torch version inference logic broken when torchvision is specified

If I start an experiment with the following requirements defined in the UI:

torch==1.3.1

The installation works well, But if I use the following requirements:

torch==1.3.1
torchvision==0.2.1

Then it fails trying to install torch==0.2.1 after installing torch==1.3.1. Probably the parsing of the version of torchvision has an error?

Here is the full log of the error:

Requirement already up-to-date: pip==20.1 in /home/H4dr1en/.trains/venvs-builds/3.7/lib/python3.7/site-packages (20.1)
Collecting Cython
  Using cached Cython-0.29.17-cp37-cp37m-manylinux1_x86_64.whl (2.1 MB)
Installing collected packages: Cython
Successfully installed Cython-0.29.17
Collecting torch==1.3.1+cpu
  File was already downloaded /home/H4dr1en/.trains/pip-download-cache/cu0/torch-1.3.1+cpu-cp37-cp37m-linux_x86_64.whl
Successfully downloaded torch
Collecting torch==0.2.1
  ERROR: HTTP error 403 while getting http://download.pytorch.org/whl/cu0/torch-0.2.1-cp37-cp37m-linux_x86_64.whl
  ERROR: Could not install requirement torch==0.2.1 from http://download.pytorch.org/whl/cu0/torch-0.2.1-cp37-cp37m-linux_x86_64.whl because of error 403 Client Error: Forbidden for url: http://download.pytorch.org/whl/cu0/torch-0.2.1-cp37-cp37m-linux_x86_64.whl
ERROR: Could not install requirement torch==0.2.1 from http://download.pytorch.org/whl/cu0/torch-0.2.1-cp37-cp37m-linux_x86_64.whl because of HTTP error 403 Client Error: Forbidden for url: http://download.pytorch.org/whl/cu0/torch-0.2.1-cp37-cp37m-linux_x86_64.whl for URL http://download.pytorch.org/whl/cu0/torch-0.2.1-cp37-cp37m-linux_x86_64.whl
trains_agent: ERROR: Could not download wheel name of "http://download.pytorch.org/whl/cu0/torch-0.2.1-cp37-cp37m-linux_x86_64.whl"
ERROR: Double requirement given: torch==0.2.1 from http://download.pytorch.org/whl/cu0/torch-0.2.1-cp37-cp37m-linux_x86_64.whl (from -r /tmp/cached-reqsipcp8nfs.txt (line 2)) (already in torch==1.3.1+cpu from file:///home/H4dr1en/.trains/pip-download-cache/cu0/torch-1.3.1%2Bcpu-cp37-cp37m-linux_x86_64.whl (from -r /tmp/cached-reqsipcp8nfs.txt (line 1)), name='torch')
trains_agent: ERROR: Could not install task requirements!
Command '['/home/H4dr1en/.trains/venvs-builds/3.7/bin/python', '-m', 'pip', '--disable-pip-version-check', 'install', '-r', '/tmp/cached-reqsipcp8nfs.txt']' returned non-zero exit status 1.
DONE: Running task 'c63fc150ff5049c4939cd6a37f3d30a8', exit status 1

System: Linux Debian 9 Cuda: not installed (no gpu)

[H4dr1en]

Regrading using pypi with torch, the problem is, this is unstabe, for example there is no way of knowing whether the torchvision on pypi is the CPU or the GPU version… Also for the GPU version, the CUDA version changes from one torch version to another, so you end up with driver mismatch with no good reason.

Thank you for pointing that out, this definitely makes sense!

With all that said, if you know what’s the correct version for your setup, you can simple replace the torchvision==0.2.1 with a direct https link to the wheel:

Thanks for the workaround! I’ll close as soon as the error is more explicit 👍

EDIT: @H4dr1en, What is the trains-agent version you are using? What is the package manager trains-agent is using ? see example here What is the pip version limit configured in trains.conf? see example here

train-agent==0.14.2rc2 package manager = pip pip version = 0.21

[bmartinn]

Yes you are correct, I’ll make sure the error message will be corrected in the next RC.

Regrading using pypi with torch, the problem is, this is unstabe, for example there is no way of knowing whether the torchvision on pypi is the CPU or the GPU version… Also for the GPU version, the CUDA version changes from one torch version to another, so you end up with driver mismatch with no good reason.

With all that said, if you know what’s the correct version for your setup, you can simple replace the torchvision==0.2.1 with a direct https link to the wheel: https://files.pythonhosted.org/packages/ca/0d/f00b2885711e08bd71242ebe7b96561e6f6d01fdb4b9dcf4d37e2e13c5e1/torchvision-0.2.1-py2.py3-none-any.whl This would work, as long as it matches the CPU/CUDA version you are running .