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Add exportable baby llama example #16100

Add exportable baby llama example

Add exportable baby llama example #16100

Workflow file for this run

name: Lint
on:
pull_request:
branches-ignore:
- nightly
push:
branches:
- main
- release/*
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
cancel-in-progress: true
jobs:
lintrunner:
uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
with:
runner: linux.2xlarge
docker-image: executorch-ubuntu-22.04-linter
fetch-depth: 0
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
timeout: 90
script: |
# The generic Linux job chooses to use base env, not the one setup by the image
CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
conda activate "${CONDA_ENV}"
CACHE_DIRECTORY="/tmp/.lintbin"
# Try to recover the cached binaries
if [[ -d "${CACHE_DIRECTORY}" ]]; then
# It's ok to fail this as lintrunner init would download these binaries
# again if they do not exist
cp -r "${CACHE_DIRECTORY}" . || true
fi
# This has already been cached in the docker image
lintrunner init 2> /dev/null
RC=0
# Run lintrunner on all files
if ! lintrunner --force-color --all-files --tee-json=lint.json 2> /dev/null; then
echo ""
echo -e "\e[1m\e[36mYou can reproduce these results locally by using \`lintrunner\`. (If you don't get the same results, run \'lintrunner init\' to update your local linter)\e[0m"
echo -e "\e[1m\e[36mSee https://github.com/pytorch/pytorch/wiki/lintrunner for setup instructions.\e[0m"
RC=1
fi
# Use jq to massage the JSON lint output into GitHub Actions workflow commands.
jq --raw-output \
'"::\(if .severity == "advice" or .severity == "disabled" then "warning" else .severity end) file=\(.path),line=\(.line),col=\(.char),title=\(.code) \(.name)::" + (.description | gsub("\\n"; "%0A"))' \
lint.json || true
exit $RC