I just configured my GPU and I was trying to use Pytorch with CUDA.
I am facing quite a simple error I think.
I run:
import torch
a = torch.randn(10).cuda()
and i get:
Traceback (most recent call last):
File “<stdin>”, line 1, in <module>
File “/home/pablo/.local/lib/python2.7/site-packages/torch/_utils.py”, line 69, in cuda return new_type(self.size()).copy(self, async)
File “/home/pablo/.local/lib/python2.7/site-packages/torch/cuda/init.py”, line 358, in _lazy_new_lazy_init()
File “/home/pablo/.local/lib/python2.7/site-packages/torch/cuda/init.py”, line 120, in _lazy_init_check_driver()
File “/home/pablo/.local/lib/python2.7/site-packages/torch/cuda/init.py”, line 55, in _check_driver raise AssertionError(“Torch not compiled with CUDA enabled”)
AssertionError: Torch not compiled with CUDA enabled
I guess the solution is as simple as: Install Pytorch with CUDA. Hence I tried running:
It seems you are using a GT 710, which should have compute capability 2.1. This might be too low. At least I had to upgrade my GTX 580, since I wasn’t able to use it.
Could someone confirm?
I am not sure that is the information you are looking for.
I run “deviceQuery” and that’s the output I get:
./deviceQuery Starting…
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 1 CUDA Capable device(s)
Device 0: “GeForce GT 710”
CUDA Driver Version / Runtime Version 9.0 / 8.0
CUDA Capability Major/Minor version number: 3.5
Total amount of global memory: 2002 MBytes (2099118080 bytes)
( 1) Multiprocessors, (192) CUDA Cores/MP: 192 CUDA Cores
GPU Max Clock rate: 954 MHz (0.95 GHz)
Memory Clock rate: 800 Mhz
Memory Bus Width: 64-bit
L2 Cache Size: 524288 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 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: 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: 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 PCI Domain ID / Bus ID / location ID: 0 / 59 / 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 = 8.0, NumDevs = 1, Device0 = GeForce GT 710
Result = PASS
Compute capability is 3.5 (or am I looking the wrong information?).
