Move CI to Github Actions #12

Workflow file for this run

	name: CI

	on:
	push:
	branches:
	- main
	pull_request:
	branches:
	- main
	schedule:
	- cron: '4 4 * * *' # This schedule runs the nightly job every night at 4:04AM


	jobs:
	lint_py39_torch_release:
	runs-on: ubuntu-latest
	steps:
	- name: Checkout
	uses: actions/checkout@v2
	- name: Set up Python
	uses: actions/setup-python@v2
	with:
	python-version: 3.9
	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install flake8 black isort
	./scripts/install_via_pip.sh
	- name: Lint with flake8
	run: flake8 --config ./.github/workflows/flake8_config.ini
	- name: Lint with black
	run: black --check --diff --color .
	- name: Check import order with isort
	run: isort -v -l 88 -o opacus --lines-after-imports 2 -m 3 --trailing-comma --check-only .

	unittest_py38_torch_release:
	runs-on: ubuntu-latest
	steps:
	- name: Checkout
	uses: actions/checkout@v2
	- name: Set up Python
	uses: actions/setup-python@v2
	with:
	python-version: 3.8
	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install pytest coverage coveralls
	./scripts/install_via_pip.sh
	- name: Run unit tests
	run: \|
	mkdir unittest-py38-release-reports
	coverage run -m pytest --doctest-modules -p conftest --junitxml=unittest-py38-release-reports/junit.xml opacus
	coverage report -i -m
	- name: Store test results
	uses: actions/upload-artifact@v2
	with:
	name: unittest-py38-release-reports
	path: unittest-py38-release-reports

	unittest_py39_torch_release:
	runs-on: ubuntu-latest
	steps:
	- name: Checkout
	uses: actions/checkout@v2
	- name: Set up Python
	uses: actions/setup-python@v2
	with:
	python-version: 3.9
	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install pytest coverage coveralls
	./scripts/install_via_pip.sh
	- name: Run unit tests
	run: \|
	mkdir unittest-py39-release-reports
	coverage run -m pytest --doctest-modules -p conftest --junitxml=unittest-py39-release-reports/junit.xml opacus
	coverage report -i -m
	- name: Store test results
	uses: actions/upload-artifact@v2
	with:
	name: unittest-py39-release-reports
	path: unittest-py39-release-reports

	unittest_py39_torch_nightly:
	runs-on: ubuntu-latest
	if: ${{ github.event_name == 'schedule' }}
	steps:
	- name: Checkout
	uses: actions/checkout@v2
	- name: Set up Python
	uses: actions/setup-python@v2
	with:
	python-version: 3.9
	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install pytest coverage coveralls
	./scripts/install_via_pip.sh -n
	- name: Run unit tests
	run: \|
	mkdir unittest-py39-nightly-reports
	coverage run -m pytest --doctest-modules -p conftest --junitxml=unittest-py39-nightly-reports/junit.xml opacus
	coverage report -i -m
	- name: Store test results
	uses: actions/upload-artifact@v2
	with:
	name: unittest-py39-nightly-reports
	path: unittest-py39-nightly-reports

	prv_accountant_values:
	runs-on: ubuntu-latest
	steps:
	- name: Checkout
	uses: actions/checkout@v2
	- name: Set up Python
	uses: actions/setup-python@v2
	with:
	python-version: 3.9
	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	./scripts/install_via_pip.sh
	- name: Run prv accountant unit tests
	run: \|
	python -m unittest opacus.tests.prv_accountant

	integrationtest_py39_torch_release_cpu:
	runs-on: ubuntu-latest
	steps:
	- name: Checkout
	uses: actions/checkout@v2
	- name: Set up Python
	uses: actions/setup-python@v2
	with:
	python-version: 3.9
	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install pytest coverage coveralls
	./scripts/install_via_pip.sh
	- name: Run MNIST integration test (CPU)
	run: \|
	mkdir -p runs/mnist/data
	mkdir -p runs/mnist/test-reports
	coverage run examples/mnist.py --lr 0.25 --sigma 0.7 -c 1.5 --batch-size 64 --epochs 1 --data-root runs/mnist/data --n-runs 1 --device cpu
	python -c "import torch; accuracy = torch.load('run_results_mnist_0.25_0.7_1.5_64_1.pt'); exit(0) if (accuracy[0]>0.78 and accuracy[0]<0.95) else exit(1)"
	coverage report -i -m
	- name: Store test results
	uses: actions/upload-artifact@v2
	with:
	name: mnist-cpu-reports
	path: runs/mnist/test-reports

	integrationtest_py39_torch_release_cuda:
	runs-on: ubuntu-latest
	needs: [unittest_py39_torch_release]
	container:
	# https://hub.docker.com/r/nvidia/cuda
	image: nvidia/cuda:12.3.1-base-ubuntu22.04
	options: --gpus all
	env:
	TZ: 'UTC'
	steps:
	- name: Checkout
	uses: actions/checkout@v2

	- name: Set up Python
	uses: actions/setup-python@v2
	with:
	python-version: 3.9

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install pytest coverage coveralls
	./scripts/install_via_pip.sh -c

	- name: Install CUDA toolkit and cuDNN
	run: \|
	apt-get update
	apt-get install -y --no-install-recommends \
	cuda-toolkit-11-1 \
	libcudnn8=8.1.1.33-1+cuda11.1 \
	libcudnn8-dev=8.1.1.33-1+cuda11.1

	- name: Run MNIST integration test (CUDA)
	run: \|
	mkdir -p runs/mnist/data
	mkdir -p runs/mnist/test-reports
	python examples/mnist.py --lr 0.25 --sigma 0.7 -c 1.5 --batch-size 64 --epochs 1 --data-root runs/mnist/data --n-runs 1 --device cuda
	python -c "import torch; accuracy = torch.load('run_results_mnist_0.25_0.7_1.5_64_1.pt'); exit(0) if (accuracy[0]>0.78 and accuracy[0]<0.95) else exit(1)"

	- name: Store MNIST test results
	uses: actions/upload-artifact@v2
	with:
	name: mnist-gpu-reports
	path: runs/mnist/test-reports

	- name: Run CIFAR10 integration test (CUDA)
	run: \|
	mkdir -p runs/cifar10/data
	mkdir -p runs/cifar10/logs
	mkdir -p runs/cifar10/test-reports
	pip install tensorboard
	python examples/cifar10.py --lr 0.1 --sigma 1.5 -c 10 --batch-size 2000 --epochs 10 --data-root runs/cifar10/data --log-dir runs/cifar10/logs --device cuda
	python -c "import torch; model = torch.load('model_best.pth.tar'); exit(0) if (model['best_acc1']>0.4 and model['best_acc1']<0.49) else exit(1)"
	python examples/cifar10.py --lr 0.1 --sigma 1.5 -c 10 --batch-size 2000 --epochs 10 --data-root runs/cifar10/data --log-dir runs/cifar10/logs --device cuda --grad_sample_mode no_op
	python -c "import torch; model = torch.load('model_best.pth.tar'); exit(0) if (model['best_acc1']>0.4 and model['best_acc1']<0.49) else exit(1)"

	- name: Store CIFAR10 test results
	uses: actions/upload-artifact@v2
	with:
	name: cifar10-gpu-reports
	path: runs/cifar10/test-reports

	- name: Run IMDb integration test (CUDA)
	run: \|
	mkdir -p runs/imdb/data
	mkdir -p runs/imdb/test-reports
	pip install --user datasets transformers
	python examples/imdb.py --lr 0.02 --sigma 1.0 -c 1.0 --batch-size 64 --max-sequence-length 256 --epochs 2 --data-root runs/imdb/data --device cuda
	python -c "import torch; accuracy = torch.load('run_results_imdb_classification.pt'); exit(0) if (accuracy>0.54 and accuracy<0.66) else exit(1)"

	- name: Store IMDb test results
	uses: actions/upload-artifact@v2
	with:
	name: imdb-gpu-reports
	path: runs/imdb/test-reports

	- name: Run charlstm integration test (CUDA)
	run: \|
	mkdir -p runs/charlstm/data
	wget https://download.pytorch.org/tutorial/data.zip -O runs/charlstm/data/data.zip
	unzip runs/charlstm/data/data.zip -d runs/charlstm/data
	rm runs/charlstm/data/data.zip
	mkdir -p runs/charlstm/test-reports
	pip install scikit-learn
	python examples/char-lstm-classification.py --epochs=20 --learning-rate=2.0 --hidden-size=128 --delta=8e-5 --batch-size 400 --n-layers=1 --sigma=1.0 --max-per-sample-grad-norm=1.5 --data-root="runs/charlstm/data/data/names/" --device cuda --test-every 5
	python -c "import torch; accuracy = torch.load('run_results_chr_lstm_classification.pt'); exit(0) if (accuracy>0.60 and accuracy<0.80) else exit(1)"

	- name: Store test results
	uses: actions/upload-artifact@v2
	with:
	name: charlstm-gpu-reports
	path: runs/charlstm/test-reports

	micro_benchmarks_py39_torch_release_cuda:
	runs-on: ubuntu-latest
	needs: [integrationtest_py39_torch_release_cuda]
	container:
	# https://hub.docker.com/r/nvidia/cuda
	image: nvidia/cuda:12.3.1-base-ubuntu22.04
	options: --gpus all
	env:
	TZ: 'UTC'
	steps:
	- name: Checkout
	uses: actions/checkout@v2

	- name: Set up Python
	uses: actions/setup-python@v2
	with:
	python-version: 3.9

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install pytest coverage coveralls
	./scripts/install_via_pip.sh

	- name: Install CUDA toolkit and cuDNN
	run: \|
	apt-get update
	apt-get install -y --no-install-recommends \
	cuda-toolkit-11-1 \
	libcudnn8=8.1.1.33-1+cuda11.1 \
	libcudnn8-dev=8.1.1.33-1+cuda11.1

	- name: Run benchmark integration tests (CUDA)
	run: \|
	mkdir -p benchmarks/results/raw
	python benchmarks/run_benchmarks.py --batch_size 16 --layers "groupnorm instancenorm layernorm" --config_file ./benchmarks/config.json --root ./benchmarks/results/raw/ --cont
	IFS=$' ';layers=("groupnorm" "instancenorm" "layernorm"); rm -rf /tmp/report_layers; mkdir -p /tmp/report_layers; IFS=$'\n'; files=`( echo "${layers[]}" ) \| sed 's/./.\/benchmarks\/results\/raw\/&*/'`
	cp -v ${files[@]} /tmp/report_layers
	report_id=`IFS=$'-'; echo "${layers[*]}"`
	python benchmarks/generate_report.py --path-to-results /tmp/report_layers --save-path benchmarks/results/report-${report_id}.csv --format csv
	python benchmarks/generate_report.py --path-to-results /tmp/report_layers --save-path benchmarks/results/report-${report_id}.pkl --format pkl
	python benchmarks/check_threshold.py --report-path "./benchmarks/results/report-"$report_id".pkl" --metric runtime --threshold 3.0 --column "hooks/baseline"
	python benchmarks/check_threshold.py --report-path "./benchmarks/results/report-"$report_id".pkl" --metric memory --threshold 1.6 --column "hooks/baseline"

	- name: Store artifacts
	uses: actions/upload-artifact@v2
	with:
	name: benchmarks-reports
	path: benchmarks/results/

	unittest_multi_gpu:
	runs-on: linux.4xlarge.nvidia.gpu
	steps:
	- name: Checkout
	uses: actions/checkout@v2

	- name: Set up Python
	uses: actions/setup-python@v2
	with:
	python-version: 3.9

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install pytest coverage coveralls
	./scripts/install_via_pip.sh -c

	- name: Run multi-GPU unit tests
	run: \|
	nvidia-smi
	nvcc --version \| grep "cuda_"
	mkdir unittest-multigpu-reports
	coverage run -m unittest opacus.tests.multigpu_gradcheck.GradientComputationTest.test_gradient_correct
	coverage report -i -m

	- name: Store test results
	uses: actions/upload-artifact@v2
	with:
	name: unittest-multigpu-reports
	path: unittest-multigpu-reports

	finish_coveralls_parallel:
	runs-on: ubuntu-latest
	steps:
	- name: Checkout
	uses: actions/checkout@v2
	- name: Finish Coveralls Parallel
	run: \|
	python -m pip install --upgrade pip
	pip install coveralls --user
	coveralls --finish
	- name: coveralls upload
	timeout-minutes: 5
	run: \|
	python -m pip install --upgrade pip
	pip install coveralls --user
	COVERALLS_PARALLEL=true COVERALLS_FLAG_NAME="${GITHUB_JOB}" coveralls

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Move CI to Github Actions #12

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Move CI to Github Actions #12

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