Remove coverage_vector from training.py

dan/manager/training.py

@@ -1247,10 +1247,6 @@ class Manager(OCRManager):
             else:
                 features = self.models["encoder"](x)
             features_size = features.size()
-            coverage_vector = torch.zeros(
-                (features.size(0), 1, features.size(2), features.size(3)),
-                device=self.device,
-            )
             pos_features = self.models["decoder"].features_updater.get_pos_features(
                 features
             )
@@ -1279,7 +1275,6 @@ class Manager(OCRManager):
                 confidence_scores.append(
                     torch.max(torch.softmax(pred[:, :], dim=1), dim=1).values
                 )
-                coverage_vector = torch.clamp(coverage_vector + weights, 0, 1)
                 predicted_tokens = torch.cat(
                     [
                         predicted_tokens,