[RFC] Online and offline adaptive batching in torchtune. #6463

	name: Unit Test

	on:
	push:
	branches: [ main ]
	pull_request:

	concurrency:
	group: unit-test${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_number \|\| github.ref }}
	cancel-in-progress: true

	defaults:
	run:
	shell: bash -l -eo pipefail {0}

	jobs:
	unit_tests:
	if: github.repository_owner == 'pytorch'
	runs-on: ubuntu-latest
	strategy:
	matrix:
	python-version: ['3.9', '3.10', '3.11']
	steps:
	- name: Check out repo
	uses: actions/checkout@v3
	- name: Setup conda env
	uses: conda-incubator/setup-miniconda@v2
	with:
	auto-update-conda: true
	miniconda-version: "latest"
	activate-environment: test
	python-version: ${{ matrix.python-version }}
	- name: Update pip
	run: python -m pip install --upgrade pip
	- name: Install dependencies
	run: \|
	python -m pip install torch torchvision torchao
	python -m pip install -e ".[dev]"
	- name: Run unit tests with coverage
	run: pytest tests --ignore tests/torchtune/modules/_export --cov=. --cov-report=xml --durations=20 -vv
	- name: Upload Coverage to Codecov
	uses: codecov/codecov-action@v3

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