Training data "T" condition

[RickyYXY]

I find that in your evaluation code, you add T as a condition by
T = T[None, None, :].repeat(n_samples, 1, 1).to(c.device)
c = torch.cat([c, T], dim=-1)
But in your training code, I can't find where you add the T condition.
In zero123/ldm/models/diffusion/ddpm.py, function get_input in class LatentDiffusion,
the variant T has never been used since
T = T[:bs].to(self.device),
which means the training cannot get any pose condition at all.
Is this a bug? Do you forget to add T condition here?
Thks

[RickyYXY]

I find the variant T, sorry to interupt