How to use the fastprogress.fastprogress.IN_NOTEBOOK function in fastprogress

ax.set_ylabel("Loss")
        ax.set_xlabel("Learning Rate")
        ax.set_xscale('log')
        ax.xaxis.set_major_formatter(plt.FormatStrFormatter('%.0e'))
        if suggestion:
            try: mg = (np.gradient(np.array(losses))).argmin()
            except:
                print("Failed to compute the gradients, there might not be enough points.")
                return
            print(f"Min numerical gradient: {lrs[mg]:.2E}")
            ax.plot(lrs[mg],losses[mg],markersize=10,marker='o',color='red')
            self.min_grad_lr = lrs[mg]
            ml = np.argmin(losses)
            print(f"Min loss divided by 10: {lrs[ml]/10:.2E}")
        if ifnone(return_fig, defaults.return_fig): return fig
        if not IN_NOTEBOOK: plot_sixel(fig)