Freeze dask version to 2024.11 for now.

python-package/xgboost/compat.py

@@ -161,4 +161,4 @@ def concat(value: Sequence[_T]) -> _T:  # pylint: disable=too-many-return-statem
             d_v = arr.device.id
             assert d_v == d, "Concatenating arrays on different devices."
         return cupy.concatenate(value, axis=0)
-    raise TypeError("Unknown type.")
+    raise TypeError(f"Unknown type: {type(value[0])}")

tests/ci_build/conda_env/linux_sycl_test.yml

@@ -17,7 +17,7 @@ dependencies:
 - pytest
 - pytest-timeout
 - pytest-cov
-- dask
+- dask=2024.11
 - dpcpp_linux-64
 - onedpl-devel
 - intel-openmp

tests/python-sycl/test_sycl_simple_dask.py

@@ -1,8 +1,6 @@
 from xgboost import dask as dxgb
 from xgboost import testing as tm
 
-from hypothesis import given, strategies, assume, settings, note
-
 import dask.array as da
 import dask.distributed
 
@@ -32,10 +30,12 @@ def test_simple(self):
         param["objective"] = "reg:squarederror"
 
         # X and y must be Dask dataframes or arrays
-        num_obs = 1e4
+        num_obs = int(1e4)
         num_features = 20
-        X = da.random.random(size=(num_obs, num_features), chunks=(1000, num_features))
-        y = da.random.random(size=(num_obs, 1), chunks=(1000, 1))
+
+        rng = da.random.RandomState(1994)
+        X = rng.random_sample((num_obs, num_features), chunks=(1000, -1))
+        y = X.sum(axis=1)
         dtrain = dxgb.DaskDMatrix(client, X, y)
 
         result = train_result(client, param, dtrain, 10)