[{'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:init = tf.global_variables_initializer()\nwith tf.Session() as sess:\nsess.run(init)\nprint("Training loss:",sess.run([mean_square],feed_dict={X:InputX1train,Y:InputY1train}))\nfor i in range(training_iterations):\nsess.run([train_step],feed_dict={X:InputX1train,Y:InputY1train})\nif i%display_iterations ==0:\nprint("Training loss is:",sess.run([mean_square],feed_dict={X:InputX1train,Y:InputY1train}),"at itertion:",i)\nprint("Validation loss is:",sess.run([mean_square],feed_dict={X:InputX1v,Y:InputY1v}),"at itertion:",i)\nsave_path = saver.save(sess, "/tmp/earthquake_model.ckpt")\nprint("Model saved in file: %s" % save_path)\nprint("Final training loss:",sess.run([mean_square],feed_dict={X:InputX1train,Y:InputY1train}))\nprint("Final validation loss:",sess.run([mean_square],feed_dict={X:InputX1v,Y:InputY1v}))'}, {'role': 'assistant', 'content': "['evaluation', 'modelling']"}]