try nvidia-cuda docker img, should clone faster #18

	name: 8 GPU 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

	jobs:
	build-test:
	uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
	with:
	runner: linux.g5.48xlarge.nvidia.gpu
	gpu-arch-type: cuda
	gpu-arch-version: "12.1"
	docker-image: "pytorch/pytorch:2.3.0-cuda12.1-cudnn8-runtime"
	repository: "pytorch/torchtitan"
	upload-artifact: "outputs"
	script: \|
	python -m pip uninstall torch
	python -m pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu121
	python -m pip install -r requirements.txt
	python -m pip install -r dev-requirements.txt
	python -m pip install git
	python -m pip install git+https://github.com/pytorch/pippy
	./run_llama_train.sh
	mv outputs artifacts-to-be-uploaded
	# upload-coverage:
	# - name: Upload Coverage to Codecov
	# uses: codecov/codecov-action@v3

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