Before using this repo, make sure you’ve completed the environment setup guide, which installs the core tools you’ll need for this module, such as:
- Git
- Git Bash (for Windows)
- Visual Studio Code
- UV
The Deep Learning module uses its own isolated environment called deep-learning-env so that packages don’t conflict with other projects.
We use UV to create this environment, activate it, and install the required packages listed in the module’s pyproject.toml.
This setup only needs to be done once per module, after that, you just activate the environment whenever you want to work in this repo.
Open a terminal (macOS/Linux) or Git Bash (Windows) in this repo, and run the following commands in order:
-
Create a virtual environment called
deep-learning-env:uv venv deep-learning-env --python 3.11 -
Activate the environment:
-
for macOS/Linux:
source deep-learning-env/bin/activate -
for windows (git bash):
source deep-learning-env/Scripts/activate
-
-
Install all required packages from the pyproject.toml
uv sync --active
In order to run any code in this repo, you must first activate its environment.
-
for macOS/Linux:
source deep-learning-env/bin/activate -
for windows (git bash):
source deep-learning-env/Scripts/activate
When the environment is active, your terminal prompt will change to show:
(deep-learning-env) $
This is your visual cue that you’re working inside the right environment.
When you’re finished, you can deactivate it with:
deactivate👉 Remember
Only one environment can be active at a time. If you switch to a different repo, first deactivate this one (or just close the terminal) and then activate the new repo’s environment.
For questions or issues, please contact the Deep Learning Module learning support team or email courses.dsi@utoronto.ca.