Upload DPST.py with huggingface_hub

DPST.py

@@ -245,7 +245,7 @@ class DPST():
                 ordered.append(f)
         return ordered
 
-    def privatize(self, texts, epsilon=10, DP=True):
+    def privatize(self, texts, epsilon=10, DP=True, verbose=False):
         results = []
         for i, t in tqdm(enumerate(texts), total=len(texts)):
             triples = self.get_triples_ie(t)
@@ -253,6 +253,9 @@ class DPST():
                 results.append(t)
                 continue
 
+            if verbose:
+                print(f"\n  Extracted Triples : {triples}")
+
             if DP == True:
                 eps = epsilon / len(triples)
                 query_vectors = self.model.encode(triples, task="text-matching", truncate_dim=32, max_length=64)
@@ -267,6 +270,9 @@ class DPST():
                         candidates.append(near)
                 private_triples = [self.exponential(c, eps) for c in candidates]
 
+                if verbose:
+                    print(f"  Private Triples   : {private_triples}")
+
                 final = []
                 for p in private_triples:
                     m = p.split(" | ")
@@ -289,5 +295,5 @@ class DPST():
             generated = generated.split("Output text: ")[-1].strip().replace("\n", "")
             generated = generated.split("USER:")[0].strip().replace("\n", "")
             generated = generated.split("\t")[0].split("ASSISTANT")[0].split("USER")[0].split("###")[0].split("Note:")[0].split("Explanation:")[0].split("```")[0].split("EXPECTED_OUTPUT")[0]
-            results.append(generated.strip())    
+            results.append(generated.strip())
         return results