@rasbt do you know if there is any possibility to conda install torchvision -c pytorch without having to install CUDA Toolkit? This is my output when I try to install torchvision  (ignore the $USERPATH):
Collecting package metadata: done
Solving environment: done

## Package Plan ##

  environment location: /$USERPATH/anaconda3/envs/maskrcnn_benchmark

  added / updated specs:
    - torchvision


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    pytorch-1.0.1              |py3.7_cuda10.0.130_cudnn7.4.2_2       375.4 MB  pytorch
    ------------------------------------------------------------
                                           Total:       375.4 MB

The following NEW packages will be INSTALLED:

  cudatoolkit        pkgs/main/linux-64::cudatoolkit-10.0.130-0
  -- freetype           pkgs/main/linux-64::freetype-2.9.1-h8a8886c_1
  -- jpeg               pkgs/main/linux-64::jpeg-9b-h024ee3a_2
  -- libpng             pkgs/main/linux-64::libpng-1.6.36-hbc83047_0
  -- libtiff            pkgs/main/linux-64::libtiff-4.0.10-h2733197_2
  -- olefile            pkgs/main/linux-64::olefile-0.46-py37_0
  -- pillow             pkgs/main/linux-64::pillow-6.0.0-py37h34e0f95_0
  pytorch            pytorch/linux-64::pytorch-1.0.1-py3.7_cuda10.0.130_cudnn7.4.2_2 
  torchvision        pytorch/noarch::torchvision-0.2.2-py_3
  -- zstd               pkgs/main/linux-64::zstd-1.3.7-h0b5b093_0


Since I will be doing inference on CPU, I installed: conda install pytorch-nightly-cpu -c pytorch, which is required by the repository.
Do you know why do I have to install the packages I highlighted? I mean, I don’t need right now neither cudatoolkit (inference on CPU) nor pytorch (which I have already installed).
Is there any possibility to only install torchvision without those two packages? Install it via pip maybe?, but I don’t know if it would be conflicting with the conda pytorch channel installation of Pytorch  (CPU).
I guess CUDA Toolkit won’t be installed on the conda environment, but system-wide. There are plans to later add a GPU to the station, but I don’t want to install anything CUDA-related until the card is installed.
Any help would be appreciated! Thanks!