[breaking] Change internal model serialization to UBJSON. (#7556)

* Use typed array for models.
* Change the memory snapshot format.
* Add new C API for saving to raw format.

tests/python/test_pickling.py

@@ -2,6 +2,7 @@ import pickle
 import numpy as np
 import xgboost as xgb
 import os
+import json
 
 
 kRows = 100
@@ -15,13 +16,14 @@ def generate_data():
 
 
 class TestPickling:
-    def run_model_pickling(self, xgb_params):
+    def run_model_pickling(self, xgb_params) -> str:
         X, y = generate_data()
         dtrain = xgb.DMatrix(X, y)
         bst = xgb.train(xgb_params, dtrain)
 
         dump_0 = bst.get_dump(dump_format='json')
         assert dump_0
+        config_0 = bst.save_config()
 
         filename = 'model.pkl'
 
@@ -42,9 +44,22 @@ class TestPickling:
         if os.path.exists(filename):
             os.remove(filename)
 
+        config_1 = bst.save_config()
+        assert config_0 == config_1
+        return json.loads(config_0)
+
     def test_model_pickling_json(self):
-        params = {
-            'nthread': 1,
-            'tree_method': 'hist',
-        }
-        self.run_model_pickling(params)
+        def check(config):
+            updater = config["learner"]["gradient_booster"]["updater"]
+            if params["tree_method"] == "exact":
+                subsample = updater["grow_colmaker"]["train_param"]["subsample"]
+            else:
+                subsample = updater["grow_quantile_histmaker"]["train_param"]["subsample"]
+            assert float(subsample) == 0.5
+
+        params = {"nthread": 8, "tree_method": "hist", "subsample": 0.5}
+        config = self.run_model_pickling(params)
+        check(config)
+        params = {"nthread": 8, "tree_method": "exact", "subsample": 0.5}
+        config = self.run_model_pickling(params)
+        check(config)