[{'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([6, 6, 1, K], stddev=0.1))  # 5x5 patch, 1 input channel, K output channels\nB1 = tf.Variable(tf.constant(0.1, tf.float32, [K]))\nW2 = tf.Variable(tf.truncated_normal([5, 5, K, L], stddev=0.1))\nB2 = tf.Variable(tf.constant(0.1, tf.float32, [L]))\nW3 = tf.Variable(tf.truncated_normal([4, 4, L, M], stddev=0.1))\nB3 = tf.Variable(tf.constant(0.1, tf.float32, [M]))\nW4 = tf.Variable(tf.truncated_normal([7 * 7 * M, N], stddev=0.1))\nB4 = tf.Variable(tf.constant(0.1, tf.float32, [N]))\nW5 = tf.Variable(tf.truncated_normal([N, 10], stddev=0.1))\nB5 = tf.Variable(tf.constant(0.1, tf.float32, [10]))'}, {'role': 'assistant', 'content': 'modelling'}]