channels:
- defaults
- conda-forge
- pytorch
dependencies:
- cudatoolkit==11.1.1
- pytorch==1.8.0
Gives CPU version
Still shows CPU version when I run conda list
I just wanna add: I can run this task on the same workstation with the same conda installation just fine.
Or there should be an early error for trying to run conda based tasks on pip agents
okay, I'll make sure we order it correctly
btw: why is agent.package_manager and agent attribute. Imo it does not make sense because conda can install pip packages, but pip cannot install conda packages which can lead to install failures, right?
Would it help you diagnose this problem if I ran conda env create --file=environment.yml and see whether it works?
So I just updated the env that clearml-agent created (and where pytorch cpu is installed) with my local environment.yml and now the correct version is installed, so most probably the `/tmp/conda_envaz1ne897.yml`` is the problem here
But I do not have anything linked correctly since I rely in conda installing cuda/cudnn for me
This my environment installed from env file. Training works just fine here:
I just tried to envrionment setup steps that clearml-agent is doing locally, but with my environment.yml instead of the one that clearml generates.
Yes I think the difference is running conda install with arguments vs conda install with env file...
But I do not have anything linked correctly since I rely in conda installing cuda/cudnn for me
From the log it installed:cudatoolkit==11.1.1
based on the CUDA it found on the host machine: agent.cuda_version = 110
But for some reason it installed the pytorch from the conda "pytorch" repo without the cuda support.
Thanks! Tomorrow is great, I'll put the wheel here 🙂
@<1523701868901961728:profile|ReassuredTiger98> if you use the latest RC! i sent and run with --debug in the log you will see the full /tmp/conda_envaz1ne897.yml content
Here it is copied from your log, do you want to see if this one works:
channels:
- defaults
- conda-forge
- pytorch
dependencies:
- blas~=1.0
- bzip2~=1.0.8
- ca-certificates~=2020.10.14
- certifi~=2020.6.20
- cloudpickle~=1.6.0
- cudatoolkit~=11.1.1
- cycler~=0.10.0
- cytoolz~=0.11.0
- dask-core~=2021.2.0
- decorator~=4.4.2
- ffmpeg~=4.3
- freetype~=2.10.4
- gmp~=6.2.1
- gnutls~=3.6.13
- imageio~=2.9.0
- jpeg~=9b.0
- kiwisolver~=1.3.1
- lame~=3.100
- lcms2~=2.11
- ld_impl_linux-64~=2.33.1
- libedit~=3.1.20191231
- libffi~=3.3
- libgcc-ng~=9.3.0
- libgfortran-ng~=7.3.0
- libiconv~=1.16
- libpng~=1.6.37
- libstdcxx-ng~=9.3.0
- libtiff~=4.1.0
- libuv~=1.41.0
- llvm-openmp~=11.0.1
- lz4-c~=1.9.3
- matplotlib-base~=3.3.4
- mkl~=2020.4
- mkl-service~=2.3.0
- mkl_fft~=1.3.0
- mkl_random~=1.2.0
- ncurses~=6.2
- nettle~=3.6
- networkx~=2.5
- ninja~=1.10.2
- numpy~=1.19.2
- numpy-base~=1.19.2
- olefile~=0.46
- openh264~=2.1.1
- openssl~=1.1.1j
- pyparsing~=2.4.7
- python~=3.7.10
- python-dateutil~=2.8.1
- python_abi~=3.7
- pytorch~=1.8.0
- pywavelets~=1.1.1
- pyyaml~=5.3.1
- readline~=8.1
- scikit-image~=0.17.2
- scipy~=1.6.1
- setuptools~=52.0.0
- six~=1.15.0
- sqlite~=3.33.0
- tifffile~=2020.10.1
- tk~=8.6.10
- toolz~=0.11.1
- torchaudio~=0.8.0
- torchvision~=0.9.0
- tornado~=6.1
- typing_extensions~=3.7.4.3
- wheel~=0.36.2
- xz~=5.2.5
- yaml~=0.2.5
- zlib~=1.2.11
- zstd~=1.4.9
I do not have a global cuda install on this machine. Everything except for the driver is installed via conda.
Perfect, will try it. fyi: The conda_channels that I used are from clearml-agent init