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I'm trying to get a basic app running with Flask + PyTorch, and host it on Heroku. However, I run into the issue that the maximum slug size is 500mb on the free version, and PyTorch itself is ~500mb.
After some google searching, someone wrote about finding a cpu-only version of PyTorch, and using that, which is much smaller here.
However, I'm pretty lost as to how this is done, and the person didn't document this at all. Any advice is appreciated, thanks.
EDIT:
To be more specific about my problem, I tried installing torch by (as far as I understand), including a requirements.txt which listed torch as a dependency. Current I have: torch==0.4.1. However this doesn't work bc of size.
My question is, do you know what I could write in the requirements file to get the cpu-only version of torch that is smaller, or alternatively, if the requirements.txt doesn't work for this, what I would do instead, to get the cpu version.
解决方案
Per the Pytorch website, you can install pytorch-cpu with
conda install pytorch-cpu torchvision-cpu -c pytorch
You can see from the files on Anaconda cloud, that the size varies between 26 and 56MB depending on the OS where you want to install it.
You can get the wheel from http://download.pytorch.org/whl/cpu/.
The wheel is 87MB.
You can setup the installation by putting the link to the wheel in the requirements.txt file. If you use Python 3.6 on Heroku:
http://download.pytorch.org/whl/cpu/torch-0.4.1-cp36-cp36m-linux_x86_64.whl
otherwise, for Python 2.7:
http://download.pytorch.org/whl/cpu/torch-0.4.1-cp27-cp27mu-linux_x86_64.whl
For example if your requirements are pytorch-cpu, numpy and scipy and you're using Python 3.6, the requirements.txt would look like:
http://download.pytorch.org/whl/cpu/torch-0.4.1-cp36-cp36m-linux_x86_64.whl
numpy
scipy
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