diff --git a/src/cdtools/reconstructors/base.py b/src/cdtools/reconstructors/base.py
index 45c806c..1184a52 100644
--- a/src/cdtools/reconstructors/base.py
+++ b/src/cdtools/reconstructors/base.py
@@ -164,7 +164,8 @@ class Reconstructor:
         for inputs, patterns in self.data_loader:
             if hasattr(self.model, 'loss_normalizer') and \
                     self.model.loss_normalizer is not None:
-                self.model.loss_normalizer.accumulate(patterns)
+                self.model.loss_normalizer.accumulate(
+                    patterns, mask=self.model.mask)
             N += 1
 
             def closure():
diff --git a/src/cdtools/tools/losses/losses.py b/src/cdtools/tools/losses/losses.py
index 5b304fc..bb65858 100644
--- a/src/cdtools/tools/losses/losses.py
+++ b/src/cdtools/tools/losses/losses.py
@@ -347,13 +347,13 @@ class SimplePoissonNLLNormalizer(object):
         
         """
         if not self.first_pass_complete:
+            self.offset += poisson_nll(patterns, patterns, mask=mask)
             if mask is None:
                 self.sum_nonzero += t.sum(patterns >= 1)
-                self.offset += poisson_nll(patterns, patterns)
             else:
                 masked_pats = patterns.masked_select(mask)
                 self.sum_nonzero += t.sum(masked_pats >= 1)
-                self.offset += poisson_nll(masked_pats, masked_pats)
+                
 
     
     def normalize_loss(self, loss):
@@ -373,7 +373,7 @@ class SimplePoissonNLLNormalizer(object):
         if not self.first_pass_complete:
             self.normalization = 0.5 * self.sum_nonzero
             self.first_pass_complete = True
-        
+
         return (loss - self.offset) / self.normalization