Small refinements for JSON model. (#5112)

* Naming consistency.

* Remove duplicated test.

src/gbm/gbtree_model.cc

@@ -40,7 +40,7 @@ void GBTreeModel::Load(dmlc::Stream* fi) {
 void GBTreeModel::SaveModel(Json* p_out) const {
   auto& out = *p_out;
   CHECK_EQ(param.num_trees, static_cast<int>(trees.size()));
-  out["model_param"] = toJson(param);
+  out["gbtree_model_param"] = toJson(param);
   std::vector<Json> trees_json;
   size_t t = 0;
   for (auto const& tree : trees) {
@@ -61,7 +61,7 @@ void GBTreeModel::SaveModel(Json* p_out) const {
 }
 
 void GBTreeModel::LoadModel(Json const& in) {
-  fromJson(in["model_param"], &param);
+  fromJson(in["gbtree_model_param"], &param);
 
   trees.clear();
   trees_to_update.clear();

src/learner.cc

@@ -269,7 +269,7 @@ class LearnerImpl : public Learner {
   void LoadModel(Json const& in) override {
     CHECK(IsA<Object>(in));
     Version::Load(in, false);
-    auto const& learner = get<Object>(in["Learner"]);
+    auto const& learner = get<Object>(in["learner"]);
     mparam_.FromJson(learner.at("learner_model_param"));
 
     auto const& objective_fn = learner.at("objective");
@@ -305,8 +305,8 @@ class LearnerImpl : public Learner {
     Version::Save(p_out);
     Json& out { *p_out };
 
-    out["Learner"] = Object();
+    out["learner"] = Object();
-    auto& learner = out["Learner"];
+    auto& learner = out["learner"];
 
     learner["learner_model_param"] = mparam_.ToJson();
     learner["gradient_booster"] = Object();

tests/cpp/gbm/test_gblinear.cc

@@ -35,22 +35,14 @@ TEST(GBLinear, Json_IO) {
   std::string model_str;
   Json::Dump(model, &model_str);
 
-  model = Json::Load({model_str.c_str(), model_str.size()});
+  model = Json::Load(StringView{model_str.c_str(), model_str.size()});
   ASSERT_TRUE(IsA<Object>(model));
-  model = model["model"];
 
   {
+    model = model["model"];
     auto weights = get<Array>(model["weights"]);
     ASSERT_EQ(weights.size(), 17);
   }
-
-  {
-    model = Json::Load({model_str.c_str(), model_str.size()});
-    model = model["model"];
-    auto weights = get<Array>(model["weights"]);
-    ASSERT_EQ(weights.size(), 17);  // 16 + 1 (bias)
-  }
-
 }
 
 }  // namespace gbm

tests/cpp/gbm/test_gbtree.cc

@@ -64,7 +64,7 @@ TEST(GBTree, ChoosePredictor) {
   }
   ASSERT_TRUE(data.HostCanWrite());
   dmlc::TemporaryDirectory tempdir;
-  const std::string fname = tempdir.path + "/model_para.bst";
+  const std::string fname = tempdir.path + "/model_param.bst";
 
   {
     std::unique_ptr<dmlc::Stream> fo(dmlc::Stream::Create(fname.c_str(), "w"));
@@ -117,17 +117,15 @@ TEST(GBTree, Json_IO) {
     CreateTrainedGBM("gbtree", Args{}, kRows, kCols, &mparam, &gparam) };
 
   Json model {Object()};
-  model["model"] = Object();
-  auto& j_model = model["model"];
 
-  gbm->SaveModel(&j_model);
+  gbm->SaveModel(&model);
 
-  std::stringstream ss;
+  std::string model_str;
-  Json::Dump(model, &ss);
+  Json::Dump(model, &model_str);
 
-  auto model_str = ss.str();
+  auto loaded_model = Json::Load(StringView{model_str.c_str(), model_str.size()});
-  model = Json::Load({model_str.c_str(), model_str.size()});
+  ASSERT_EQ(get<String>(loaded_model["name"]), "gbtree");
-  ASSERT_EQ(get<String>(model["model"]["name"]), "gbtree");
+  ASSERT_TRUE(IsA<Object>(loaded_model["model"]["gbtree_model_param"]));
 }
 
 TEST(Dart, Json_IO) {

tests/cpp/test_learner.cc

@@ -143,7 +143,7 @@ TEST(Learner, Json_ModelIO) {
     for (int32_t iter = 0; iter < kIters; ++iter) {
       learner->UpdateOneIter(iter, p_dmat.get());
     }
-    learner->SetAttr("bset_score", "15.2");
+    learner->SetAttr("best_score", "15.2");
 
     Json out { Object() };
     learner->SaveModel(&out);
@@ -153,8 +153,8 @@ TEST(Learner, Json_ModelIO) {
     learner->Configure();
     learner->SaveModel(&new_in);
 
-    ASSERT_TRUE(IsA<Object>(out["Learner"]["attributes"]));
+    ASSERT_TRUE(IsA<Object>(out["learner"]["attributes"]));
-    ASSERT_EQ(get<Object>(out["Learner"]["attributes"]).size(), 1);
+    ASSERT_EQ(get<Object>(out["learner"]["attributes"]).size(), 1);
     ASSERT_EQ(out, new_in);
   }
 

tests/cpp/tree/test_gpu_hist.cu

@@ -13,7 +13,6 @@
 
 #include "xgboost/json.h"
 #include "../../../src/data/sparse_page_source.h"
-#include "../../../src/gbm/gbtree_model.h"
 #include "../../../src/tree/updater_gpu_hist.cu"
 #include "../../../src/tree/updater_gpu_common.cuh"
 #include "../../../src/common/common.h"

tests/python/test_basic_models.py

@@ -213,12 +213,12 @@ class TestModels(unittest.TestCase):
 
         with open('./model.json', 'r') as fd:
             j_model = json.load(fd)
-        assert isinstance(j_model['Learner'], dict)
+        assert isinstance(j_model['learner'], dict)
 
         bst = xgb.Booster(model_file='./model.json')
 
         with open('./model.json', 'r') as fd:
             j_model = json.load(fd)
-        assert isinstance(j_model['Learner'], dict)
+        assert isinstance(j_model['learner'], dict)
 
         os.remove('model.json')