kabyleai / conda-piptools

Quick demo of setting up a deep learning Python environment using conda and pip-tools.

Conda + Pip-Tools Sample Project

Quick demo of setting up a deep learning Python environment.

Our goals:

• Easily specify the exact Python, CUDA, CUDNN environment
• Humans should specify minimal constraints (torch >= 1.7 and numpy), computer should figure out exact, mutually compatible versions (torch==1.7.1; numpy==1.19.5)
• Separate production (torch) from development (black) dependencies

We achieve this by:

• We specify our Python and CUDA versions in environment.yml
• We use the conda package manager to create our environment from this file
• We specify our requirements in requirements/prod.in and requirements/dev.in
• We use pip-tools to lock in mutually compatbile versions of all requirements
• We add a Makefile so we can simply run make to update everything

Try it out by running docker run --rm -vpwd:/var/task -it continuumio/miniconda /bin/bash, and then in the container:

apt-get install make
cd /var/task
make

This will set up the environment.

Don't forget to activate it by running conda activate conda-piptools-sample-project!