Dutzel
commented
5 years ago This is the current state of the CUDA Device Query:
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "GeForce RTX 2080" CUDA Driver Version / Runtime Version 10.1 / 9.0 CUDA Capability Major/Minor version number: 7.5 Total amount of global memory: 7951 MBytes (8337227776 bytes) MapSMtoCores for SM 7.5 is undefined. Default to use 64 Cores/SM MapSMtoCores for SM 7.5 is undefined. Default to use 64 Cores/SM (46) Multiprocessors, ( 64) CUDA Cores/MP: 2944 CUDA Cores GPU Max Clock rate: 1710 MHz (1.71 GHz) Memory Clock rate: 7000 Mhz Memory Bus Width: 256-bit L2 Cache Size: 4194304 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 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 Supports Cooperative Kernel Launch: Yes Supports MultiDevice Co-op Kernel Launch: Yes Device PCI Domain ID / Bus ID / location ID: 0 / 8 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
TontonTremblay
g1y5x3
avinashsen707
Hi, for my master thesis, I am interested in trying out this report for object recognition. Unfortunately, I am getting every time the same error even after updating cuda and torch as required.
Here is the error message:
Loading DOPE parameters from '/home/dustin/catkin_ws/src/dope/config/config_pose.yaml'... Parameters loaded. Loading DOPE model '/home/dustin/catkin_ws/src/dope/weights/soup_60.pth'... /home/dustin/.local/lib/python2.7/site-packages/torch/cuda/init.py:114: UserWarning: Found GPU0 GeForce RTX 2080 which requires CUDA_VERSION >= 9000 for optimal performance and fast startup time, but your PyTorch was compiled with CUDA_VERSION 8000. Please install the correct PyTorch binary using instructions from http://pytorch.org
warnings.warn(incorrect_binary_warn % (d, name, 9000, CUDA_VERSION)) Model loaded in 468.114012003 seconds. Running DOPE... (Listening to camera topic: '/dope/webcam_rgb_raw') Ctrl-C to stop Traceback (most recent call last): File "/home/dustin/catkin_ws/src/dope/src/dope.py", line 271, in
run_dope_node(params)
File "/home/dustin/catkin_ws/src/dope/src/dope.py", line 208, in run_dope_node
config_detect
File "/home/dustin/catkin_ws/src/dope/src/inference/detector.py", line 265, in detect_object_in_image
out, seg = net_model(image_torch)
File "/home/dustin/.local/lib/python2.7/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, kwargs)
File "/home/dustin/.local/lib/python2.7/site-packages/torch/nn/parallel/data_parallel.py", line 112, in forward
return self.module(*inputs[0], *kwargs[0])
File "/home/dustin/.local/lib/python2.7/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(input, kwargs)
File "/home/dustin/catkin_ws/src/dope/src/inference/detector.py", line 105, in forward
out1 = self.vgg(x)
File "/home/dustin/.local/lib/python2.7/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(*input, *kwargs)
File "/home/dustin/.local/lib/python2.7/site-packages/torch/nn/modules/container.py", line 91, in forward
input = module(input)
File "/home/dustin/.local/lib/python2.7/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(input, **kwargs)
File "/home/dustin/.local/lib/python2.7/site-packages/torch/nn/modules/conv.py", line 301, in forward
self.padding, self.dilation, self.groups)
RuntimeError: CUDNN_STATUS_MAPPING_ERROR
Do you guys have any idea that I can do to fix this issue? I hope to hear from you, thank you very much!