[{'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:def build_rnn(inputs, n_outputs, rnn_width, rnn_depth, keep_prob):\n"""\nDefines architecture of an RNN.\n@type inputs: tensorflow.Tensor\n@type n_outputs: int\n@type rnn_width: int\n@type rnn_depth: int\n@type keep_prob: tensorflow.Tensor\n@rtype: tuple(tensorflow.Tensor)\n"""\nbasic_cell = tf.contrib.rnn.BasicLSTMCell(rnn_width)\ndropout_cell = tf.contrib.rnn.DropoutWrapper(basic_cell, keep_prob)\nmulti_cell = tf.contrib.rnn.MultiRNNCell([dropout_cell for _ in range(rnn_depth)])\nbatch_size = tf.shape(inputs)[0]\ninitial_state = tf.identity(multi_cell.zero_state(batch_size, tf.float32),\nname=\'initial_state\')\nlstm_outputs, final_state = tf.nn.dynamic_rnn(multi_cell, inputs, dtype=tf.float32)\nfinal_state = tf.identity(final_state, name=\'final_state\')\npreds = tf.contrib.layers.fully_connected(lstm_outputs, n_outputs,\nactivation_fn=None)\npreds = tf.identity(preds, name=\'predictions\')\nreturn preds, initial_state, final_state'}, {'role': 'assistant', 'content': 'modelling'}]