input: Write a function to predict the class labels of a given set of data using a pre-trained DecisionTreeClassifier model. The function should accept a list of four features (Length, Width, Height, Weight) as input and return the predicted class label. The model has already been trained on a dataset that contains these four features and a corresponding class label.
  
  def predict(data):
      predicted_label = model.predict([data])
      return predicted_label
  
  assert predict([10, 20, 30, 40]) == 3
  assert predict([5, 15, 25, 35]) == 1
  assert predict([1, 2, 3, 4]) == 2
  assert predict([90, 80, 70, 60]) == 4
  assert predict([12, 13, 14, 15]) == 0
output: def predict(data):
      predicted_label = model.predict([data])
      return predicted_label[0]