Predict on Ellpack. (#5327)

* Unify GPU prediction node.
* Add `PageExists`.
* Dispatch prediction on input data for GPU Predictor.

tests/cpp/predictor/test_predictor.h

@@ -0,0 +1,70 @@
+#ifndef XGBOOST_TEST_PREDICTOR_H_
+#define XGBOOST_TEST_PREDICTOR_H_
+
+#include <xgboost/predictor.h>
+#include <string>
+#include <cstddef>
+#include "../helpers.h"
+
+namespace xgboost {
+template <typename Page>
+void TestPredictionFromGradientIndex(std::string name, size_t rows, int32_t bins) {
+  constexpr size_t kCols { 8 }, kClasses { 3 };
+
+  LearnerModelParam param;
+  param.num_feature = kCols;
+  param.num_output_group = kClasses;
+  param.base_score = 0.5;
+
+  auto lparam = CreateEmptyGenericParam(0);
+
+  std::unique_ptr<Predictor> predictor =
+      std::unique_ptr<Predictor>(Predictor::Create(name, &lparam));
+  predictor->Configure({});
+
+  gbm::GBTreeModel model = CreateTestModel(&param, kClasses);
+
+  {
+    auto pp_ellpack = CreateDMatrix(rows, kCols, 0);
+    auto p_ellpack = *pp_ellpack;
+    // Use same number of bins as rows.
+    for (auto const &page DMLC_ATTRIBUTE_UNUSED :
+         p_ellpack->GetBatches<Page>({0, static_cast<int32_t>(bins), 0})) {
+    }
+
+    auto pp_precise = CreateDMatrix(rows, kCols, 0);
+    auto p_precise = *pp_precise;
+
+    PredictionCacheEntry approx_out_predictions;
+    predictor->PredictBatch(p_ellpack.get(), &approx_out_predictions, model, 0);
+
+    PredictionCacheEntry precise_out_predictions;
+    predictor->PredictBatch(p_precise.get(), &precise_out_predictions, model, 0);
+
+    for (size_t i = 0; i < rows; ++i) {
+      CHECK_EQ(approx_out_predictions.predictions.HostVector()[i],
+               precise_out_predictions.predictions.HostVector()[i]);
+    }
+
+    delete pp_precise;
+    delete pp_ellpack;
+  }
+
+  {
+    // Predictor should never try to create the histogram index by itself.  As only
+    // histogram index from training data is valid and predictor doesn't known which
+    // matrix is used for training.
+    auto pp_dmat = CreateDMatrix(rows, kCols, 0);
+    auto p_dmat = *pp_dmat;
+    PredictionCacheEntry precise_out_predictions;
+    predictor->PredictBatch(p_dmat.get(), &precise_out_predictions, model, 0);
+    ASSERT_FALSE(p_dmat->PageExists<Page>());
+    delete pp_dmat;
+  }
+}
+
+void TestTrainingPrediction(size_t rows, std::string tree_method);
+
+}  // namespace xgboost
+
+#endif  // XGBOOST_TEST_PREDICTOR_H_