old version is installed for arm64 based conda

🐛 Describe the bug

I installed miniforge for apple silicon with the following specs:

          conda version : 4.11.0
    conda-build version : not installed
         python version : 3.9.7.final.0
               platform : osx-arm64

I then created a conda environment and then install pytorch and torchvision,

conda create --name pytorch_env python=3.9
conda activate pytorch_env
conda install -c pytorch pytorch torchvision

When trying to run this main.py script I get the following error:

from PIL import Image, ImageOps, ImageEnhance, PILLOW_VERSION 
ImportError: cannot import name 'PILLOW_VERSION' from 'PIL

Looking at the torchvision package version it installed a very old version in-spite of the new pillow and pytorch versions installed

pillow                    9.0.0            py39hcb29f89_0    conda-forge
python                    3.9.10          h38ef502_2_cpython    conda-forge
pytorch                   1.10.1          cpu_py39hbfdb42d_0    conda-forge
torchvision               0.2.2                      py_3    pytorch

After installing the right version as advised on the readme it all worked fine!

conda install torchvision==0.11.2 -c pytorch

But seems the requirements / package dependencies are not aligned as an old version 0.2.2 was installed with new pytorch and pillow versions.

I also did not have this problem when I installed the Intel based miniforge

(more details here)

Versions

conda setup:

          conda version : 4.11.0
    conda-build version : not installed
         python version : 3.9.7.final.0
               platform : osx-arm64

pytorch and python:

pillow                    9.0.0            py39hcb29f89_0    conda-forge
python                    3.9.10          h38ef502_2_cpython    conda-forge
pytorch                   1.10.1          cpu_py39hbfdb42d_0    conda-forge
torchvision               0.2.2                      py_3    pytorch

Reproduce the issue with the listed conda commands on an osx-arm64 environment, then inspect the resolved torchvision package metadata and the main.py example mentioned in the report. Check why torchvision 0.2.2 is selected alongside the reported PyTorch and Pillow versions; done means dependency resolution selects a compatible torchvision version without manual pinning.