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.
Do you know how I can make sure I do not have CUDA or a broken installation installed?
I don't think this is the case, it is quite specifically installing the CPU version.
BTW: after the agent fails it will not remove the venv, so you can get into it and check, from the log it will be in: /home/tim/.clearml/venvs-builds/3.7
@<1523701868901961728:profile|ReassuredTiger98> it works on my machine 😞
Where again does clearml place the venv?
Usually ~/.clearml/venvs-builds/<python version>/
Multiple agents will be venvs-builds.1 and so on
Perfect! I have to thank you for helping me, not the other way around!
Uninstall the current clearml-agent and reinstall this wheel, I hacked it to have ==, let's see if that works
Wtf? can you try with = (notice single not double)?
channels:
- defaults
- conda-forge
- pytorch
dependencies:
- cudatoolkit=11.1.1
- pytorch=1.8.0
I can install pytorch just fine locally on the agent, when I do not use clearml(-agent)
My thinking is the issue might be on the env file we are passing to conda, I can't find any other diff.
BTW:
@<1523701868901961728:profile|ReassuredTiger98> Can I send a specific wheel with mode debug prints for you to check (basically it will print the conda env YAML it is using)?
I will try again tomorrow. It s getting late! Thank you for helping so far!
The ordering of the channels seems to matter!
I just wanna add: I can run this task on the same workstation with the same conda installation just fine.
But here is the funny thing:
channels:
- pytorch
- conda-forge
- defaults
dependencies:
- cudatoolkit=11.1.1
- pytorch=1.8.0
Installs GPU
Is ther a way to see the contents of /tmp/conda_envaz1ne897.yml ? Seems to be deleted after the task is finihsed
What's the difference between the two env files?
Installed miniconda finally, now trying to run the task
I tried to run the task with detect_with_conda_freeze: false instead of true and got
Executing Conda: /home/tim/miniconda3/condabin/conda install -p /home/tim/.clearml/venvs-builds/3.8 -c defaults -c conda-forge -c pytorch 'pip<20.2' --quiet --json
Pass
Conda: Trying to install requirements:
['pytorch~=1.8.0']
Executing Conda: /home/tim/miniconda3/condabin/conda env update -p /home/tim/.clearml/venvs-builds/3.8 --file /tmp/conda_envh7rq4qmc.yml --quiet --json
Conda 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~=1.8.0 -> cudatoolkit[version='>=10.1,<10.2|>=10.2,<10.3']
The following specifications were found to be incompatible with each other:
Package cudatoolkit conflicts for:
cudatoolkit=11.0
Conda: Installing requirements: step 2 - using pip:
['clearml==0.17.4', 'tensorboard==2.4.1', 'pytorch~=1.8.0']
Collecting tensorboard==2.4.1
Using cached tensorboard-2.4.1-py3-none-any.whl (10.6 MB)
ERROR: Could not find a version that satisfies the requirement pytorch~=1.8.0 (from -r /tmp/cached-reqsubuv0zrf.txt (line 3)) (from versions: 0.1.2, 1.0.2)
ERROR: No matching distribution found for pytorch~=1.8.0 (from -r /tmp/cached-reqsubuv0zrf.txt (line 3))
Command 'source /home/tim/miniconda3/etc/profile.d/conda.sh && conda activate /home/tim/.clearml/venvs-builds/3.8 && pip install -r /tmp/cached-reqsubuv0zrf.txt' returned non-zero exit status 1.
Okay. AndÂ
110
 means 11.1 and not 11.0? (edited)
110 means 11.0, the odd thing is, it actually installed 11.1, and from the pytorch website this is exactly how they suggest to install with conda...
Let me know if forcing the CUDA version changes anything
name: core
channels:
- pytorch
- anaconda
- conda-forge
- defaults
dependencies:
- _libgcc_mutex=0.1
- _openmp_mutex=4.5
- 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
- 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
- pip=21.0.1
- 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
- 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
- pip:
- aiostream==0.4.2
- attrs==20.3.0
- clearml==0.17.4
- dm-control==0.0.355168290
- dm-env==1.4
- furl==2.1.0
- future==0.18.2
- glfw==2.1.0
- gym==0.18.0
- humanfriendly==9.1
- imageio-ffmpeg==0.4.3
- jsonschema==3.2.0
- labmaze==1.0.3
- lxml==4.6.2
- moviepy==1.0.3
- orderedmultidict==1.0.1
- pathlib2==2.3.5
- pillow==7.2.0
- proglog==0.1.9
- psutil==5.8.0
- pybullet==3.0.9
- pygame==2.0.1
- pyglet==1.5.0
- pyjwt==2.0.1
- pyrsistent==0.17.3
- requests-file==1.5.1
- tensorboard==2.4.1
- tensorboardx==2.1
No problem! I profit so much from clearml 🙂
This my environment installed from env file. Training works just fine here:
Interesting: This command failes (with an error similar to the one I posted above) in conda version 4.7.12 but runs just fine in version 4.9.2: conda create --name test-pytorch python=3.8 cudatoolkit=11.1 -c conda-forge