I understand there's a similar question asked but that was for a conda environment. I am running a non-conda environment for python 3.7.10, 3.8.9 i got the wheels file from https://download.pytorch.org/whl/torch_stable.html
Here are the errors after trying with several versions.
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.
This is my python version, i have tried with both python 3.7 and 3.8 virtual environments
python3
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.
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
I have CUDA 9 installed based on the output from deviceQuery
/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
Output from nvcc –version
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
Output from “head -n 1 /etc/nv_tegra_release”
“head -n 1 /etc/nv_tegra_release
# R28 (release), REVISION: 2.1, GCID: 11272647, BOARD: t186ref, EABI: aarch64, DATE: Thu May 17 07:29:06 UTC 2018
Links i have looked at, but didnt work
