Which is the command to see the "correct" CUDA Version that pytorch
in conda env is seeing? This, is a similar question, but doesn't get me far.
nvidia-smi
says I have cuda version 10.1
conda list
tells me cudatoolkit version is 10.2.89
torch.cuda.is_available()
shows FALSE, so it sees No CUDA
?
print(torch.cuda.current_device())
, I get 10.0.10
(10010??) (it
looks like):
AssertionError: The NVIDIA driver on your system is too old (found version 10010)
print(torch._C._cuda_getCompiledVersion(), 'cuda compiled version')
tells me my version is 10.0.20
(10020??)?
10020 cuda compiled version
Why are there so many different versions? What am I missing?
P.S
I have Nvidia driver 430
on Ubuntu 16.04 with Geforce 1050. It comes
with libcuda1-430
when I installed the driver from additional drivers
tab in ubuntu (Software and Updates
). I installed pytorch
with conda
which also installed the cudatoolkit
using conda install -c fastai -c pytorch -c anaconda fastai
In the conda env (myenv) where pytorch is installed do the following:
conda activate myenv
torch.version.cuda
Nvidia-smi
only shows compatible version. Does not seem to talk about the version pytorch
's own cuda is built on.
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