Merge branch 'master' into vignette

dmlc · Jan 7, 2025 · 196273d · 196273d
2 parents 107f18d + 4500941
commit 196273d
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Showing 4 changed files with 12 additions and 4 deletions.
diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
@@ -174,6 +174,7 @@ jobs:
       - runner=${{ matrix.runner }}
       - run-id=${{ github.run_id }}
       - tag=main-test-cpp-gpu-${{ matrix.suite }}
+    timeout-minutes: 30
     strategy:
       fail-fast: false
       matrix:
@@ -213,6 +214,7 @@ jobs:
       - runner=${{ matrix.runner }}
       - run-id=${{ github.run_id }}
       - tag=main-test-python-wheel-${{ matrix.description }}
+    timeout-minutes: 60
     strategy:
       fail-fast: false
       matrix:

diff --git a/tests/test_distributed/test_gpu_with_dask/test_gpu_ranking.py b/tests/test_distributed/test_gpu_with_dask/test_gpu_ranking.py
@@ -4,8 +4,15 @@
 import pytest
 from distributed import Client
 
+from xgboost import testing as tm
 from xgboost.testing import dask as dtm
 
+pytestmark = [
+    pytest.mark.skipif(**tm.no_dask()),
+    pytest.mark.skipif(**tm.no_dask_cuda()),
+    tm.timeout(120),
+]
+
 
 @pytest.mark.filterwarnings("error")
 def test_no_group_split(local_cuda_client: Client) -> None:

diff --git a/tests/test_distributed/test_gpu_with_dask/test_gpu_with_dask.py b/tests/test_distributed/test_gpu_with_dask/test_gpu_with_dask.py
@@ -376,8 +376,6 @@ def test_early_stopping(self, local_cuda_client: Client) -> None:
     @pytest.mark.skipif(**tm.no_cudf())
     @pytest.mark.parametrize("model", ["boosting"])
     def test_dask_classifier(self, model: str, local_cuda_client: Client) -> None:
-        import dask_cudf
-
         X_, y_, w_ = generate_array(with_weights=True)
         y_ = (y_ * 10).astype(np.int32)
         X = dd.from_dask_array(X_).to_backend("cudf")

diff --git a/tests/test_distributed/test_with_dask/test_with_dask.py b/tests/test_distributed/test_with_dask/test_with_dask.py
@@ -643,7 +643,7 @@ def run_dask_classifier(
     tree_method: Optional[str],
     device: Literal["cpu", "cuda"],
     client: "Client",
-    n_classes,
+    n_classes: int,
 ) -> None:
     metric = "merror" if n_classes > 2 else "logloss"
 
@@ -930,8 +930,9 @@ def run_empty_dmatrix_auc(client: "Client", device: str, n_workers: int) -> None
     valid_X = dd.from_array(valid_X_, chunksize=n_samples)
     valid_y = dd.from_array(valid_y_, chunksize=n_samples)
 
+    # Specify base score in case if there are only two workers and one sample.
     cls = dxgb.DaskXGBClassifier(
-        device=device, n_estimators=2, eval_metric=["auc", "aucpr"]
+        device=device, n_estimators=2, eval_metric=["auc", "aucpr"], base_score=0.5
     )
     cls.fit(X, y, eval_set=[(valid_X, valid_y)])