[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': "Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:def generate_train(data,batch_size = 128):\nbatch_steering = np.zeros(batch_size)\nbatch_images = np.zeros((batch_size, new_col, new_row, 3))\nwhile 1:\nfor i_batch in range(batch_size):\ni = np.random.randint(len(data))\nline = data.iloc[[i]].reset_index()\nx,y = preprocess_image(line)\nbatch_images[i_batch] = x\nbatch_steering[i_batch] = y\nyield batch_images, batch_steering\ndef generate_validate(data):\nwhile 1:\nfor i in range(len(data)):\nline = data.iloc[[i]].reset_index()\nimage = cv2.imread(line['center'][0].strip())\nimage = cv2.cvtColor(image,cv2.COLOR_BGR2RGB)\nimage = np.array(resize_image(image))\nx = image.reshape(1, image.shape[0], image.shape[1], image.shape[2])\ny = np.array([[line['steering'][0]]])\nyield x, y"}, {'role': 'assistant', 'content': "['data_preprocessing']"}]