change name of func

app.py

@@ -142,7 +142,7 @@ def mask_out(input_ids,pron_locs,option_locs,mask_id):
     # note annotations are shifted by 1 because special tokens were omitted
     return input_ids[:pron_locs[0]+1] + [mask_id for _ in range(len(option_locs))] + input_ids[pron_locs[-1]+2:]
 
-def run(interventions,batch_size,model,masked_ids_option_1,masked_ids_option_2,option_1_tokens,option_2_tokens,pron_locs):
+def run_intervention(interventions,batch_size,model,masked_ids_option_1,masked_ids_option_2,option_1_tokens,option_2_tokens,pron_locs):
     probs = []
     for masked_ids, option_tokens in zip([masked_ids_option_1, masked_ids_option_2],[option_1_tokens,option_2_tokens]]):
         input_ids = torch.tensor([
@@ -247,9 +247,9 @@ if __name__=='__main__':
             option_2_tokens = option_2_tokens_1
 
             interventions = [{'lay':[],'qry':[],'key':[],'val':[]} for i in range(num_layers)]
-            probs_original = run(interventions,1,model,masked_ids_option_1,masked_ids_option_2,option_1_tokens,option_2_tokens,pron_locs)
+            probs_original = run_intervention(interventions,1,model,masked_ids_option_1,masked_ids_option_2,option_1_tokens,option_2_tokens,pron_locs)
             st.write(probs_original)
 
             for layer_id in range(num_layers):
                 interventions = [create_interventions(16,['lay','qry','key','val'],num_heads) if i==layer_id else {'lay':[],'qry':[],'key':[],'val':[]} for i in range(num_layers)]
-                probs = run(interventions,num_heads,model,masked_ids_option_1,masked_ids_option_2,option_1_tokens,option_2_tokens,pron_locs)
+                probs = run_intervention(interventions,num_heads,model,masked_ids_option_1,masked_ids_option_2,option_1_tokens,option_2_tokens,pron_locs)