Trying to Serve a ML (pytorch) model on a Heroku, slug size too large [duplicate] - heroku

Question

I've been getting the slug size too large warning (Compiled slug size: 789.8M is too large (max is 500M)) from Heroku and I can't figure out why, as my model size (cnn.pth below) is fairly small and my file directory is only 1.1mb in total: screenshot of directory.
It seems like the size increase is caused by running pipenv install torch, as the slug size was 89.1mb before installing torch and 798.8mb after.
My Pipfile currently has these packages installed:
[packages]
flask = "*"
flask-sqlalchemy = "*"
psycopg2 = "*"
psycopg2-binary = "*"
requests = "*"
numpy = "*"
gunicorn = "*"
pillow = "*"
torch = "*"
Is there any workaround for this?
Edit: I'm running Mac OSX 10.10.5, using Flask and pipenv.

Answer 1

The pytorch package that you're installing comes with both cpu and gpu support, thus has a large size. It seems you're using the free version of heroku, and only require the cpu support. The solution is to install the pytorch package for cpu only i.e.
In requirements.txt, write the wheel file path corresponding to the version of pytorch (cpu) that you're interested in. You can find the list of wheel files, which can be installed with pip. For example, for PyTorch 1.3.1, torchvision 0.4.2, Python 3.7, Linux, you can write the following for pytorch and torchvision respectively:
https://download.pytorch.org/whl/cpu/torch-1.3.1%2Bcpu-cp37-cp37m-linux_x86_64.whl
https://download.pytorch.org/whl/cpu/torchvision-0.4.2%2Bcpu-cp37-cp37m-linux_x86_64.whl
The above will download torch-1.3.1+cpu-cp37-cp37m-linux_x86_64.whl (107MB) torchvision-0.4.2+cpu-cp37-cp37m-linux_x86_64.whl (13MB) respectively.

Answer 2

Go to PyTorch Get Started page. Choose Stable version, Linux, pip, python, cpu and you can see:
pip install torch==1.8.1+cpu torchvision==0.9.1+cpu torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html
Copy versions to your requirements.txt.
torch==1.8.1+cpu
torchvision==0.9.1+cpu
And add to the beginning of the requirements.txt this:
-f https://download.pytorch.org/whl/torch_stable.html
After that, all packages will be installed on Heroku.
For reference:
torch==1.8.1+cpu (169.1 MB);
torchvision==0.9.1+cpu (13.3 MB)

Answer 3

By today, March 28, 2022, these are the working versions:
torch==1.11.0+cpu
torchvision==0.12.0+cpu

Answer 4

(Aug, 2, 2022) the only solution I found was leaving the requirements.txt like this:
--find-links https://download.pytorch.org/whl/torch_stable.html
torch==1.11.0+cpu
--find-links https://download.pytorch.org/whl/torch_stable.html
torchvision==0.12.0+cpu