Fix bug in decoder

1 files changed, 24 insertions, 29 deletions

diff --git a/text_recognizer/model/greedy_decoder.py b/text_recognizer/model/greedy_decoder.py
index 5cbbb66..2c4c16e 100644
--- a/text_recognizer/model/greedy_decoder.py
+++ b/text_recognizer/model/greedy_decoder.py
@@ -25,34 +25,29 @@ class GreedyDecoder:
         img_features = self.network.encode(x)
 
         # Create a placeholder matrix for storing outputs from the network
-        indecies = torch.ones((bsz, self.max_output_len), dtype=torch.long).to(x.device)
+        indecies = (
+            torch.ones((bsz, self.max_output_len), dtype=torch.long, device=x.device)
+            * self.pad_index
+        )
         indecies[:, 0] = self.start_index
 
-        try:
-            for i in range(1, self.max_output_len):
-                tokens = indecies[:, :i]  # (B, Sy)
-                logits = self.network.decode(tokens, img_features)  # (B, C, Sy)
-                indecies_ = torch.argmax(logits, dim=1)  # (B, Sy)
-                indecies[:, i : i + 1] = indecies_[:, -1:]
-
-                # Early stopping of prediction loop if token is end or padding token.
-                if (
-                    (indecies[:, i - 1] == self.end_index)
-                    | (indecies[:, i - 1] == self.pad_index)
-                ).all():
-                    break
-
-            # Set all tokens after end token to pad token.
-            for i in range(1, self.max_output_len):
-                idx = (indecies[:, i - 1] == self.end_index) | (
-                    indecies[:, i - 1] == self.pad_index
-                )
-                indecies[idx, i] = self.pad_index
-
-            return indecies
-        except Exception:
-            # TODO: investigate this error more
-            print(x.shape)
-            # print(indecies)
-            print(indecies.shape)
-            print(img_features.shape)
+        for i in range(1, self.max_output_len):
+            tokens = indecies[:, :i]  # (B, Sy)
+            logits = self.network.decode(tokens, img_features)  # [ B, N, C ]
+            indecies_ = torch.argmax(logits, dim=2)  # [ B, N ]
+            indecies[:, i] = indecies_[:, -1]
+
+            # Early stopping of prediction loop if token is end or padding token.
+            if (
+                (indecies[:, i] == self.end_index) | (indecies[:, i] == self.pad_index)
+            ).all():
+                break
+
+        # Set all tokens after end token to pad token.
+        for i in range(1, self.max_output_len):
+            idx = (indecies[:, i - 1] == self.end_index) | (
+                indecies[:, i - 1] == self.pad_index
+            )
+            indecies[idx, i] = self.pad_index
+
+        return indecies