[{'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:training_epochs = 400\nbatch_size      = 100\ndisplay_step    = 40\nsess = tf.Session()\nsess.run(init)\nfor epoch in range(training_epochs):\navg_cost = 0.\nnum_batch = int(ntrain/batch_size)+1\nfor i in range(num_batch):\nrandidx = np.random.randint(ntrain, size=batch_size)\nbatch_xs = trainimg[randidx, :]\nbatch_ys = trainlabel[randidx, :]\nsess.run(optm, feed_dict={x: batch_xs, y: batch_ys\n, keepratio:0.5})\navg_cost += sess.run(cost, feed_dict={x: batch_xs, y: batch_ys\n, keepratio:1.})/num_batch\nif epoch % display_step == 0 or epoch == training_epochs-1:\nprint("Epoch: %03d/%03d cost: %.9f" %\n(epoch, training_epochs, avg_cost))\ntrain_acc = sess.run(accr, feed_dict={x: batch_xs\n, y: batch_ys, keepratio:1.})\nprint(" Training accuracy: %.3f" % (train_acc))\ntest_acc = sess.run(accr, feed_dict={x: testimg\n, y: testlabel, keepratio:1.})\nprint(" Test accuracy: %.3f" % (test_acc))\nprint("Optimization Finished!")'}, {'role': 'assistant', 'content': 'modelling'}]