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Move CI to Github Actions (pytorch#620)
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Summary:

Moves the continuous integration (CI) processy from CircleCI to Github Actions. The changes include creating new yml files to define the CI workflows that largely mimic the existing circleCi config.

There are two new workflows, one for cpu jobs and one for gpu jobs.

NOTE: Currently, the CPU jobs are running fine, but NOT the GPU jobs.

Reviewed By: HuanyuZhang

Differential Revision: D53107145
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Karthik Prasad authored and facebook-github-bot committed Jan 30, 2024
1 parent 8ec2d12 commit a0c4e18
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170 changes: 170 additions & 0 deletions .github/workflows/ci_cpu.yml
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name: CI_CPU

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 ##############
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 .

########### UNIT TESTS ##############
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

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
########### NIGHTLY TEST ##############
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
python -m pytest --doctest-modules -p conftest --junitxml=unittest-py39-nightly-reports/junit.xml opacus
- name: Store test results
uses: actions/upload-artifact@v2
with:
name: unittest-py39-nightly-reports
path: unittest-py39-nightly-reports

########### INTEGRATION TEST ##############
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

######## FINISH COVERALLS ##########
finish_coveralls_parallel:
needs: [unittest_py38_torch_release, unittest_py39_torch_release, integrationtest_py39_torch_release_cpu]
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v2
- name: Finish Coveralls Parallel
uses: coverallsapp/github-action@v2
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
parallel-finished: true
173 changes: 173 additions & 0 deletions .github/workflows/ci_gpu.yml
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name: CI_GPU

on:
push:
branches:
- main
pull_request:
branches:
- main

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: |
./scripts/install_via_pip.sh -c
- name: Run multi-GPU unit tests
run: |
nvidia-smi
nvcc --version
python -m unittest opacus.tests.multigpu_gradcheck.GradientComputationTest.test_gradient_correct
integrationtest_py39_torch_release_cuda:
runs-on: ubuntu-latest
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/
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