sanity_check issue with geodesic loss

[fenaux]

In order to avoid loss is Nan

In compute_geodesic_distance_from_two_matrices(m1, m2)
I changed
cos = torch.min(cos, torch.autograd.Variable(torch.ones(batch).cuda()) )
cos = torch.max(cos, torch.autograd.Variable(torch.ones(batch).cuda())*-1 )
to
cos = torch.min(cos, torch.autograd.Variable(torch.ones(batch).cuda()) * 0.9999)
cos = torch.max(cos, torch.autograd.Variable(torch.ones(batch).cuda()) * -0.9999 )

then training ran but after few iterations I got a constant error and the same for all models
Then I realized their is a problem as teta value can be negative and in model definition we have
def compute_geodesic_loss(self, gt_r_matrix, out_r_matrix):
theta = tools.compute_geodesic_distance_from_two_matrices(gt_r_matrix, out_r_matrix)
error = theta.mean()
return error
so if I am not wrong error can be negative

I tried
In compute_geodesic_distance_from_two_matrices(m1, m2)
at the end : return torch.abs( teta)

I now have a steady decrease of geodesic loss for all the models :)
after 100000 iterations
ortho6d 0.018
ortho5d 0.021
quaternion 0.162
euler 0.198
rodriguez 0.104
euler_sin_cos 0.066
Quaternion_half 0.041

[Frank-ZY-Dou]

You could have a check here: https://pytorch3d.readthedocs.io/en/latest/modules/transforms.html#pytorch3d.transforms.so3_relative_angle