Update app.py

app.py

@@ -402,26 +402,26 @@ 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()
-        #print(sequences_input)
-        input_a = np.asarray(sequences_input)
+  if len(sequences_input) <= window_size:
+    sequences_input = pad_sequences([sequences_input], value=0, padding="post", maxlen=window_size).tolist()
+    #print(sequences_input)
+    input_a = np.asarray(sequences_input)
+    pred = Modell.predict(input_a, batch_size=None, verbose=0, steps=None)
+    #print(pred)
+    predicted_class = np.argmax(pred)
+    #print(labels[predicted_class])
+  else:
+    predictions = []
+    for i in range(len(sequences_input) - window_size + 1):
+        window_input = sequences_input[i : i + window_size]
+        #print(window_input)
+        input_a = np.asarray([window_input])
         pred = Modell.predict(input_a, batch_size=None, verbose=0, steps=None)
         #print(pred)
-        predicted_class = np.argmax(pred)
-        #print(labels[predicted_class])
-    else:
-        predictions = []
-        for i in range(len(sequences_input) - window_size + 1):
-            window_input = sequences_input[i : i + window_size]
-            #print(window_input)
-            input_a = np.asarray([window_input])
-            pred = Modell.predict(input_a, batch_size=None, verbose=0, steps=None)
-            #print(pred)
-            predictions.append(pred)
-        accumulated_pred = np.sum(predictions, axis=0)
-        predicted_class = np.argmax(np.sum(accumulated_pred, axis=0))
-        #print(labels[predicted_class])
+        predictions.append(pred)
+    accumulated_pred = np.sum(predictions, axis=0)
+    predicted_class = np.argmax(np.sum(accumulated_pred, axis=0))
+    #print(labels[predicted_class])
 
   return labels[predicted_class]
 input_text = gr.inputs.Textbox(label="Enter a sentence")