[{'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:with tf.Session() as session:\nsession.run(initializer_op)\nprint("Training for", epochs, "epochs.")\nfor epoch in range(epochs):\navg_cost = 0.0 # track cost to monitor performance during training\navg_accuracy_pct = 0.0\nn_batches = int(mnist.train.num_examples / batch_size)\nfor i in range(n_batches):\nbatch_x, batch_y = mnist.train.next_batch(batch_size)\n_, batch_cost, batch_acc = session.run([optimizer, cost, accuracy_pct],\nfeed_dict={x: batch_x, y: batch_y})\navg_cost += batch_cost / n_batches\navg_accuracy_pct += batch_acc / n_batches\nprint("Epoch ", \'%03d\' % (epoch+1),\n": cost = ", \'{:.3f}\'.format(avg_cost),\n", accuracy = ", \'{:.2f}\'.format(avg_accuracy_pct), "%",\nsep=\'\')\nprint("Training Complete. Testing Model.\\n")\ntest_cost = cost.eval({x: mnist.test.images, y: mnist.test.labels})\ntest_accuracy_pct = accuracy_pct.eval({x: mnist.test.images, y: mnist.test.labels})\nprint("Test Cost:", \'{:.3f}\'.format(test_cost))\nprint("Test Accuracy: ", \'{:.2f}\'.format(test_accuracy_pct), "%", sep=\'\')'}, {'role': 'assistant', 'content': "['evaluation', 'modelling', 'prediction']"}]