torch.clamp(weight2, 1e-3, 10) else: weight1 = None weight2 = None
Hello, could you please explain the meaning of the weights here?
This coefficient is not included in the paper, and I have found that it is not necessary to calculate this weight in the test.py.