Remove coverage_vector from predict.py

Closes #53 (closed)

dan/predict/prediction.py

@@ -148,10 +148,6 @@ class DAN:
 
             features = self.encoder(input_tensor.float())
             features_size = features.size()
-            coverage_vector = torch.zeros(
-                (features.size(0), 1, features.size(2), features.size(3)),
-                device=self.device,
-            )
             pos_features = self.decoder.features_updater.get_pos_features(features)
             features = torch.flatten(pos_features, start_dim=2, end_dim=3).permute(
                 2, 0, 1
@@ -179,7 +175,6 @@ class DAN:
                 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,