Minor updates.

1 files changed, 8 insertions, 17 deletions

diff --git a/src/text_recognizer/networks/metrics.py b/src/text_recognizer/networks/metrics.py
index af9adb5..ffad792 100644
--- a/src/text_recognizer/networks/metrics.py
+++ b/src/text_recognizer/networks/metrics.py
@@ -6,28 +6,13 @@ from torch import Tensor
 from text_recognizer.networks import greedy_decoder
 
 
-def accuracy_ignore_pad(
-    output: Tensor,
-    target: Tensor,
-    pad_index: int = 79,
-    eos_index: int = 81,
-    seq_len: int = 97,
-) -> float:
-    """Sets all predictions after eos to pad."""
-    start_indices = torch.nonzero(target == eos_index, as_tuple=False).squeeze(1)
-    end_indices = torch.arange(seq_len, target.shape[0] + 1, seq_len)
-    for start, stop in zip(start_indices, end_indices):
-        output[start + 1 : stop] = pad_index
-
-    return accuracy(output, target)
-
-
-def accuracy(outputs: Tensor, labels: Tensor,) -> float:
+def accuracy(outputs: Tensor, labels: Tensor, pad_index: int = 53) -> float:
     """Computes the accuracy.
 
     Args:
         outputs (Tensor): The output from the network.
         labels (Tensor): Ground truth labels.
+        pad_index (int): Padding index.
 
     Returns:
         float: The accuracy for the batch.
@@ -36,6 +21,12 @@ def accuracy(outputs: Tensor, labels: Tensor,) -> float:
 
     _, predicted = torch.max(outputs, dim=-1)
 
+    # Mask out the pad tokens
+    mask = labels != pad_index
+
+    predicted *= mask
+    labels *= mask
+
     acc = (predicted == labels).sum().float() / labels.shape[0]
     acc = acc.item()
     return acc