fix divergence_exact's diagonal sum

[ventusff]

In run_nerf_helpers.py: L71 divergence_loss, the original code to calculate the diagonal of jacobian matrix is wrong.

I'm guessing since it's using divergence_approx function by default, this error does not affect the default training behavior.
But still it will affect the behavior when setting exact=true for training.

example:

jac[0,...]=
        [[  1.5425,   8.1350,   5.7477],
        [ -1.1500, -14.2937,  -9.5665],
        [ -0.5321,  11.8239,   5.3827]]

jac.view(jac.shape[0], -1)[0,...]=
         [  1.5425, 8.1350, 5.7477, -1.1500, -14.2937, -9.5665, -0.5321, 11.8239, 5.3827]

# wrong way
jac.view(jac.shape[0], -1)[0, :: jac.shape[1]]=
         [ 1.5425, -1.1500, -0.5321]

# correct way
jac.view(jac.shape[0], -1)[0, :: (jac.shape[1]+1)]=
         [  1.5425, -14.2937,   5.3827]

[edgar-tr]

Thank you!