Update app.py

app.py

@@ -140,7 +140,8 @@ def fit_outputs_constraints(x, hardness_target, ys_target, request: gr.Request):
     predictions = predict(x, request)
     error_hardness = np.sqrt(np.square(predictions[0]-float(hardness_target)))
     error_ys = np.sqrt(np.square(predictions[2]-float(ys_target)))
-    print(predictions, float(hardness_target), float(ys_target), error_hardness, error_ys)
+    print("Optimization step is ", predictions, float(hardness_target), float(ys_target),
+          error_hardness, error_ys)
     return error_hardness + error_ys
 
 def predict_inverse(hardness_target, ys_target, request: gr.Request):