clean up forward hooks on exception (#4778)

CHANGELOG.md

@@ -15,6 +15,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
+- Fixed a bug where forward hooks were not cleaned up with saliency interpreters if there
+  was an exception.
 - Fixed the computation of saliency maps in the Interpret code when using mismatched indexing.
   Previously, we would compute gradients from the top of the transformer, after aggregation from
   wordpieces to tokens, which gives results that are not very informative.  Now, we compute gradients

allennlp/interpret/saliency_interpreters/integrated_gradient.py

@@ -88,9 +88,11 @@ def _integrate_gradients(self, instance: Instance) -> Dict[str, numpy.ndarray]:
             # Hook for modifying embedding value
             handles = self._register_hooks(alpha, embeddings_list, token_offsets)
 
-            grads = self.predictor.get_gradients([instance])[0]
-            for handle in handles:
-                handle.remove()
+            try:
+                grads = self.predictor.get_gradients([instance])[0]
+            finally:
+                for handle in handles:
+                    handle.remove()
 
             # Running sum of gradients
             if ig_grads == {}:

allennlp/interpret/saliency_interpreters/simple_gradient.py

@@ -30,9 +30,11 @@ def saliency_interpret_from_json(self, inputs: JsonDict) -> JsonDict:
 
             # Hook used for saving embeddings
             handles = self._register_hooks(embeddings_list, token_offsets)
-            grads = self.predictor.get_gradients([instance])[0]
-            for handle in handles:
-                handle.remove()
+            try:
+                grads = self.predictor.get_gradients([instance])[0]
+            finally:
+                for handle in handles:
+                    handle.remove()
 
             # Gradients come back in the reverse order that they were sent into the network
             embeddings_list.reverse()

allennlp/interpret/saliency_interpreters/smooth_gradient.py

@@ -72,8 +72,10 @@ def _smooth_grads(self, instance: Instance) -> Dict[str, numpy.ndarray]:
         total_gradients: Dict[str, Any] = {}
         for _ in range(self.num_samples):
             handle = self._register_forward_hook(self.stdev)
-            grads = self.predictor.get_gradients([instance])[0]
-            handle.remove()
+            try:
+                grads = self.predictor.get_gradients([instance])[0]
+            finally:
+                handle.remove()
 
             # Sum gradients
             if total_gradients == {}: