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I've been using Anaconda for a few years now, but since I started using a Mac with a M1 processor I had to deal with a bunch of problem with the installation of some packages, which left me a little confused about some basic concepts.

For example, I was trying to install Tensorflow, and it turns out the proper way is to install miniforge, and get Tensorflow from the conda-forge channel (which is the default for miniforge), as explained here. Then, I was wondering whether I could do the same using Anaconda/Miniconda...set up the conda-forge channel as default, and install Tensorflow (or any other arm-compatible package), but I've been told it's not possible

So, now I'm trying to understand how this all works. If a Tensorflow version compatible with M1 processors exists in the conda-forge channel (and it does exist), why can't I install it by using Anaconda/Miniconda, after configuring it to use said channel? To phrase it in another way, what is the difference between Anaconda/Miniconda and Miniforge, other than the channels they look into for packages (and, as I understand, some licenses)?

Here there is a similar question, but the answers don't seem to address my main concern (why Anaconda/Miniconda with conda-forge as default channel is different than miniforge).

Carlo
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1 Answers1

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It's not impossible, but you'll have to jump through hoops to get it done. First, if you have an Anaconda installation, you can't install conda-forge packages into the base environment consistently, because the anaconda package in the base environment of Anaconda will conflict with packages from conda-forge. Second, since Anaconda is only x86_64 at the moment, you can only install it via Rossetta emulation. After that, you need to tell conda that you need arm64 compatible packages by setting the env variable CONDA_SUBDIR.

CONDA_SUBDIR=osx-arm64 conda create -n native numpy -c conda-forge

will get you a new env with native arm64 packages. However if you want to update this env, you have to prefix all your conda commands with CONDA_SUBDIR=osx-arm64.

To fix this permanently, you can do the following

conda activate native
conda config --env --set subdir osx-arm64

which will make conda use osx-arm64 for this environment.

isuruf
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