Enhance inplace prediction. (#6653)

* Accept array interface for csr and array.
* Accept an optional proxy dmatrix for metainfo.

This constructs an explicit `_ProxyDMatrix` type in Python.

* Remove unused doc.
* Add strict output.

tests/python-gpu/test_device_quantile_dmatrix.py

@@ -11,8 +11,7 @@ import testing as tm
 class TestDeviceQuantileDMatrix:
     def test_dmatrix_numpy_init(self):
         data = np.random.randn(5, 5)
-        with pytest.raises(TypeError,
-                           match='is not supported for DeviceQuantileDMatrix'):
+        with pytest.raises(TypeError, match='is not supported'):
             xgb.DeviceQuantileDMatrix(data, np.ones(5, dtype=np.float64))
 
     @pytest.mark.skipif(**tm.no_cupy())

tests/python-gpu/test_gpu_prediction.py

@@ -141,6 +141,13 @@ class TestGPUPredict:
         assert np.allclose(cpu_train_score, gpu_train_score)
         assert np.allclose(cpu_test_score, gpu_test_score)
 
+    def run_inplace_base_margin(self, booster, dtrain, X, base_margin):
+        import cupy as cp
+        dtrain.set_info(base_margin=base_margin)
+        from_inplace = booster.inplace_predict(data=X, base_margin=base_margin)
+        from_dmatrix = booster.predict(dtrain)
+        cp.testing.assert_allclose(from_inplace, from_dmatrix)
+
     @pytest.mark.skipif(**tm.no_cupy())
     def test_inplace_predict_cupy(self):
         import cupy as cp
@@ -175,6 +182,9 @@ class TestGPUPredict:
         for i in range(10):
             run_threaded_predict(X, rows, predict_dense)
 
+        base_margin = cp_rng.randn(rows)
+        self.run_inplace_base_margin(booster, dtrain, X, base_margin)
+
     @pytest.mark.skipif(**tm.no_cudf())
     def test_inplace_predict_cudf(self):
         import cupy as cp
@@ -208,6 +218,9 @@ class TestGPUPredict:
         for i in range(10):
             run_threaded_predict(X, rows, predict_df)
 
+        base_margin = cudf.Series(rng.randn(rows))
+        self.run_inplace_base_margin(booster, dtrain, X, base_margin)
+
     @given(strategies.integers(1, 10),
            tm.dataset_strategy, shap_parameter_strategy)
     @settings(deadline=None)