[{'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:with tf.Session() as sess:\nsess.run(init)\nfor epoch in range(training_epochs):\ntotal_batch = int(mnist.train.num_examples/batch_size)\nc=0.0\navg_cost=0.0\nfor i in range(total_batch):\nlearning_rate = min_learning_rate + (max_learning_rate - min_learning_rate) * math.exp(-i/decay_speed)\nbatch_X, batch_Y = mnist.train.next_batch(batch_size)\n_,c=sess.run([optimizer,cost], feed_dict={X:batch_X,Y_:batch_Y,lr: learning_rate,pkeep: 0.75})\navg_cost += c / total_batch\nprint("epchos {} cross entropy={}".format(epoch+1,avg_cost))\nprint("Optimization Finished!")\nprint( "Accuracy:", accuracy.eval({X: mnist.test.images, Y_: mnist.test.labels, pkeep: 1.0}))'}, {'role': 'assistant', 'content': 'modelling'}]