White line in demo on RTX 3090

[yuangan]

Hello, thank you for your great work. I run your demo and find the output has strange white lines as the video shows. Do you know the reason?

https://user-images.githubusercontent.com/12268263/220037152-d7f411a1-a8c3-494b-ae76-01663bbfd117.mp4

To make the environment work in RTX 3090, I updated the cudatoolkit to 11.3. And then I installed the following package:

PyTorch version: 1.11.0
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A

OS: Ubuntu 18.04.6 LTS (x86_64)
GCC version: (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
Clang version: Could not collect
CMake version: version 3.10.2
Libc version: glibc-2.27

Python version: 3.8.16 (default, Jan 17 2023, 23:13:24)  [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-4.15.0-191-generic-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: 11.3.58
GPU models and configuration: 
GPU 0: NVIDIA GeForce RTX 3090
GPU 1: NVIDIA GeForce RTX 3090
GPU 2: NVIDIA GeForce RTX 3090

Nvidia driver version: 465.19.01
cuDNN version: Probably one of the following:
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn.so.8
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_adv_train.so.8
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_ops_train.so.8
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] pytorch-lightning==1.5.0
[pip3] pytorch3d==0.7.2
[pip3] torch==1.11.0
[pip3] torchmetrics==0.11.1
[pip3] torchvision==0.12.0
[conda] blas                      1.0                         mkl    http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
[conda] cudatoolkit               11.3.1               ha36c431_9    nvidia
[conda] ffmpeg                    4.3                  hf484d3e_0    pytorch
[conda] mkl                       2021.4.0           h06a4308_640    http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
[conda] mkl-service               2.4.0            py38h7f8727e_0    http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
[conda] mkl_fft                   1.3.1            py38hd3c417c_0    http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
[conda] mkl_random                1.2.2            py38h51133e4_0    http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
[conda] numpy                     1.23.5           py38h14f4228_0    http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
[conda] numpy-base                1.23.5           py38h31eccc5_0    http://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
[conda] pytorch                   1.11.0          py3.8_cuda11.3_cudnn8.2.0_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch
[conda] pytorch-lightning         1.5.0                    pypi_0    pypi
[conda] pytorch-mutex             1.0                        cuda    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch
[conda] pytorch3d                 0.7.2                    pypi_0    pypi
[conda] torchmetrics              0.11.1                   pypi_0    pypi
[conda] torchvision               0.12.0               py38_cu113    https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch

[Alex-JYJ]

The same issue. Have you solved the problem? @yuangan

[wenduof]

The same issue. Looking forward to a solution.

[yuangan]

This might be because of the device of GPU. I tried 2080Ti, and the results were right.

[longxiang-ai]

The same issue. Looking forward to a solution.