chore(workflow): use Python 3.7 in tests

metaopt · XuehaiPan · Jul 10, 2022 · Jul 7, 2022 · Jul 7, 2022 · Jul 7, 2022
commit 8640b814d6d1e37fddffbb79448741c5520d8064
diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml
@@ -22,10 +22,11 @@ jobs:
           submodules: "recursive"
           fetch-depth: 1
 
-      - name: Set up Python 3.8
+      - name: Set up Python 3.7  # the lowest version we support
         uses: actions/setup-python@v4
         with:
-          python-version: "3.8"
+          python-version: "3.7"
+          update-environment: true
 
       - name: Setup CUDA Toolkit
         uses: Jimver/cuda-toolkit@v0.2.7

diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
@@ -24,10 +24,11 @@ jobs:
           submodules: "recursive"
           fetch-depth: 1
 
-      - name: Set up Python 3.8
+      - name: Set up Python 3.7  # the lowest version we support
         uses: actions/setup-python@v4
         with:
-          python-version: "3.8"
+          python-version: "3.7"
+          update-environment: true
 
       - name: Setup CUDA Toolkit
         uses: Jimver/cuda-toolkit@v0.2.7

diff --git a/tests/requirements.txt b/tests/requirements.txt
@@ -1,5 +1,8 @@
 -r ../requirements.txt
 
-pytest
 torchvision
 functorch
+
+pytest
+pytest_cov
+pytest_xdist
diff --git a/tests/unit/high_level/test_high_level_inplace.py b/tests/unit/high_level/test_high_level_inplace.py
@@ -124,7 +124,7 @@ def test_accelerated_adam_cpu(self) -> None:
                 mse = F.mse_loss(b, b_ref)
                 self.assertAlmostEqual(float(mse), 0)
 
-    @pytest.mark.skipIf(not torch.cuda.is_available(), reason='No CUDA device available.')
+    @pytest.mark.skipif(not torch.cuda.is_available(), reason='No CUDA device available.')
     def test_accelerated_adam_cuda(self) -> None:
         self.model.cuda()
         self.model_ref.cuda()

diff --git a/tests/unit/low_level/test_low_level_inplace.py b/tests/unit/low_level/test_low_level_inplace.py
@@ -136,7 +136,7 @@ def test_accelerated_adam_cpu(self) -> None:
                 mse = F.mse_loss(b, b_ref)
                 self.assertAlmostEqual(float(mse), 0)
 
-    @pytest.mark.skipIf(not torch.cuda.is_available(), reason='No CUDA device available.')
+    @pytest.mark.skipif(not torch.cuda.is_available(), reason='No CUDA device available.')
     def test_accelerated_adam_cuda(self) -> None:
         self.model.cuda()
         self.model_ref.cuda()