Suppress hypothesis health check for dask client. (#6589)

tests/python-gpu/test_gpu_with_dask.py

@@ -6,7 +6,7 @@ import numpy as np
 import asyncio
 import xgboost
 import subprocess
-from hypothesis import given, strategies, settings, note
+from hypothesis import given, strategies, settings, note, HealthCheck
 from hypothesis._settings import duration
 from test_gpu_updaters import parameter_strategy
 
@@ -18,6 +18,7 @@ from test_with_dask import run_empty_dmatrix_reg  # noqa
 from test_with_dask import run_empty_dmatrix_cls  # noqa
 from test_with_dask import _get_client_workers  # noqa
 from test_with_dask import generate_array     # noqa
+from test_with_dask import suppress
 import testing as tm                          # noqa
 
 
@@ -171,25 +172,30 @@ class TestDistributedGPU:
             run_with_dask_dataframe(dxgb.DaskDMatrix, client)
             run_with_dask_dataframe(dxgb.DaskDeviceQuantileDMatrix, client)
 
-    @given(params=parameter_strategy, num_rounds=strategies.integers(1, 20),
+    @given(
-           dataset=tm.dataset_strategy)
+        params=parameter_strategy,
-    @settings(deadline=duration(seconds=120))
+        num_rounds=strategies.integers(1, 20),
+        dataset=tm.dataset_strategy,
+    )
+    @settings(deadline=duration(seconds=120), suppress_health_check=suppress)
     @pytest.mark.skipif(**tm.no_dask())
     @pytest.mark.skipif(**tm.no_dask_cuda())
-    @pytest.mark.parametrize('local_cuda_cluster', [{'n_workers': 2}], indirect=['local_cuda_cluster'])
+    @pytest.mark.parametrize(
+        "local_cuda_cluster", [{"n_workers": 2}], indirect=["local_cuda_cluster"]
+    )
     @pytest.mark.mgpu
     def test_gpu_hist(
         self,
         params: Dict,
         num_rounds: int,
         dataset: tm.TestDataset,
-        local_cuda_cluster: LocalCUDACluster
+        local_cuda_cluster: LocalCUDACluster,
     ) -> None:
         with Client(local_cuda_cluster) as client:
-            run_gpu_hist(params, num_rounds, dataset, dxgb.DaskDMatrix,
+            run_gpu_hist(params, num_rounds, dataset, dxgb.DaskDMatrix, client)
-                         client)
+            run_gpu_hist(
-            run_gpu_hist(params, num_rounds, dataset,
+                params, num_rounds, dataset, dxgb.DaskDeviceQuantileDMatrix, client
-                         dxgb.DaskDeviceQuantileDMatrix, client)
+            )
 
     @pytest.mark.skipif(**tm.no_cupy())
     @pytest.mark.skipif(**tm.no_dask())

tests/python/test_with_dask.py

@@ -14,7 +14,8 @@ from sklearn.datasets import make_classification
 import sklearn
 import os
 import subprocess
-from hypothesis import given, settings, note
+import hypothesis
+from hypothesis import given, settings, note, HealthCheck
 from test_updaters import hist_parameter_strategy, exact_parameter_strategy
 from test_with_sklearn import run_feature_weights
 
@@ -23,14 +24,19 @@ if sys.platform.startswith("win"):
 if tm.no_dask()['condition']:
     pytest.skip(msg=tm.no_dask()['reason'], allow_module_level=True)
 
-
+from distributed import LocalCluster, Client
-from distributed import LocalCluster, Client, get_client
 from distributed.utils_test import client, loop, cluster_fixture
 import dask.dataframe as dd
 import dask.array as da
 from xgboost.dask import DaskDMatrix
 
 
+if hasattr(HealthCheck, 'function_scoped_fixture'):
+    suppress = [HealthCheck.function_scoped_fixture]
+else:
+    suppress = hypothesis.utils.conventions.not_set
+
+
 kRows = 1000
 kCols = 10
 kWorkers = 5
@@ -803,7 +809,7 @@ class TestWithDask:
 
     @given(params=hist_parameter_strategy,
            dataset=tm.dataset_strategy)
-    @settings(deadline=None)
+    @settings(deadline=None, suppress_health_check=suppress)
     def test_hist(
             self, params: Dict, dataset: tm.TestDataset, client: "Client"
     ) -> None:
@@ -812,7 +818,7 @@ class TestWithDask:
 
     @given(params=exact_parameter_strategy,
            dataset=tm.dataset_strategy)
-    @settings(deadline=None)
+    @settings(deadline=None, suppress_health_check=suppress)
     def test_approx(
             self, client: "Client", params: Dict, dataset: tm.TestDataset
     ) -> None: