Hi i am running a dji manifold2, which contains a NVIDIA Jetson TX2, however it tells me CUDA device not found, even though there is CUDA 9 installed !
Command: python3 track.py --source 0 --show-vid
Loading weights from deep_sort_pytorch/deep_sort/deep/checkpoint/ckpt.t7... Done!
Traceback (most recent call last):
File "track.py", line 243, in <module>
detect(opt)
File "track.py", line 51, in detect
device = select_device(opt.device)
File "/media/dji/80GBstore/targetTrack/mikelbrostromNov2021/Yolov5_DeepSort_Pytorch/yolov5/utils/torch_utils.py", line 65, in select_device
assert torch.cuda.is_available(), f'CUDA unavailable, invalid device {device} requested' # check availability
AssertionError: CUDA unavailable, invalid device 0 requested
Python version and pip list
Python 3.8.9 (default, Apr 3 2021, 01:02:10)
[GCC 5.4.0 20160609] on linux
Type "help", "copyright", "credits" or "license" for more information.
torch 1.8.0
torchaudio 0.10.1
torchvision 0.11.1
Drivers query
/usr/local/cuda/samples/1_Utilities/deviceQuery$ ./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: "NVIDIA Tegra X2"
CUDA Driver Version / Runtime Version 9.0 / 9.0
CUDA Capability Major/Minor version number: 6.2
Total amount of global memory: 7839 MBytes (8219348992 bytes)
( 2) Multiprocessors, (128) CUDA Cores/MP: 256 CUDA Cores
GPU Max Clock rate: 1301 MHz (1.30 GHz)
Memory Clock rate: 1600 Mhz
Memory Bus Width: 128-bit
L2 Cache Size: 524288 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: 32768
Warp size: 32
Maximum number of threads per multiprocessor: 2048
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 1 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: Yes
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 / 0 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 9.0, CUDA Runtime Version = 9.0, NumDevs = 1
Result = PASS
nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Sun_Nov_19_03:16:56_CST_2017
Cuda compilation tools, release 9.0, V9.0.252
nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Sun_Nov_19_03:16:56_CST_2017
Cuda compilation tools, release 9.0, V9.0.252
My system
DJI Manifold 2
NVIDIA Jetson TX2
ARMv8 Processor rev 3 (v8l) × 4 ARMv8 Processor rev 0 (v8l) × 2
NVIDIA Tegra X2 (nvgpu)/integrated
64-bit
Extra debugging as requested:
>>> import torch
>>> print(torch.version.cuda)
None
>>> torch.cuda.current_device()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/media/dji/80GBstore/pyenvs/newpy38/lib/python3.8/site-packages/torch/cuda/__init__.py", line 388, in current_device
_lazy_init()
File "/media/dji/80GBstore/pyenvs/newpy38/lib/python3.8/site-packages/torch/cuda/__init__.py", line 164, in _lazy_init
raise AssertionError("Torch not compiled with CUDA enabled")
AssertionError: Torch not compiled with CUDA enabled
>>> torch.cuda.device(0)
<torch.cuda.device object at 0x7fa871ad00>
The odd thing is, i have also attempted to install CUDA-enabled versions of torch from torch’s website, and this is what i got, after trying on virtual environments for python3.7 and python3.8
pip install torch-1.1.0-cp37-cp37m-linux_x86_64.whl
ERROR: torch-1.1.0-cp37-cp37m-linux_x86_64.whl is not a supported wheel on this platform.
pip install torch-1.0.1.post2-cp37-cp37m-linux_x86_64.whl
ERROR: torch-1.0.1.post2-cp37-cp37m-linux_x86_64.whl is not a supported wheel on this platform.
pip install torch-1.7.0+cu92-cp38-cp38-linux_x86_64.whl
ERROR: torch-1.7.0+cu92-cp38-cp38-linux_x86_64.whl is not a supported wheel on this platform.
pip install torch-1.7.1+cu92-cp39-cp39-linux_x86_64.whl
ERROR: torch-1.7.1+cu92-cp39-cp39-linux_x86_64.whl is not a supported wheel on this platform.
pip install torch-1.7.1+cpu-cp39-cp39-linux_x86_64.whl
ERROR: torch-1.7.1+cpu-cp39-cp39-linux_x86_64.whl is not a supported wheel on this platform.
Here are the python run virtual environments
Python 3.8.9 (default, Apr 3 2021, 01:02:10)
[GCC 5.4.0 20160609] on linux
Type "help", "copyright", "credits" or "license" for more information.
Python 3.7.10 (default, Feb 20 2021, 21:21:24)
[GCC 5.4.0 20160609] on linux
Type "help", "copyright", "credits" or "license" for more information.
Could anyone advise what could be the problem ?
-
Why cant CUDA-compatible version of torch be installed ?
-
Are there any updates I have to do before this can be done ?