[{'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 sess:\nsess.run(tf.global_variables_initializer())\nnum_examples = len(X_train)\nprint("Training...")\nprint()\nfor i in range(EPOCHS):\nX_train, y_train = shuffle(X_train, y_train)\nfor offset in range(0, num_examples, BATCH_SIZE):\nend = offset + BATCH_SIZE\nbatch_x, batch_y = X_train[offset:end], y_train[offset:end]\nsess.run(training_operation, feed_dict={x: batch_x, y: batch_y})\nvalidation_accuracy = evaluate(X_validation, y_validation)\nprint("EPOCH {} ...".format(i+1))\nprint("Validation Accuracy = {:.3f}".format(validation_accuracy))\nprint()\nsaver.save(sess, \'./lenet\')\nprint("Model saved")'}, {'role': 'assistant', 'content': "['modelling', 'save_results']"}]