temp tests

wyli · wyli · commit 1356e8e968d3 · 2021-11-09T11:26:19.000Z
Signed-off-by: Wenqi Li &lt;wenqil@nvidia.com&gt;
diff --git a/.github/workflows/cron.yml b/.github/workflows/cron.yml
@@ -5,64 +5,16 @@ on:
   #   - cron: "0 2 * * *"  # at 02:00 UTC
   # Allows you to run this workflow manually from the Actions tab
   workflow_dispatch:
+  push:
+    branches:
+      - test-2110
 
 jobs:
-  cron-gpu:
-    if: github.repository == 'Project-MONAI/MONAI'
-    container:
-      image: nvcr.io/nvidia/pytorch:20.03-py3  # CUDA 10.2
-      options: "--gpus all"
-    runs-on: [self-hosted, linux, x64, common]
-    strategy:
-      matrix:
-        pytorch-version: [1.5.1, 1.6.0, 1.7.1, 1.8.1, latest]
-    steps:
-    - uses: actions/checkout@v2
-    - name: Install the dependencies
-      run: |
-        which python
-        python -m pip install --upgrade pip wheel
-        python -m pip uninstall -y torch torchvision
-        if [ ${{ matrix.pytorch-version }} == "latest" ]; then
-          python -m pip install torch torchvision
-        elif [ ${{ matrix.pytorch-version }} == "1.5.1" ]; then
-          python -m pip install torch==1.5.1 torchvision==0.6.1
-        elif [ ${{ matrix.pytorch-version }} == "1.6.0" ]; then
-          python -m pip install torch==1.6.0 torchvision==0.7.0
-        elif [ ${{ matrix.pytorch-version }} == "1.7.1" ]; then
-          python -m pip install torch==1.7.1 torchvision==0.8.2
-        elif [ ${{ matrix.pytorch-version }} == "1.8.1" ]; then
-          python -m pip install torch==1.8.1 torchvision==0.9.1
-        fi
-        python -m pip install -r requirements-dev.txt
-        python -m pip list
-    - name: Run tests report coverage
-      run: |
-        export LAUNCH_DELAY=$[ $RANDOM % 16 * 60 ]
-        echo "Sleep $LAUNCH_DELAY"
-        sleep $LAUNCH_DELAY
-        nvidia-smi
-        export CUDA_VISIBLE_DEVICES=$(python -m tests.utils)
-        echo $CUDA_VISIBLE_DEVICES
-        trap 'if pgrep python; then pkill python; fi;' ERR
-        python -c $'import torch\na,b=torch.zeros(1,device="cuda:0"),torch.zeros(1,device="cuda:1");\nwhile True:print(a,b)' > /dev/null &
-        python -c "import torch; print(torch.__version__); print('{} of GPUs available'.format(torch.cuda.device_count()))"
-        python -c 'import torch; print(torch.rand(5, 3, device=torch.device("cuda:0")))'
-        BUILD_MONAI=1 ./runtests.sh --coverage --unittests  # unit tests with coverage report
-        BUILD_MONAI=1 ./runtests.sh --coverage --net  # integration tests with coverage report
-        coverage xml
-        if pgrep python; then pkill python; fi
-    - name: Upload coverage
-      uses: codecov/codecov-action@v1
-      with:
-        fail_ci_if_error: false
-        file: ./coverage.xml
-
   cron-pt-image:
     if: github.repository == 'Project-MONAI/MONAI'
     strategy:
       matrix:
-        container: ["pytorch:21.02", "pytorch:21.10"]  # 21.02 for backward comp.
+        container: ["pytorch:21.10"]  # 21.02 for backward comp.
     container:
       image: nvcr.io/nvidia/${{ matrix.container }}-py3  # testing with the latest pytorch base image
       options: "--gpus all"
@@ -106,7 +58,7 @@ jobs:
     if: github.repository == 'Project-MONAI/MONAI'
     strategy:
       matrix:
-        container: ["pytorch:21.02", "pytorch:21.10"]  # 21.02 for backward comp.
+        container: ["pytorch:21.10"]  # 21.02 for backward comp.
     container:
       image: nvcr.io/nvidia/${{ matrix.container }}-py3  # testing with the latest pytorch base image
       options: "--gpus all"
@@ -170,41 +122,10 @@ jobs:
           PYTHONPATH="$tmp_dir":$PYTHONPATH BUILD_MONAI=1 python ./tests/runner.py -p 'test_((?!integration).)'  # unit tests
           if pgrep python; then pkill python; fi
 
-  cron-docker:
-    if: github.repository == 'Project-MONAI/MONAI'
-    container:
-      image: docker://projectmonai/monai:latest  # this might be slow and has the pull count limitations
-      options: "--gpus all"
-    runs-on: [self-hosted, linux, x64, common]
-    steps:
-    - name: Run tests report coverage
-      # The docker image process has done the compilation.
-      # BUILD_MONAI=1 is necessary for triggering the USE_COMPILED flag.
-      run: |
-        cd /opt/monai
-        nvidia-smi
-        export CUDA_VISIBLE_DEVICES=$(python -m tests.utils)
-        echo $CUDA_VISIBLE_DEVICES
-        trap 'if pgrep python; then pkill python; fi;' ERR
-        python -c $'import torch\na,b=torch.zeros(1,device="cuda:0"),torch.zeros(1,device="cuda:1");\nwhile True:print(a,b)' > /dev/null &
-        python -c "import torch; print(torch.__version__); print('{} of GPUs available'.format(torch.cuda.device_count()))"
-        python -c 'import torch; print(torch.rand(5,3, device=torch.device("cuda:0")))'
-        ngc --version
-        BUILD_MONAI=1 ./runtests.sh --coverage --pytype --unittests  # unit tests with pytype checks, coverage report
-        BUILD_MONAI=1 ./runtests.sh --coverage --net  # integration tests with coverage report
-        coverage xml
-        if pgrep python; then pkill python; fi
-    - name: Upload coverage
-      uses: codecov/codecov-action@v1
-      with:
-        fail_ci_if_error: false
-        file: ./coverage.xml
-
   cron-tutorial-notebooks:
     if: github.repository == 'Project-MONAI/MONAI'
-    needs: cron-gpu  # so that monai itself is verified first
     container:
-      image: nvcr.io/nvidia/pytorch:21.09-py3  # testing with the latest pytorch base image
+      image: nvcr.io/nvidia/pytorch:21.10-py3  # testing with the latest pytorch base image
       options: "--gpus all --ipc=host"
     runs-on: [self-hosted, linux, x64, common]
     steps:
