I tried with the other solutions mentioned in similar posts but torch.cuda.is_available() is still returning false
nvida-smi
Thu Apr 29 22:56:44 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.33.01 Driver Version: 440.33.01 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 108... Off | 00000000:04:00.0 Off | N/A |
| 34% 61C P2 64W / 250W | 2398MiB / 11176MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 GeForce GTX 108... Off | 00000000:05:00.0 Off | N/A |
| 35% 60C P2 74W / 250W | 9587MiB / 11178MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 2 GeForce GTX 108... Off | 00000000:08:00.0 Off | N/A |
| 18% 58C P2 62W / 250W | 6621MiB / 11178MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 3 GeForce GTX 108... Off | 00000000:0A:00.0 Off | N/A |
| 47% 80C P2 239W / 250W | 10687MiB / 11178MiB | 96% Default |
+-------------------------------+----------------------+----------------------+
| 4 GeForce GTX 108... Off | 00000000:85:00.0 Off | N/A |
| 0% 91C P2 156W / 250W | 9647MiB / 11178MiB | 97% Default |
+-------------------------------+----------------------+----------------------+
| 5 GeForce GTX 108... Off | 00000000:86:00.0 Off | N/A |
| 37% 63C P2 63W / 250W | 9087MiB / 11178MiB | 16% Default |
+-------------------------------+----------------------+----------------------+
| 6 GeForce GTX 108... Off | 00000000:89:00.0 Off | N/A |
| 28% 50C P2 64W / 250W | 9747MiB / 11178MiB | 19% Default |
+-------------------------------+----------------------+----------------------+
| 7 GeForce GTX 108... Off | 00000000:8A:00.0 Off | N/A |
| 0% 37C P8 10W / 250W | 10MiB / 11178MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
python collect_env.py yields the following information:
Collecting environment information...
PyTorch version: 1.8.1
Is debug build: False
CUDA used to build PyTorch: 10.1
ROCM used to build PyTorch: N/A
OS: Ubuntu 16.04.3 LTS (x86_64)
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.12) 5.4.0 20160609
Clang version: Could not collect
CMake version: version 3.5.1
Python version: 3.7 (64-bit runtime)
Is CUDA available: False
CUDA runtime version: 10.2.89
GPU models and configuration:
GPU 0: GeForce GTX 1080 Ti
GPU 1: GeForce GTX 1080 Ti
GPU 2: GeForce GTX 1080 Ti
GPU 3: GeForce GTX 1080 Ti
GPU 4: GeForce GTX 1080 Ti
GPU 5: GeForce GTX 1080 Ti
GPU 6: GeForce GTX 1080 Ti
GPU 7: GeForce GTX 1080 Ti
Nvidia driver version: 440.33.01
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Versions of relevant libraries:
[pip3] numpy==1.20.1
[pip3] torch==1.8.1
[pip3] torchvision==0.9.1
[conda] blas 1.0 mkl
[conda] cudatoolkit 10.1.243 h6bb024c_0
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] mkl 2021.2.0 h06a4308_296
[conda] mkl-service 2.3.0 py37h27cfd23_1
[conda] mkl_fft 1.3.0 py37h42c9631_2
[conda] mkl_random 1.2.1 py37ha9443f7_2
[conda] numpy 1.20.1 py37h93e21f0_0
[conda] numpy-base 1.20.1 py37h7d8b39e_0
[conda] pytorch 1.8.1 py3.7_cuda10.1_cudnn7.6.3_0 pytorch
[conda] torchvision 0.9.1 py37_cu101 pytorch
```nvcc --version```
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Wed_Oct_23_19:24:38_PDT_2019
Cuda compilation tools, release 10.2, V10.2.89
python -c ‘import torch;print(torch.cuda.is_available())’
False
Tried Conda remove pytorch and reinstalled, but the problem persists. Unable to use ‘Cuda’