Use in-memory communicator to test quantile (#8710)

tests/test_distributed/test_with_dask/test_with_dask.py

@@ -1490,62 +1490,6 @@ class TestWithDask:
         num_rounds = 10
         self.run_updater_test(client, params, num_rounds, dataset, 'approx')
 
-    def run_quantile(self, name: str) -> None:
-        exe: Optional[str] = None
-        for possible_path in {'./testxgboost', './build/testxgboost',
-                              '../build/cpubuild/testxgboost',
-                              '../cpu-build/testxgboost'}:
-            if os.path.exists(possible_path):
-                exe = possible_path
-        if exe is None:
-            return
-
-        test = "--gtest_filter=Quantile." + name
-
-        def runit(
-            worker_addr: str, rabit_args: Dict[str, Union[int, str]]
-        ) -> subprocess.CompletedProcess:
-            # setup environment for running the c++ part.
-            env = os.environ.copy()
-            env['DMLC_TRACKER_PORT'] = str(rabit_args['DMLC_TRACKER_PORT'])
-            env["DMLC_TRACKER_URI"] = str(rabit_args["DMLC_TRACKER_URI"])
-            return subprocess.run([str(exe), test], env=env, capture_output=True)
-
-        with LocalCluster(n_workers=4, dashboard_address=":0") as cluster:
-            with Client(cluster) as client:
-                workers = tm.get_client_workers(client)
-                rabit_args = client.sync(
-                    xgb.dask._get_rabit_args, len(workers), None, client
-                )
-                futures = client.map(runit,
-                                     workers,
-                                     pure=False,
-                                     workers=workers,
-                                     rabit_args=rabit_args)
-                results = client.gather(futures)
-
-                for ret in results:
-                    msg = ret.stdout.decode('utf-8')
-                    assert msg.find('1 test from Quantile') != -1, msg
-                    assert ret.returncode == 0, msg
-
-    @pytest.mark.skipif(**tm.no_dask())
-    @pytest.mark.gtest
-    def test_quantile_basic(self) -> None:
-        self.run_quantile('DistributedBasic')
-        self.run_quantile('SortedDistributedBasic')
-
-    @pytest.mark.skipif(**tm.no_dask())
-    @pytest.mark.gtest
-    def test_quantile(self) -> None:
-        self.run_quantile('Distributed')
-        self.run_quantile('SortedDistributed')
-
-    @pytest.mark.skipif(**tm.no_dask())
-    @pytest.mark.gtest
-    def test_quantile_same_on_all_workers(self) -> None:
-        self.run_quantile("SameOnAllWorkers")
-
     def test_adaptive(self) -> None:
         def get_score(config: Dict) -> float:
             return float(config["learner"]["learner_model_param"]["base_score"])