[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': 'Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:w1 = tf.Variable(tf.truncated_normal([5, 5, 3, l1], stddev=0.1))  # 5x5 patch, 3 input channel, K output channels\nb1 = tf.Variable(tf.random_normal([l1]))\nw2 = tf.Variable(tf.truncated_normal([5, 5, l1, l2], stddev=0.1))\nb2 = tf.Variable(tf.random_normal([l2]))\nw3 = tf.Variable(tf.truncated_normal([4, 4, l2, l3], stddev=0.1))\nb3 = tf.Variable(tf.random_normal([l3]))\nw4 = tf.Variable(tf.truncated_normal([4, 4, l3,l4], stddev=0.1))\nb4 = tf.Variable(tf.random_normal([l4]))\nw5 = tf.Variable(tf.truncated_normal([7 * 7 * l4, l5], stddev=0.1))\nb5 = tf.Variable(tf.random_normal([l5]))\nw = tf.Variable(tf.truncated_normal([l5, num_classes], stddev=0.1))\nb = tf.Variable(tf.random_normal([num_classes]))'}, {'role': 'assistant', 'content': 'modelling'}]