Dear ptrblck,
it works !
I follow your instruction.
uninstall pytorch
$ conda remove pytorch
## Package Plan ##
environment location: /home/silverant/anaconda3/envs/rl_gym_book
removed specs:
- pytorch
The following packages will be downloaded:
package | build
---------------------------|-----------------
mkl-2018.0.3 | 1 126.9 MB
mkl_fft-1.0.6 | py35h7dd41cf_0 134 KB
mkl_random-1.0.1 | py35h4414c95_1 313 KB
numpy-1.15.2 | py35h1d66e8a_0 46 KB
numpy-base-1.15.2 | py35h81de0dd_0 3.4 MB
tbb-2019.8 | hfd86e86_0 1.1 MB
tbb4py-2018.0.5 | py35h6bb024c_0 201 KB
------------------------------------------------------------
Total: 132.1 MB
The following NEW packages will be INSTALLED:
mkl_fft pkgs/main/linux-64::mkl_fft-1.0.6-py35h7dd41cf_0
mkl_random pkgs/main/linux-64::mkl_random-1.0.1-py35h4414c95_1
numpy-base pkgs/main/linux-64::numpy-base-1.15.2-py35h81de0dd_0
tbb pkgs/main/linux-64::tbb-2019.8-hfd86e86_0
tbb4py pkgs/main/linux-64::tbb4py-2018.0.5-py35h6bb024c_0
The following packages will be REMOVED:
cudatoolkit-10.1.243-h6bb024c_0
libtiff-4.1.0-h2733197_0
olefile-0.46-py35_0
pillow-5.2.0-py35heded4f4_0
pytorch-1.3.1-py3.5_cuda10.1.243_cudnn7.6.3_0
torchvision-0.4.2-py35_cu101
zstd-1.3.7-h0b5b093_0
The following packages will be UPDATED:
numpy 1.14.2-py35hdbf6ddf_0 --> 1.15.2-py35h1d66e8a_0
The following packages will be DOWNGRADED:
mkl 2019.4-243 --> 2018.0.3-1
Proceed ([y]/n)? y
then install pytorch again
conda install pytorch torchvision cudatoolkit=10.1 -c pytorch
## Package Plan ##
environment location: /home/silverant/anaconda3/envs/rl_gym_book
added / updated specs:
- cudatoolkit=10.1
- pytorch
- torchvision
The following NEW packages will be INSTALLED:
cudatoolkit pkgs/main/linux-64::cudatoolkit-10.1.243-h6bb024c_0
libtiff pkgs/main/linux-64::libtiff-4.1.0-h2733197_0
olefile pkgs/main/linux-64::olefile-0.46-py35_0
pillow pkgs/main/linux-64::pillow-5.2.0-py35heded4f4_0
pytorch pytorch/linux-64::pytorch-1.3.1-py3.5_cuda10.1.243_cudnn7.6.3_0
torchvision pytorch/linux-64::torchvision-0.4.2-py35_cu101
zstd pkgs/main/linux-64::zstd-1.3.7-h0b5b093_0
Proceed ([y]/n)? y
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
and after that, the cuda.is_available() return True
$ python -c 'import torch;print(torch.cuda.is_available())'
True
Thank you very much sir.
best regards,