if __name__ == '__main__': os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # you can modify your file path file_train = './data/train.csv' file_test = './data/test.csv' embed_dim = 8 read_part = True sample_num = 6000000 test_si

ze = 1000000 batch_size = 1024 epochs = 5 hidden_units = [256, 128] learning_rate = 0.001 dropout_rate = 0.2 # Load data train_data, test_data, feature_columns = load_data(file_train, file_test, read_part, sample_num) # Preprocess data train_data, test_data = preprocess_data(train_data, test_data, feature_columns) # Build model model = build_model(feature_columns, embed_dim, hidden_units, learning_rate, dropout_rate) # Train model train_model(model, train_data, batch_size, epochs) # Evaluate model evaluate_model(model, test_data) # Save model save_model(model)