[{'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:tf.reset_default_graph()\nsess = tf.Session()\nwith tf.variable_scope("model", reuse=False):\ntrain_model = Model(X_train.shape[0], X_train.shape[1], phase = Phase.Train)\nwith tf.variable_scope("model", reuse=True):\nvalidation_model = Model(X_validate.shape[0], X_validate.shape[1], phase = Phase.Validation)\nwith tf.variable_scope("model", reuse=True):\npredict_model = Model(X_validate.shape[0], X_validate.shape[1], phase = Phase.Predict)\nsess.run(tf.global_variables_initializer())\nfor i in range(10):\nepoch_loss, _ = sess.run([train_model.loss, train_model.train_op],\n{train_model.x: X_train, train_model.y: Y_train})\naccuracy, = sess.run([validation_model.accuracy],\n{validation_model.x: X_validate, validation_model.y: Y_validate})\nprint(epoch_loss, accuracy)'}, {'role': 'assistant', 'content': "['evaluation', 'modelling']"}]