Work around dmlc#10994

tests/test_distributed/test_gpu_with_dask/test_gpu_with_dask.py

@@ -10,6 +10,7 @@
 import pytest
 from hypothesis import given, note, settings, strategies
 from hypothesis._settings import duration
+from packaging.version import parse as parse_version
 
 import xgboost as xgb
 from xgboost import testing as tm
@@ -41,14 +42,20 @@
 try:
     import cudf
     import dask.dataframe as dd
+    from dask import __version__ as dask_version
     from dask import array as da
     from dask.distributed import Client
     from dask_cuda import LocalCUDACluster
 
     from xgboost import dask as dxgb
     from xgboost.testing.dask import check_init_estimation, check_uneven_nan
 except ImportError:
-    pass
+    dask_version = None
+
+
+dask_version_ge110 = dask_version and parse_version(dask_version) >= parse_version(
+    "2024.11.0"
+)
 
 
 def run_with_dask_dataframe(DMatrixT: Type, client: Client) -> None:
@@ -378,6 +385,9 @@ def test_early_stopping(self, local_cuda_client: Client) -> None:
         dump = booster.get_dump(dump_format="json")
         assert len(dump) - booster.best_iteration == early_stopping_rounds + 1
 
+    @pytest.mark.xfail(
+        dask_version_ge110, reason="Test cannot pass with Dask 2024.11.0+"
+    )
     @pytest.mark.skipif(**tm.no_cudf())
     @pytest.mark.parametrize("model", ["boosting"])
     def test_dask_classifier(self, model: str, local_cuda_client: Client) -> None: