Correctly handle missing neighbor list

run.py

@@ -98,9 +98,10 @@ def get_mia_scores(
         neighbors = data[f"neighbors"]
         print("Loaded neighbors from cache!")
 
-    collected_neighbors = {
-        n_perturbation: [] for n_perturbation in n_perturbation_list
-    }
+    if neigh_config and neigh_config.dump_cache:
+        collected_neighbors = {
+            n_perturbation: [] for n_perturbation in n_perturbation_list
+        }
 
     recall_config = config.recall_config
     if recall_config:
@@ -129,8 +130,9 @@ def get_mia_scores(
                 detokenized_sample = [target_model.tokenizer.decode(s) for s in sample]
                 sample_information["detokenized"] = detokenized_sample
 
+            if neigh_config and neigh_config.dump_cache:
+                neighbors_within = {n_perturbation: [] for n_perturbation in n_perturbation_list}
             # For each substring
-            neighbors_within = {n_perturbation: [] for n_perturbation in n_perturbation_list}
             for i, substr in enumerate(sample):
                 # compute token probabilities for sample
                 s_tk_probs, s_all_probs = (