[{'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 plot_images(images, cls_true, cls_pred=None):\nassert len(images) == len(cls_true) == 9\nfig, axes = plt.subplots(3,3)\nfig.subplots_adjust(hspace=0.3, wspace=0.3)\nfor i, ax in enumerate(axes.flat):\nax.imshow(images[i].reshape(img_shape), cmap=\'binary\')\nif cls_pred is None:\nxlabel = "True: {0}".format(cls_true[i])\nelse:\nxlabel = "True: {0}, Pred: {1}".format(cls_true[i], cls_pred[i])\nax.set_xlabel(xlabel)\nax.set_xticks([])\nax.set_yticks([])\nplt.show()'}, {'role': 'assistant', 'content': "['data_exploration']"}]