If my data is 6 dimension, how can I use this code to process it?

[SpiderDKing]

I wanna use this code to predict stocks, but my data shape is (n,6)，the example moons has only dimension 2, I can't do this:

        xline = torch.linspace(-1.5, 2.5, 100)
        yline = torch.linspace(-.75, 1.25, 100)
        xgrid, ygrid = torch.meshgrid(xline, yline)
        xyinput = torch.cat([xgrid.reshape(-1, 3), ygrid.reshape(-1, 3)], dim=1)

        with torch.no_grad():
            zgrid = flow.log_prob(xyinput).exp().reshape(100, 100)

        plt.contourf(xgrid.numpy(), ygrid.numpy(), zgrid.numpy())
        plt.title('iteration {}'.format(i + 1))
        plt.show()

[arturbekasov]

Hi @SpiderDKing. This is a package for building normalizing flows, a type of a generative model. Normalizing flows aren't very well suited to predictive tasks, so I am not sure how we can be of help, unfortunately. Cheers, Artur