the GUI can‘t work about torch-ngp HOT 4 CLOSED

On Fri, Apr 8, 2022 at 1:21 PM alittle-cike ***@***.***> wrote: yes,I mean that GUI windows are very stuck, both before and after training. I use the lego data, CUDA_VISIBLE_DEVICES=0 python main_nerf.py data/lego --workspace trial_nerf --mode blender --gui --radius 1 When the training starts, I try to move the angle to view the 3D model, but the GUI window is very stuck (it looks like the FPS is very low) and I can't move. i have two GPUs=RTX2080TI, Device 0: "NVIDIA GeForce RTX 2080 Ti" CUDA Driver Version / Runtime Version 11.4 / 11.3 CUDA Capability Major/Minor version number: 7.5 Total amount of global memory: 11019 MBytes (11554717696 bytes) (068) Multiprocessors, (064) CUDA Cores/MP: 4352 CUDA Cores GPU Max Clock rate: 1545 MHz (1.54 GHz) Memory Clock rate: 7000 Mhz Memory Bus Width: 352-bit L2 Cache Size: 5767168 bytes Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384) Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers Total amount of constant memory: 65536 bytes Total amount of shared memory per block: 49152 bytes Total shared memory per multiprocessor: 65536 bytes Total number of registers available per block: 65536 Warp size: 32 Maximum number of threads per multiprocessor: 1024 Maximum number of threads per block: 1024 Max dimension size of a thread block (x,y,z): (1024, 1024, 64) Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535) Maximum memory pitch: 2147483647 bytes Texture alignment: 512 bytes Concurrent copy and kernel execution: Yes with 3 copy engine(s) Run time limit on kernels: Yes Integrated GPU sharing Host Memory: No Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Disabled Device supports Unified Addressing (UVA): Yes Device supports Managed Memory: Yes Device supports Compute Preemption: Yes Supports Cooperative Kernel Launch: Yes Supports MultiDevice Co-op Kernel Launch: Yes Device PCI Domain ID / Bus ID / location ID: 0 / 23 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) > Device 1: "NVIDIA GeForce RTX 2080 Ti" CUDA Driver Version / Runtime Version 11.4 / 11.3 CUDA Capability Major/Minor version number: 7.5 Total amount of global memory: 11016 MBytes (11551440896 bytes) (068) Multiprocessors, (064) CUDA Cores/MP: 4352 CUDA Cores GPU Max Clock rate: 1545 MHz (1.54 GHz) Memory Clock rate: 7000 Mhz Memory Bus Width: 352-bit L2 Cache Size: 5767168 bytes Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384) Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers Total amount of constant memory: 65536 bytes Total amount of shared memory per block: 49152 bytes Total shared memory per multiprocessor: 65536 bytes Total number of registers available per block: 65536 Warp size: 32 Maximum number of threads per multiprocessor: 1024 Maximum number of threads per block: 1024 Max dimension size of a thread block (x,y,z): (1024, 1024, 64) Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535) Maximum memory pitch: 2147483647 bytes Texture alignment: 512 bytes Concurrent copy and kernel execution: Yes with 3 copy engine(s) Run time limit on kernels: Yes Integrated GPU sharing Host Memory: No Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Disabled Device supports Unified Addressing (UVA): Yes Device supports Managed Memory: Yes Device supports Compute Preemption: Yes Supports Cooperative Kernel Launch: Yes Supports MultiDevice Co-op Kernel Launch: Yes Device PCI Domain ID / Bus ID / location ID: 0 / 101 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) > Peer access from NVIDIA GeForce RTX 2080 Ti (GPU0) -> NVIDIA GeForce RTX 2080 Ti (GPU1) : No Peer access from NVIDIA GeForce RTX 2080 Ti (GPU1) -> NVIDIA GeForce RTX 2080 Ti (GPU0) : No ------------------------------ thank you — Reply to this email directly, view it on GitHub <#46 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AGFKL2TOJ6WRE27PRX5JCYLVD6645ANCNFSM5SZOQIMA> . You are receiving this because you commented.Message ID: ***@***.***>