diff --git a/netam/dcsm.py b/netam/dcsm.py
index 3d952da8..efbd393e 100644
--- a/netam/dcsm.py
+++ b/netam/dcsm.py
@@ -305,19 +305,11 @@ def predictions_of_batch(self, batch):
         # Create mask for valid (non-ambiguous) codons.
         valid_mask = parent_indices != AMBIGUOUS_CODON_IDX  # Shape: [B, L]
 
-        # Now unsqueeze indices for scatter operation.
-        parent_indices = parent_indices.unsqueeze(-1)  # Shape: [B, L, 1]
-
-        # Zero out valid parent codon entries.
-        preds[valid_mask, :].scatter_(-1, parent_indices[valid_mask, :], 0.0)
-
-        # Sum non-parent probabilities for valid indices.
-        non_parent_sum = preds[valid_mask, :].sum(dim=-1, keepdim=True)
-
-        # Set parent probability for valid indices.
-        preds[valid_mask, :].scatter_(
-            -1, parent_indices[valid_mask, :], 1.0 - non_parent_sum
-        )
+        # Zero out valid parent codon entries, and then assign so it's 
+        # 1-(sum of the non-parent codons).
+        preds[valid_mask, parent_indices[valid_mask]] = 0.0
+        non_parent_sum = preds[valid_mask, :].sum(dim=-1)
+        preds[valid_mask, parent_indices[valid_mask]] = 1.0 - non_parent_sum
 
         # We have to clamp the predictions to avoid log(0) issues.
         preds = torch.clamp(preds, min=torch.finfo(preds.dtype).eps)