[{'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_conv_layer(layer, image):\nfeed_dict = {x: [image]}\nvalues = session.run(layer, feed_dict=feed_dict)\nnum_filters = values.shape[3]\nnum_grids = math.ceil(math.sqrt(num_filters))\nfig, axes = plt.subplots(num_grids, num_grids)\nfor i, ax in enumerate(axes.flat):\nif i<num_filters:\nimg = values[0, :, :, i]\nax.imshow(img, interpolation='nearest', cmap='binary')\nax.set_xticks([])\nax.set_yticks([])\nplt.show()\ndef plot_image(image):\nplt.imshow(image.reshape(img_shape),\ninterpolation='nearest',\ncmap='binary')\nplt.show()"}, {'role': 'assistant', 'content': "['result_visualization']"}]