Update app.py

app.py

@@ -18,8 +18,6 @@ def load_model():
 
 interpreter, text_preprocessor, label_encoder, tokenizer = load_model()
 
-def softmax(x):
-    return tf.exp(x) / tf.math.reduce_sum(tf.exp(x))
 
 def inference(text):
     tflite_pred = "Can't Predict"
@@ -35,9 +33,8 @@ def inference(text):
         interpreter.set_tensor(input_details[1]["index"], input_ids)
         interpreter.invoke()
         tflite_pred = interpreter.get_tensor(output_details["index"])[0]
-        tflite_pred = softmax(tflite_pred)
         tflite_pred_argmax = np.argmax(tflite_pred)
-        tflite_pred = f"{label_encoder.inverse_transform([tflite_pred_argmax])[0]}"
+        tflite_pred = f"{label_encoder.inverse_transform([tflite_pred_argmax])[0]} ({str(np.round(tflite_pred[tflite_pred_argmax], 5))})"
     return tflite_pred
 
 
@@ -45,8 +42,6 @@ def main():
     st.title("Sentiment Analysis")
     review = st.text_area("Enter Review:", "", height=200)
     if st.button("Submit"):
-        # result = "Can't Predict"
-        # if len(review.strip()) > 0:
         result = inference(review)
         if result.find("positive") >=0 :
             st.success(f"{result}")