fixed mixed_precision NaN (espnet#4236)

espnet2/gan_tts/vits/vits.py

@@ -3,6 +3,8 @@
 
 """VITS module for GAN-TTS task."""
 
+from contextlib import contextmanager
+from distutils.version import LooseVersion
 from typing import Any
 from typing import Dict
 from typing import Optional
@@ -37,6 +39,14 @@
     "hifigan_multi_scale_multi_period_discriminator": HiFiGANMultiScaleMultiPeriodDiscriminator,  # NOQA
 }
 
+if LooseVersion(torch.__version__) >= LooseVersion("1.6.0"):
+    from torch.cuda.amp import autocast
+else:
+    @contextmanager
+    def autocast(enabled=True):
+        """Define dummy function to be compatible with torch < 1.6.0."""
+        yield
+
 
 class VITS(AbsGANTTS):
     """VITS module (generator + discriminator).
@@ -398,18 +408,19 @@ def _forward_generator(
             p = self.discriminator(speech_)
 
         # calculate losses
-        mel_loss = self.mel_loss(speech_hat_, speech_)
-        kl_loss = self.kl_loss(z_p, logs_q, m_p, logs_p, z_mask)
-        dur_loss = torch.sum(dur_nll.float())
-        adv_loss = self.generator_adv_loss(p_hat)
-        feat_match_loss = self.feat_match_loss(p_hat, p)
-
-        mel_loss = mel_loss * self.lambda_mel
-        kl_loss = kl_loss * self.lambda_kl
-        dur_loss = dur_loss * self.lambda_dur
-        adv_loss = adv_loss * self.lambda_adv
-        feat_match_loss = feat_match_loss * self.lambda_feat_match
-        loss = mel_loss + kl_loss + dur_loss + adv_loss + feat_match_loss
+        with autocast(enabled=False):
+            mel_loss = self.mel_loss(speech_hat_, speech_)
+            kl_loss = self.kl_loss(z_p, logs_q, m_p, logs_p, z_mask)
+            dur_loss = torch.sum(dur_nll.float())
+            adv_loss = self.generator_adv_loss(p_hat)
+            feat_match_loss = self.feat_match_loss(p_hat, p)
+
+            mel_loss = mel_loss * self.lambda_mel
+            kl_loss = kl_loss * self.lambda_kl
+            dur_loss = dur_loss * self.lambda_dur
+            adv_loss = adv_loss * self.lambda_adv
+            feat_match_loss = feat_match_loss * self.lambda_feat_match
+            loss = mel_loss + kl_loss + dur_loss + adv_loss + feat_match_loss
 
         stats = dict(
             generator_loss=loss.item(),
@@ -504,8 +515,9 @@ def _forward_discrminator(
         p = self.discriminator(speech_)
 
         # calculate losses
-        real_loss, fake_loss = self.discriminator_adv_loss(p_hat, p)
-        loss = real_loss + fake_loss
+        with autocast(enabled=False):
+            real_loss, fake_loss = self.discriminator_adv_loss(p_hat, p)
+            loss = real_loss + fake_loss
 
         stats = dict(
             discriminator_loss=loss.item(),