前言:
利用while True:的方法後，已經能夠以少次數的 epochs 來重複儲存模型，但至於總共訓練了幾次，我將在之後新增方法

程式碼:

if os.path.exists(DATASET_PATH):
    if os.path.exists(DATASET_PATH + WEIGHTS_FINAL):
        print(WEIGHTS_FINAL + "模型存在，將繼續訓練模型")
        # net_final.save(WEIGHTS_FINAL)
        new_net_final = load_model(WEIGHTS_FINAL)
        while True :
            new_net_final.fit(train_batches,
                              steps_per_epoch = train_batches.samples // BATCH_SIZE,
                              validation_data = valid_batches,
                              validation_steps = valid_batches.samples // BATCH_SIZE,
                              epochs = NUM_EPOCHS)
            # 儲存訓練好的模型
            print("儲存訓練模型")
            new_net_final.save(WEIGHTS_FINAL)
    else:
        print(WEIGHTS_FINAL + '模型不存在，將新建訓練模型')
        # 訓練模型
        while True :
            net_final.fit(train_batches,
                          steps_per_epoch = train_batches.samples // BATCH_SIZE,
                          validation_data = valid_batches,
                          validation_steps = valid_batches.samples // BATCH_SIZE,
                          epochs = NUM_EPOCHS)
            # 儲存訓練好的模型
            print("儲存訓練模型")
            net_final.save(WEIGHTS_FINAL)
else:
    print(WEIGHTS_FINAL + '路徑不存在，請確認路徑')