diff --git a/src/torchjd/autogram/_engine.py b/src/torchjd/autogram/_engine.py
index 5aabcdc9..96610e38 100644
--- a/src/torchjd/autogram/_engine.py
+++ b/src/torchjd/autogram/_engine.py
@@ -169,11 +169,20 @@ def compute_gramian(self, output: Tensor) -> Tensor:
         """
 
         reshaped_output = output.reshape([-1])
-        return self._compute_square_gramian(reshaped_output)
 
-    def _compute_square_gramian(self, output: Tensor) -> Tensor:
         self._module_hook_manager.gramian_accumulation_phase = True
 
+        try:
+            square_gramian = self._compute_square_gramian(reshaped_output)
+        finally:
+            # Reset everything that has a state, even if the previous call raised an exception
+            self._module_hook_manager.gramian_accumulation_phase = False
+            self._gramian_accumulator.reset()
+            self._target_edges.reset()
+
+        return square_gramian
+
+    def _compute_square_gramian(self, output: Tensor) -> Tensor:
         leaf_targets = list(self._target_edges.get_leaf_edges({get_gradient_edge(output)}))
 
         def differentiation(_grad_output: Tensor) -> tuple[Tensor, ...]:
@@ -190,9 +199,4 @@ def differentiation(_grad_output: Tensor) -> tuple[Tensor, ...]:
         # have failed. So gramian is necessarily a valid Tensor here.
         gramian = cast(Tensor, self._gramian_accumulator.gramian)
 
-        # Reset everything that has a state
-        self._module_hook_manager.gramian_accumulation_phase = False
-        self._gramian_accumulator.reset()
-        self._target_edges.reset()
-
         return gramian