Update app.py

app.py

@@ -364,14 +364,14 @@ with open('model_google.pkl', 'rb') as f:
 
 def Test_model(text, Model):
     #print(text)
-    window_size = 10
+    windows_size = 10
     word_list = text_to_wordlist(text)
     #print(word_list)
     sequences = tokenizer.texts_to_sequences([word_list])
     sequences_input = list(itertools.chain(*sequences))
     
-    if len(sequences_input) <= window_size:
-        sequences_input = pad_sequences([sequences_input], value=0, padding="post", maxlen=window_size).tolist()
+    if len(sequences_input) <= windows_size_size:
+        sequences_input = pad_sequences([sequences_input], value=0, padding="post", maxlen=windows_size).tolist()
         #print(sequences_input)
         input_a = np.asarray(sequences_input)
         pred = Modell.predict(input_a, batch_size=None, verbose=0, steps=None)
@@ -380,8 +380,8 @@ def Test_model(text, Model):
         #print(labels[predicted_class])
     else:
         predictions = []
-        for i in range(len(sequences_input) - window_size + 1):
-            window_input = sequences_input[i : i + window_size]
+        for i in range(len(sequences_input) - windows_size + 1):
+            window_input = sequences_input[i : i + windows_size]
             #print(window_input)
             input_a = np.asarray([window_input])
             pred = Modell.predict(input_a, batch_size=None, verbose=0, steps=None)
@@ -404,8 +404,8 @@ def predict(text):
   word_list = text_to_wordlist(text)
   sequences = tokenizer.texts_to_sequences([word_list])
   sequences_input = list(itertools.chain(*sequences))
-  if len(sequences_input) <= window_size:
-    sequences_input = pad_sequences([sequences_input], value=0, padding="post", maxlen=window_size).tolist()
+  if len(sequences_input) <= windows_size:
+    sequences_input = pad_sequences([sequences_input], value=0, padding="post", maxlen=windows_size).tolist()
     #print(sequences_input)
     input_a = np.asarray(sequences_input)
     pred = Modell.predict(input_a, batch_size=None, verbose=0, steps=None)
@@ -414,8 +414,8 @@ def predict(text):
     #print(labels[predicted_class])
   else:
     predictions = []
-    for i in range(len(sequences_input) - window_size + 1):
-        window_input = sequences_input[i : i + window_size]
+    for i in range(len(sequences_input) - windows_size + 1):
+        window_input = sequences_input[i : i + windows_size]
         #print(window_input)
         input_a = np.asarray([window_input])
         pred = Modell.predict(input_a, batch_size=None, verbose=0, steps=None)