[dask] Allow empty data matrix in AFT survival (#6379)

* [dask] Allow empty data matrix in AFT survival

* Add unit test

src/metric/survival_metric.cu

@@ -206,10 +206,6 @@ struct EvalEWiseSurvivalBase : public Metric {
   bst_float Eval(const HostDeviceVector<bst_float>& preds,
                  const MetaInfo& info,
                  bool distributed) override {
-    CHECK_NE(info.labels_lower_bound_.Size(), 0U)
-      << "labels_lower_bound cannot be empty";
-    CHECK_NE(info.labels_upper_bound_.Size(), 0U)
-      << "labels_upper_bound cannot be empty";
     CHECK_EQ(preds.Size(), info.labels_lower_bound_.Size());
     CHECK_EQ(preds.Size(), info.labels_upper_bound_.Size());
 

tests/python/test_survival.py

@@ -52,6 +52,16 @@ def test_aft_survival_toy_data():
     for tree in model_json:
         assert gather_split_thresholds(tree).issubset({2.5, 3.5, 4.5})
 
+
+def test_aft_empty_dmatrix():
+    X = np.array([]).reshape((0, 2))
+    y_lower, y_upper = np.array([]), np.array([])
+    dtrain = xgb.DMatrix(X)
+    dtrain.set_info(label_lower_bound=y_lower, label_upper_bound=y_upper)
+    bst = xgb.train({'objective': 'survival:aft', 'tree_method': 'hist'},
+                    dtrain, num_boost_round=2, evals=[(dtrain, 'train')])
+
+
 @pytest.mark.skipif(**tm.no_pandas())
 def test_aft_survival_demo_data():
     import pandas as pd

tests/python/test_with_dask.py

@@ -594,7 +594,6 @@ def test_predict_with_meta(client):
 
 
 def run_aft_survival(client, dmatrix_t):
-    # survival doesn't handle empty dataset well.
     df = dd.read_csv(os.path.join(tm.PROJECT_ROOT, 'demo', 'data',
                                   'veterans_lung_cancer.csv'))
     y_lower_bound = df['Survival_label_lower_bound']
@@ -632,7 +631,7 @@ def run_aft_survival(client, dmatrix_t):
 
 
 def test_aft_survival():
-    with LocalCluster(n_workers=1) as cluster:
+    with LocalCluster(n_workers=kWorkers) as cluster:
         with Client(cluster) as client:
             run_aft_survival(client, DaskDMatrix)