I am trying to install
cudatoolkit=11.2 on google colab using:
conda install pytorch cudatoolkit=11.2 -c pytorch -c nvidia
But why does it install old
pytorch=1.0.0 version not something
If I try to force install
pytorch=1.6, it gives the following error:
UnsatisfiableError: The following specifications were found to be incompatible with a past
explicit spec that is not an explicit spec in this operation (cudatoolkit):
- pytorch=1.6 -> cudatoolkit[version='>=10.1,<10.2|>=10.2,<10.3|>=9.2,<9.3']
The following specifications were found to be incompatible with each other:
Output in format: Requested package -> Available versions
Package setuptools conflicts for:
python=3.7 -> pip -> setuptools
conda[version='>=4.10.3'] -> setuptools[version='>=31.0.1']
wheel -> setuptools
pip -> setuptools
I basically want to work with the latest versions of pytorch with
The PyTorch binaries are not built with CUDA11.2 and you would have to stick to the install commands provided here.
conda install pytorch cudatoolkit=11.1 -c pytorch -c nvidia
Can this work for even
No, you cannot install the PyTorch binaries built with CUDA11.2, since they are not available.
If you want to use this specific CUDA version, you could build from source.
Alternatively, you could install the nightly binaries with CUDA11.3 using:
pip install --pre torch -f https://download.pytorch.org/whl/nightly/cu113/torch_nightly.html
Thanks for the reply, I guess you overlooked
cudatoolkit=11.1 in my previous reply?
No, I haven’t overlooked it.
Your posted command using
cudatoolkit=11.1 will work.
No, this won’t work.
ok. I am curious why it did install cudatoolkit=11.1 even though my cuda version is actually 11.2.
The binaries ship with their own CUDA runtime so your local CUDA toolkit (assuming that’s what you mean by “cuda 11.2”) won’t be used unless you are building from source or a custom CUDA extension.