PLL approach

app.py

@@ -174,7 +174,25 @@ def greet(X, ny):
 #         else:
 #             astr+=mock.capitalize()     
     er = er+" (with PLL value of: "+str(vali)+")"
-    return er
+    return er, vali
+
+def meet(X):
+    tot_pll = 100.00
+    print_str = ""
+    fin_out = "The highest confidence prediction is: "
+    add_out = ""
+    for r in range(6):
+        er, pll = greet(X, 6-r)
+        print_str+= er
+        print_str+='\n'
+        if pll >= tot_pll:
+            break
+        else:
+            add_out = er
+            tot_pll = pll
+    print_str= print_str+fin_out+add_out
+    return print_str
+            
 title = "Rename a variable in a Java class"
 description = """This model is a fine-tuned GraphCodeBERT model fine-tuned to output higher-quality variable names for Java classes. Long classes are handled by the 
 model. Replace any variable name with a "[MASK]" to get an identifier renaming.
@@ -200,7 +218,7 @@ ex.printStackTrace();
             }
         }
     }
-}""", "0"], ["""import java.net.*;
+}"""], ["""import java.net.*;
 import java.io.*;
 
 public class s {
@@ -218,7 +236,7 @@ public class s {
             if ([MASK] != null) [MASK].close();
         }
     }
-}""", "2"], ["""import java.io.*;
+}"""], ["""import java.io.*;
 import java.util.*;
 
 public class y {
@@ -235,13 +253,13 @@ public class y {
             e.printStackTrace();
         }
     }
-}""", "2"]]
+}"""]]
 # We instantiate the Textbox class
 textbox = gr.Textbox(label="Type Java code snippet:", placeholder="replace variable with [MASK]", lines=10)
-textbox1 = gr.Textbox(label="Number of tokens in name:", placeholder="0 for randomly sampled number of tokens",lines=1)
+#textbox1 = gr.Textbox(label="Number of tokens in name:", placeholder="0 for randomly sampled number of tokens",lines=1)
 
 gr.Interface(title = title, description = description, examples = ex, fn=greet, inputs=[
-        textbox,textbox1
+        textbox
     ], outputs="text").launch()