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difference between "padded_grad" and "torch.norm(grads, dim=-1)" when perform densification

Same question => Solved The shape of tensor grads is (N, 1) where N is the total number of points. So torch.norm(grads, dim=-1) doesn't change the gradient values

How can I visualize the Gaussians after optimization?

Same question... Do we have to implement gaussian-shape visualizer ourselves?