[{'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 style_loss(style, combination):\nS = gram_matrix(style)\nC = gram_matrix(combination)\nchannels = 3\nsize = height * width\nreturn backend.sum(backend.square(S - C)) / (4. * (channels ** 2) * (size ** 2))\nfeature_layers = ['block1_conv2', 'block2_conv2',\n'block3_conv3', 'block4_conv3',\n'block5_conv3']\nfor layer_name in feature_layers:\nlayer_features = layers[layer_name]\nstyle_features = layer_features[1, :, :, :]\ncombination_features = layer_features[2, :, :, :]\nsl = style_loss(style_features, combination_features)\nloss += (style_weight / len(feature_layers)) * sl"}, {'role': 'assistant', 'content': "['modelling']"}]