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R-U-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intents
This is the repository accompanying the paper "R-U-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intents".
If you use the code released through this repository, please cite the following paper:
@article{johnson2023rusure,
title = {{R-U-SURE?} Uncertainty-Aware Code Suggestions By Maximizing
Utility Across Random User Intents},
author = {Daniel D. Johnson and
Daniel Tarlow and
Christian Walder},
journal = {arXiv preprint arXiv:2303.00732},
year = {2023},
}
Demo
If you would like to try out the R-U-SURE system, you can open our demo notebook in Google Colab:
You might also be interested in the intro and details notebooks for our utility function decision diagram representation.
Installation
If you would like to install the R-U-SURE library on your own system, you can follow the instructions below.
Prerequisite: Setting up a virtual environment
It is highly recommended to install this package into a virtual environment,
as it currently depends on a patched version of numba
that may be incompatible
with a global installation.
To create and activate a virtual environment, you can run the Bash commands
# you can use any path here
venv_path="$HOME/venvs/rusure"
python3 -m venv $venv_path
source $venv_path/bin/activate
echo "Active virtual environment is: $VIRTUAL_ENV"
(On Linux, you may need to run sudo apt-get install python3-venv
first.)
Installing the package directly from GitHub
If you want to use the r_u_sure
package from Python without modifying it, you
can directly install it from GitHub using pip
:
# Optional: disable some unused numba features to prevent build errors
export NUMBA_DISABLE_TBB=1
export NUMBA_DISABLE_OPENMP=1
pip install "r_u_sure @ git+https://github.com/google-research/r_u_sure"
pip
will then automatically install the most recent version of the package
and make it available from Python via import r_u_sure
.
Note that you can also add r_u_sure @ git+https://github.com/google-research/r_u_sure
to your requirements.txt
or pyproject.toml
files if you are developing a
package that depends on R-U-SURE.
Installing from source
If you prefer to download the R-U-SURE source files manually, or if you would like to contribute to the R-U-SURE library, you can perform a local installation. Start by cloning this GitHub repository:
git clone https://github.com/google-research/r_u_sure
cd r_u_sure
Next, install it:
# Optional: disable some unused numba features to prevent build errors
export NUMBA_DISABLE_TBB=1
export NUMBA_DISABLE_OPENMP=1
pip install -e .
Local edits to the source files will now be reflected properly in the python interpreter.
(If you'd prefer, you can also omit the export NUMBA_DISABLE_{X}=1
lines to
compile those features into numba. Those features have additional dependencies;
see the Numba documentation.)
Running tests
To run the R-U-SURE tests, you can use the command
python -m r_u_sure.testing.run_tests
Note that some tests require jit-compiling large programs, which can take a few minutes. To run a faster subset of the tests, you can instead run
python -m r_u_sure.testing.run_tests --skip_jit_tests
This is not an officially supported Google product.