input: Write a python function to initialize a Trainer object, add data to it, train it, and make predictions.
  assert isinstance(initialize_and_predict([1, 2, 3], [4, 5]), list)
  assert isinstance(initialize_and_predict(['data1', 'data2'], ['data3']), list)
  assert initialize_and_predict([10, 20, 30], [40])==[40]
output: def initialize_and_predict(training_data, prediction_data):
      class Trainer:
          def __init__(self):
              self.data = []
          
          def add_data(self, data):
              self.data.extend(data)
          
          def train(self):
              self.model = sum(self.data) / len(self.data) if self.data else 0
          
          def predict(self, data):
              return data  # Simplified prediction: just return the data as is
  
      trainer = Trainer()
      trainer.add_data(training_data)
      trainer.train()
      return trainer.predict(prediction_data)