Update app.py

app.py

@@ -24,12 +24,6 @@ def stop_generation():
     return "Generation stopped."
 
 def CTXGen(X0, X1, X2, τ, g_num, model_name):
-    print(X0)
-    print(X1)
-    print(X2)
-    print(τ)
-    print(g_num)
-    print(model_name)
     global is_stopped
     is_stopped = False
 
@@ -41,7 +35,6 @@ def CTXGen(X0, X1, X2, τ, g_num, model_name):
     train_seq = train_seqs['Seq'].tolist()
     model = torch.load(save_path, map_location=torch.device('cpu'))
     model = model.to(device)
-    print(model)
 
     X3 = "X" * len(X0)
     msa_data = pd.read_csv('conoData_C0.csv') 
@@ -95,6 +88,7 @@ def CTXGen(X0, X1, X2, τ, g_num, model_name):
 
         start_time = time.time()
         while count < gen_num:
+            gen_len = len(X0)
             if is_stopped:
                 return pd.DataFrame(), "output.csv"
 
@@ -102,7 +96,6 @@ def CTXGen(X0, X1, X2, τ, g_num, model_name):
                 break
 
             seq = [f"{X1}|{X2}|{X3}|{X4}|{X5}|{X6}"]
-            print(seq)
             vocab_mlm.token_to_idx["X"] = 4
 
             padded_seq, _, _, _ = get_paded_token_idx_gen(vocab_mlm, seq, new_seq)
@@ -110,9 +103,7 @@ def CTXGen(X0, X1, X2, τ, g_num, model_name):
 
             gen_length = len(input_text)
             length = gen_length - sum(1 for x in input_text if x != '[MASK]')
-            print(input_text)
             for i in range(length):
-                print(i)
                 if is_stopped:
                     return pd.DataFrame(), "output.csv"
                 
@@ -135,7 +126,6 @@ def CTXGen(X0, X1, X2, τ, g_num, model_name):
                 new_seq = padded_seq
 
             generated_seq = input_text
-            print(generated_seq)
         
             generated_seq[1] = "[MASK]"
             input_ids = vocab_mlm.__getitem__(generated_seq)