From 6f4c1108f07ead33bf6da21675fdb2765e0fc133 Mon Sep 17 00:00:00 2001 From: erogol Date: Wed, 3 Jun 2020 12:33:53 +0200 Subject: [PATCH] suppress pylint no-self-use for loss layers --- vocoder/layers/losses.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/vocoder/layers/losses.py b/vocoder/layers/losses.py index fb4e85d4..22e2fb54 100644 --- a/vocoder/layers/losses.py +++ b/vocoder/layers/losses.py @@ -77,6 +77,7 @@ class MultiScaleSTFTLoss(torch.nn.Module): class MultiScaleSubbandSTFTLoss(MultiScaleSTFTLoss): """ Multiscale STFT loss for multi band model outputs """ + # pylint: disable=no-self-use def forward(self, y_hat, y): y_hat = y_hat.view(-1, 1, y_hat.shape[2]) y = y.view(-1, 1, y.shape[2]) @@ -85,6 +86,7 @@ class MultiScaleSubbandSTFTLoss(MultiScaleSTFTLoss): class MSEGLoss(nn.Module): """ Mean Squared Generator Loss """ + # pylint: disable=no-self-use def forward(self, score_fake): loss_fake = torch.mean(torch.sum(torch.pow(score_fake, 2), dim=[1, 2])) return loss_fake @@ -92,6 +94,7 @@ class MSEGLoss(nn.Module): class HingeGLoss(nn.Module): """ Hinge Discriminator Loss """ + # pylint: disable=no-self-use def forward(self, score_fake): loss_fake = torch.mean(F.relu(1. + score_fake)) return loss_fake @@ -104,6 +107,7 @@ class HingeGLoss(nn.Module): class MSEDLoss(nn.Module): """ Mean Squared Discriminator Loss """ + # pylint: disable=no-self-use def forward(self, score_fake, score_real): loss_real = torch.mean(torch.sum(torch.pow(score_real - 1.0, 2), dim=[1, 2])) loss_fake = torch.mean(torch.sum(torch.pow(score_fake, 2), dim=[1, 2])) @@ -113,6 +117,7 @@ class MSEDLoss(nn.Module): class HingeDLoss(nn.Module): """ Hinge Discriminator Loss """ + # pylint: disable=no-self-use def forward(self, score_fake, score_real): loss_real = torch.mean(F.relu(1. - score_real)) loss_fake = torch.mean(F.relu(1. + score_fake)) @@ -121,6 +126,7 @@ class HingeDLoss(nn.Module): class MelganFeatureLoss(nn.Module): + # pylint: disable=no-self-use def forward(self, fake_feats, real_feats): loss_feats = 0 for fake_feat, real_feat in zip(fake_feats, real_feats):