[{'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:def main():\nif not os.path.exists(IRIS_TRAINING):\nraw = urlopen(IRIS_TRAINING_URL).read()\nwith open(IRIS_TRAINING, "w") as f:\nf.write(raw.decode(\'utf-8\'))\nif not os.path.exists(IRIS_TEST):\nraw = urlopen(IRIS_TEST_URL).read()\nwith open(IRIS_TEST, "w") as f:\nf.write(raw.decode(\'utf-8\'))\ntraining_set = tf.contrib.learn.datasets.base.load_csv_with_header(\nfilename = IRIS_TRAINING,\ntarget_dtype = np.int,\nfeatures_dtype = np.float32\n)\ntest_set = tf.contrib.learn.datasets.base.load_csv_with_header(\nfilename = IRIS_TEST,\ntarget_dtype = np.int,\nfeatures_dtype = np.float32\n)\nfeature_columns = [tf.contrib.layers.real_valued_column("", dimension = 4)]\nclassifier = tf.contrib.learn.DNNClassifier(feature_columns = feature_columns,\nhidden_units = [10, 20, 10],\nn_classes = 3,\nmodel_dir = "./iris_model"\n)\ndef get_train_inputs():\nx = tf.constant(training_set.data)\ny = tf.constant(training_set.target)\nreturn x, y\nclassifier.fit(input_fn = get_train_inputs, steps = 2000)\ndef get_test_inputs():\nx = tf.constant(test_set.data)\ny = tf.constant(test_set.target)\nreturn x, y\naccuracy_score = classifier.evaluate(input_fn = get_test_inputs, steps = 1)["accuracy"]\nprint("\\nTest Accuracy: {0: f}\\n".format(accuracy_score))\ndef new_samples():\nreturn np.array(\n[[6.4, 3.2, 4.5, 1.5],\n[5.8, 3.1, 5.0, 1.7]], dtype = np.float32)\npredictions = list(classifier.predict(input_fn = new_samples))\nprint(\n"New Sample, Class Prediction:    {}\\n".format(predictions))'}, {'role': 'assistant', 'content': 'modelling'}]