Migrate to macos-latest

Signed-off-by: Keith Battocchi <kebatt@microsoft.com>
py-why · Nov 13, 2024 · 5ab0bf1 · 5ab0bf1
1 parent 56e48c5
commit 5ab0bf1
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Showing 2 changed files with 15 additions and 8 deletions.
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
@@ -203,13 +203,16 @@ jobs:
     if: ${{ needs.eval.outputs.testCode == 'True' }}
     strategy:
       matrix:
-        os: [ubuntu-latest, windows-latest, macos-12]
+        os: [ubuntu-latest, windows-latest, macos-latest]
         python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
         kind: [serial, other, dml, main, treatment, ray]
         exclude:
           # Serial tests fail randomly on mac sometimes, so we don't run them there
-          - os: macos-12
+          - os: macos-latest
             kind: serial
+          # Mac ARM doesn't support tensorflow versions compatible with python 3.8
+          - os: macos-latest
+            python-version: '3.8'        
           # Ray tests run out of memory on Windows
           - os: windows-latest
             kind: ray
@@ -249,6 +252,10 @@ jobs:
       uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
+    - name: Install libomp
+      # lightgbm needs libomp on mac
+      run: brew install libomp
+      if: matrix.os == 'macos-latest'
     - name: Install uv
       # check if we're running on windows
       run: ${{ runner.os == 'Windows' && 'irm https://astral.sh/uv/install.ps1 | iex' || 'curl -LsSf https://astral.sh/uv/install.sh | sh' }}
@@ -299,7 +306,7 @@ jobs:
     strategy:
       matrix:
         kind: [tests]
-        os: [ubuntu-latest, windows-latest, macos-12]
+        os: [ubuntu-latest, windows-latest, macos-latest]
         python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
         extras: ["[tf,plt,dowhy,ray]"]
         include:

diff --git a/econml/tests/test_grf_python.py b/econml/tests/test_grf_python.py
@@ -494,10 +494,10 @@ def test_projection(self,):
         forest = RegressionForest(**config).fit(X, y)
         projector = np.ones((X.shape[0], 2)) / 2.0
         mean_proj, var_proj = forest.predict_projection_and_var(X, projector)
-        np.testing.assert_array_equal(mean_proj, mean)
-        np.testing.assert_array_equal(var_proj, var)
-        np.testing.assert_array_equal(var_proj, forest.predict_projection_var(X, projector))
-        np.testing.assert_array_equal(mean_proj, forest.predict_projection(X, projector))
+        np.testing.assert_allclose(mean_proj, mean)
+        np.testing.assert_allclose(var_proj, var)
+        np.testing.assert_allclose(var_proj, forest.predict_projection_var(X, projector))
+        np.testing.assert_allclose(mean_proj, forest.predict_projection(X, projector))
         return
 
     def test_feature_importances(self,):
@@ -547,7 +547,7 @@ def test_feature_importances(self,):
                             feature_importances /= tw[0]
                             totest = tree.tree_.compute_feature_importances(normalize=False,
                                                                             max_depth=max_depth, depth_decay=2.0)
-                            np.testing.assert_array_equal(feature_importances, totest)
+                            np.testing.assert_allclose(feature_importances, totest)
 
                             het_importances = np.zeros(n_features)
                             for it, (feat, depth, left, right, w) in\