diff --git a/tetragono/tetragono/sampling_neural_state/observer.py b/tetragono/tetragono/sampling_neural_state/observer.py
index 38933ce0..51fab1de 100644
--- a/tetragono/tetragono/sampling_neural_state/observer.py
+++ b/tetragono/tetragono/sampling_neural_state/observer.py
@@ -76,11 +76,11 @@ def __exit__(self, exc_type, exc_val, exc_tb):
         if exc_type is not None:
             return False
         buffer = []
-        for name, observers in self._observer.items():
-            for positions in observers:
-                buffer.append(self._result_reweight[name][positions])
-                buffer.append(self._result_reweight_square[name][positions])
-                buffer.append(self._result_square_reweight_square[name][positions])
+        #for name, observers in self._observer.items():
+        #    for positions in observers:
+        #        buffer.append(self._result_reweight[name][positions])
+        #        buffer.append(self._result_reweight_square[name][positions])
+        #        buffer.append(self._result_square_reweight_square[name][positions])
         buffer.append(self._count)
         buffer.append(self._total_weight)
         buffer.append(self._total_weight_square)
@@ -104,11 +104,11 @@ def __exit__(self, exc_type, exc_val, exc_tb):
         self._total_weight_square = buffer.pop()
         self._total_weight = buffer.pop()
         self._count = buffer.pop()
-        for name, observers in reversed(self._observer.items()):
-            for positions in reversed(observers):
-                self._result_square_reweight_square[name][positions] = buffer.pop()
-                self._result_reweight_square[name][positions] = buffer.pop()
-                self._result_reweight[name][positions] = buffer.pop()
+        #for name, observers in reversed(self._observer.items()):
+        #    for positions in reversed(observers):
+        #        self._result_square_reweight_square[name][positions] = buffer.pop()
+        #        self._result_reweight_square[name][positions] = buffer.pop()
+        #        self._result_reweight[name][positions] = buffer.pop()
 
         if self._enable_gradient:
             allreduce_buffer(self._Delta)
@@ -381,11 +381,11 @@ def __call__(self, configurations, amplitudes, weights, multiplicities):
             self._total_log_ws += multiplicity * amplitude.abs().log().item()
 
             for name, observers in self._observer.items():
-                for positions in observers:
-                    to_save = result[batch_index][name][positions].real
-                    self._result_reweight[name][positions] += multiplicity * to_save * reweight
-                    self._result_reweight_square[name][positions] += multiplicity * to_save * reweight**2
-                    self._result_square_reweight_square[name][positions] += multiplicity * to_save**2 * reweight**2
+                # for positions in observers:
+                #     to_save = result[batch_index][name][positions].real
+                #     self._result_reweight[name][positions] += multiplicity * to_save * reweight
+                #     self._result_reweight_square[name][positions] += multiplicity * to_save * reweight**2
+                #     self._result_square_reweight_square[name][positions] += multiplicity * to_save**2 * reweight**2
                 to_save = whole_result[batch_index][name].real
                 self._whole_result_reweight[name] += multiplicity * to_save * reweight
                 self._whole_result_reweight_square[name] += multiplicity * to_save * reweight**2