Rename vq loss to commitment loss

1 files changed, 16 insertions, 18 deletions

diff --git a/text_recognizer/models/vqvae.py b/text_recognizer/models/vqvae.py
index 56229b3..92f28ad 100644
--- a/text_recognizer/models/vqvae.py
+++ b/text_recognizer/models/vqvae.py
@@ -11,7 +11,7 @@ from text_recognizer.models.base import BaseLitModel
 class VQVAELitModel(BaseLitModel):
     """A PyTorch Lightning model for transformer networks."""
 
-    latent_loss_weight: float = attr.ib(default=0.25)
+    commitment: float = attr.ib(default=0.25)
 
     def forward(self, data: Tensor) -> Tensor:
         """Forward pass with the transformer network."""
@@ -21,37 +21,35 @@ class VQVAELitModel(BaseLitModel):
         """Training step."""
         data, _ = batch
 
-        reconstructions, vq_loss = self(data)
+        reconstructions, commitment_loss = self(data)
+
         loss = self.loss_fn(reconstructions, data)
-        loss = loss + self.latent_loss_weight * vq_loss
+        loss = loss + self.commitment * commitment_loss
 
-        self.log("train/vq_loss", vq_loss)
+        self.log("train/commitment_loss", commitment_loss)
         self.log("train/loss", loss)
-
-        # self.train_acc(reconstructions, data)
-        # self.log("train/acc", self.train_acc, on_step=False, on_epoch=True)
         return loss
 
     def validation_step(self, batch: Tuple[Tensor, Tensor], batch_idx: int) -> None:
         """Validation step."""
         data, _ = batch
-        reconstructions, vq_loss = self(data)
+
+        reconstructions, commitment_loss = self(data)
+
         loss = self.loss_fn(reconstructions, data)
-        loss = loss + self.latent_loss_weight * vq_loss
+        loss = loss + self.commitment * commitment_loss
 
-        self.log("val/vq_loss", vq_loss)
+        self.log("val/commitment_loss", commitment_loss)
         self.log("val/loss", loss, prog_bar=True)
 
-        # self.val_acc(reconstructions, data)
-        # self.log("val/acc", self.val_acc, on_step=False, on_epoch=True, prog_bar=True)
-
     def test_step(self, batch: Tuple[Tensor, Tensor], batch_idx: int) -> None:
         """Test step."""
         data, _ = batch
-        reconstructions, vq_loss = self(data)
+
+        reconstructions, commitment_loss = self(data)
+
         loss = self.loss_fn(reconstructions, data)
-        loss = loss + self.latent_loss_weight * vq_loss
-        self.log("test/vq_loss", vq_loss)
+        loss = loss + self.commitment * commitment_loss
+
+        self.log("test/commitment_loss", commitment_loss)
         self.log("test/loss", loss)
-        # self.test_acc(reconstructions, data)
-        # self.log("test/acc", self.test_acc, on_step=False, on_epoch=True)