Training error on Custom dataset

[gwang-kim]

Hi,
I'm using XHumans Dataset which provide mesh. I rendered normal with camera poses and got error as following while training the model. Any insight would be helpful.

true_normal torch.Size([2048, 3, 3, 3]) tensor(0.9999) tensor(-1.0000)
comp_normal torch.Size([2048, 3, 3, 3]) tensor(0.4257, grad_fn=<MaxBackward1>) tensor(-0.6862, grad_fn=<MinBackward1>)
normal_loss 1.0001189708709717
eikonal_loss 0.0007976764463819563
mask_loss 2.1950364112854004

 16%|█████████████████▊                                                                                              | 796/5000 [00:21<01:52, 37.46it/s, loss=3.443e+00, s=4.836e-01, rm_step=7.248e-03, samples_per_ray=0.3]
Traceback (most recent call last):
  File "/home/bradleyk/project/SuperNormal/exp_runner.py", line 670, in <module>
    runner.train()
  File "/home/bradleyk/project/SuperNormal/exp_runner.py", line 186, in train
    if render_out['gradients'] is None:  # all rays are in the zero region of the occupancy grid
KeyError: 'gradients'

[xucao-42]

It looks like the forward pass in models/renderer.py has not been executed correctly. The renderer returns a dictionary, but it does not contain "gradients." You may check whether it's accidentally deleted, or you can try modify the line as if "gradients" in render_out