This repository is archived and our Probot stuff has moved to https://github.com/pytorch/test-infra/tree/main/torchci
A GitHub App built with Probot that implements bot actions for PyTorch
This bot implements a few behaviors. This bot currently only implements idempotent behaviors (i.e., it is harmless if the bot process events multiple times. If you add support for non-idempotent behaviors, you need to make sure only the GitHub Action or AWS Lambda is enabled.
Add an issue to your project like pytorch/pytorch#24422
and add a .github/pytorch-probot.yml
file with:
tracking_issue: 24422
Based on who is listed in the tracking issue, the bot will automatically CC people when labels are added to an issue.
- If an issue is labeled high priority, also label it triage review
- If an issue is labeled topic: flaky-tests, also label it high priority and triage review
- If an issue or pull request contains a regex in its title, label it accordingly, e.g., a title containing 'ROCm' would yield the module: rocm label.
- Trigger circleci workflows based off of labeling events / push events
Configuration (.github/pytorch-circleci-labels.yml
) should look similar to this:
labels_to_circle_params:
# Refers to github labels
ci/binaries:
# Refers to circleci parameters
# For circleci documentation on pipeline parameters check:
# https://circleci.com/docs/2.0/pipeline-variables/#pipeline-parameters-in-configuration
parameter: run_binaries_tests
# [[optional]] Automatically trigger workflows with parameters on push
default_true_on:
branches:
- nightly
# Regex is allowed as well
- ci-all/.*
# Even works on tags!
tags:
- v[0-9]+(\.[0-9]+)*-rc[0-9]+
# Multiple label / parameters can be defined
ci/bleh:
parameter: run_bleh_tests
ci/foo:
parameter: run_foo_tests
# Install dependencies
yarn install
# Run the tests
yarn test
# Run the bot
yarn start
If you want to smoketest the bot on a test repository, you'll need to create a GitHub app. Go to the webpage from probot; it will walk through the process.
Although a GitHub App is convenient for testing, it requires an actual server to deploy in prod. Previously we ran the server on AWS, but this deployment process was substantially more involved. GitHub Actions deployment is simpler. Follow the instructions at https://github.com/actions/toolkit/blob/master/docs/action-versioning.md
Right now the GitHub Actions deployment is a little rocky because massive queueing in the PyTorch repository means it takes something like 30min before actions are run. So we are also running AWS side-by-side.
.github/workflows/build.yml
will build and deploy the code on every push to main
.
If you have suggestions for how pytorchbot could be improved, or want to report a bug, open an issue! We'd love all and any contributions.
For more, check out the Contributing Guide.
ISC © 2019 Edward Z. Yang [email protected] (https://pytorch.org)