Removing the option for configuring prior loss, the durations predicted are not so good then

configs/model/matcha.yaml

@@ -12,4 +12,3 @@ spk_emb_dim: 64
 n_feats: 80
 data_statistics: ${data.data_statistics}
 out_size: null # Must be divisible by 4
-prior_loss: true

matcha/models/matcha_tts.py

@@ -34,7 +34,6 @@ class MatchaTTS(BaseLightningClass):  # 🍵
         out_size,
         optimizer=None,
         scheduler=None,
-        prior_loss=True,
     ):
         super().__init__()
 
@@ -45,7 +44,6 @@ class MatchaTTS(BaseLightningClass):  # 🍵
         self.spk_emb_dim = spk_emb_dim
         self.n_feats = n_feats
         self.out_size = out_size
-        self.prior_loss = prior_loss
 
         if n_spks > 1:
             self.spk_emb = torch.nn.Embedding(n_spks, spk_emb_dim)
@@ -230,10 +228,7 @@ class MatchaTTS(BaseLightningClass):  # 🍵
         # Compute loss of the decoder
         diff_loss, _ = self.decoder.compute_loss(x1=y, mask=y_mask, mu=mu_y, spks=spks, cond=cond)
 
-        if self.prior_loss:
-            prior_loss = torch.sum(0.5 * ((y - mu_y) ** 2 + math.log(2 * math.pi)) * y_mask)
-            prior_loss = prior_loss / (torch.sum(y_mask) * self.n_feats)
-        else:
-            prior_loss = 0
+        prior_loss = torch.sum(0.5 * ((y - mu_y) ** 2 + math.log(2 * math.pi)) * y_mask)
+        prior_loss = prior_loss / (torch.sum(y_mask) * self.n_feats)
 
         return dur_loss, prior_loss, diff_loss