def METHOD_NAME(nn, x_test, y_test, input_scaler, output_scaler):
    scaled_x_test = input_scaler.scale(x_test)
    scaled_y_test_hat = nn.predict(scaled_x_test.to_numpy())
    scaled_y_test_hat = pd.DataFrame(
        data=scaled_y_test_hat, columns=["EnthMol", "VapFrac"]
    )
    y_test_hat = output_scaler.unscale(scaled_y_test_hat)
    y_test_hat.rename(
        columns={"EnthMol": "EnthMol_hat", "VapFrac": " VapFrac_hat"}, inplace=True
    )
    df = pd.concat([x_test, y_test, y_test_hat], axis=1)
    df.plot(
        x="Temperature_K", y=["EnthMol", "EnthMol_hat"], marker=".", linestyle="none"
    )
    plt.savefig("fit_{}.png".format(nn.name))
    df.to_csv("fit_{}.csv".format(nn.name), index=False)