I tried to run the code with the pre-trained models for Inference using the Google Colab reference notebook and by creating a docker image as well. However, I am facing the same issue in both the cases.
Creating output directory...
Launching processes...
Setting up PyTorch plugin "upfirdn2d_plugin"... Done.
Setting up PyTorch plugin "bias_act_plugin"... Done.
Setting up PyTorch plugin "filtered_lrelu_plugin"... Done.
==> resume from pretrained path /GET3D/get3d_release/shapenet_car.pt
==> generate
/GET3D/training/networks_get3d.py:430: UserWarning: torch.range is deprecated and will be removed in a future release because its behavior is inconsistent with Python's range builtin. Instead, use torch.arange, which produces values in [start, end).
camera_theta = torch.range(0, n_camera - 1, device=self.device).unsqueeze(dim=-1) / n_camera math.pi 2.0
[F glutil.cpp:338] eglInitialize() failedAborted
Hi Team,
I tried to run the code with the pre-trained models for Inference using the Google Colab reference notebook and by creating a docker image as well. However, I am facing the same issue in both the cases.
Creating output directory... Launching processes... Setting up PyTorch plugin "upfirdn2d_plugin"... Done. Setting up PyTorch plugin "bias_act_plugin"... Done. Setting up PyTorch plugin "filtered_lrelu_plugin"... Done. ==> resume from pretrained path /GET3D/get3d_release/shapenet_car.pt ==> generate /GET3D/training/networks_get3d.py:430: UserWarning: torch.range is deprecated and will be removed in a future release because its behavior is inconsistent with Python's range builtin. Instead, use torch.arange, which produces values in [start, end). camera_theta = torch.range(0, n_camera - 1, device=self.device).unsqueeze(dim=-1) / n_camera math.pi 2.0 [F glutil.cpp:338] eglInitialize() failed Aborted
Can you please guide me on how to fix this issue?