Loading audiolm_pytorch/soundstream.py +1 −1 Original line number Diff line number Diff line Loading @@ -413,7 +413,7 @@ class SoundStream(nn.Module): if self.single_channel: real, fake = orig_x.clone(), recon_x.detach() stft_real_logits, stft_fake_logits = map(self.stft_discriminator, (real.requires_grad_(), fake)) stft_discr_loss = (hinge_discr_loss(stft_fake_logits.real, stft_real_logits.real) + hinge_discr_loss(stft_fake_logits.imag, stft_real_logits.imag)) / 2 stft_discr_loss = hinge_discr_loss(stft_fake_logits, stft_real_logits) if apply_grad_penalty: stft_grad_penalty = gradient_penalty(real, stft_discr_loss) Loading setup.py +1 −1 Original line number Diff line number Diff line Loading @@ -3,7 +3,7 @@ from setuptools import setup, find_packages setup( name = 'audiolm-pytorch', packages = find_packages(exclude=[]), version = '0.3.0', version = '0.3.1', license='MIT', description = 'AudioLM - Language Modeling Approach to Audio Generation from Google Research - Pytorch', author = 'Phil Wang', Loading Loading
audiolm_pytorch/soundstream.py +1 −1 Original line number Diff line number Diff line Loading @@ -413,7 +413,7 @@ class SoundStream(nn.Module): if self.single_channel: real, fake = orig_x.clone(), recon_x.detach() stft_real_logits, stft_fake_logits = map(self.stft_discriminator, (real.requires_grad_(), fake)) stft_discr_loss = (hinge_discr_loss(stft_fake_logits.real, stft_real_logits.real) + hinge_discr_loss(stft_fake_logits.imag, stft_real_logits.imag)) / 2 stft_discr_loss = hinge_discr_loss(stft_fake_logits, stft_real_logits) if apply_grad_penalty: stft_grad_penalty = gradient_penalty(real, stft_discr_loss) Loading
setup.py +1 −1 Original line number Diff line number Diff line Loading @@ -3,7 +3,7 @@ from setuptools import setup, find_packages setup( name = 'audiolm-pytorch', packages = find_packages(exclude=[]), version = '0.3.0', version = '0.3.1', license='MIT', description = 'AudioLM - Language Modeling Approach to Audio Generation from Google Research - Pytorch', author = 'Phil Wang', Loading