[{'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:import tensorflow as tf\nfrom tensorflow.keras import backend as K\nfrom tensorflow.keras.models import Sequential\nfrom tensorflow.keras.layers import Dense\nfrom tensorflow.keras.optimizers import Adam, Nadam\nfrom tensorflow.keras.layers import Input, Embedding, Reshape, GlobalAveragePooling1D\nfrom tensorflow.keras.layers import Flatten, concatenate, Concatenate, Lambda, Dropout, SpatialDropout1D\nfrom tensorflow.keras.layers import Reshape, MaxPooling1D,BatchNormalization, AveragePooling1D, Conv1D\nfrom tensorflow.keras.layers import Activation, LeakyReLU\nfrom tensorflow.keras.optimizers import SGD, Adam, Nadam\nfrom tensorflow.keras.models import Model, load_model\nfrom tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint, ReduceLROnPlateau\nfrom tensorflow.keras.regularizers import l2, l1_l2\nfrom keras.losses import binary_crossentropy\n\nfrom sklearn.metrics import roc_auc_score\nfrom sklearn.metrics import average_precision_score\n\nimport matplotlib.pyplot as plt'}, {'role': 'assistant', 'content': 'helper_functions'}]