Update transformer models

2 files changed, 7 insertions, 6 deletions

diff --git a/text_recognizer/models/transformer.py b/text_recognizer/models/transformer.py
index dbdc7f2..0acc30a 100644
--- a/text_recognizer/models/transformer.py
+++ b/text_recognizer/models/transformer.py
@@ -1,10 +1,11 @@
 """PyTorch Lightning model for base Transformers."""
-from typing import Tuple, Set
+from typing import Tuple, Type, Set
 
 import attr
 import torch
 from torch import Tensor
 
+from text_recognizer.data.base_mapping import AbstractMapping
 from text_recognizer.models.metrics import CharacterErrorRate
 from text_recognizer.models.base import BaseLitModel
 
@@ -13,6 +14,8 @@ from text_recognizer.models.base import BaseLitModel
 class TransformerLitModel(BaseLitModel):
     """A PyTorch Lightning model for transformer networks."""
 
+    mapping: Type[AbstractMapping] = attr.ib()
+
     max_output_len: int = attr.ib(default=451)
     start_token: str = attr.ib(default="<s>")
     end_token: str = attr.ib(default="<e>")
diff --git a/text_recognizer/models/vq_transformer.py b/text_recognizer/models/vq_transformer.py
index 339ce09..b419e97 100644
--- a/text_recognizer/models/vq_transformer.py
+++ b/text_recognizer/models/vq_transformer.py
@@ -1,10 +1,11 @@
 """PyTorch Lightning model for base Transformers."""
-from typing import Tuple
+from typing import Tuple, Type
 
 import attr
 import torch
 from torch import Tensor
 
+from text_recognizer.data.base_mapping import AbstractMapping
 from text_recognizer.models.transformer import TransformerLitModel
 
 
@@ -12,6 +13,7 @@ from text_recognizer.models.transformer import TransformerLitModel
 class VqTransformerLitModel(TransformerLitModel):
     """A PyTorch Lightning model for transformer networks."""
 
+    mapping: Type[AbstractMapping] = attr.ib()
     alpha: float = attr.ib(default=1.0)
 
     def forward(self, data: Tensor) -> Tensor:
@@ -30,8 +32,6 @@ class VqTransformerLitModel(TransformerLitModel):
     def validation_step(self, batch: Tuple[Tensor, Tensor], batch_idx: int) -> None:
         """Validation step."""
         data, targets = batch
-
-        # Compute the loss.
         logits, commitment_loss = self.network(data, targets[:, :-1])
         loss = self.loss_fn(logits, targets[:, 1:]) + self.alpha * commitment_loss
         self.log("val/loss", loss, prog_bar=True)
@@ -47,8 +47,6 @@ class VqTransformerLitModel(TransformerLitModel):
     def test_step(self, batch: Tuple[Tensor, Tensor], batch_idx: int) -> None:
         """Test step."""
         data, targets = batch
-
-        # Compute the text prediction.
         pred = self(data)
         self.test_cer(pred, targets)
         self.log("test/cer", self.test_cer, on_step=False, on_epoch=True, prog_bar=True)