JSON configuration IO. (#5111)

* Add saving/loading JSON configuration.
* Implement Python pickle interface with new IO routines.
* Basic tests for training continuation.

tests/python-gpu/load_pickle.py

@@ -1,20 +1,39 @@
-'''Loading a pickled model generated by test_pickling.py'''
-import pickle
+'''Loading a pickled model generated by test_pickling.py, only used by
+`test_gpu_with_dask.py`'''
 import unittest
 import os
 import xgboost as xgb
-import sys
+import json
 
-sys.path.append("tests/python")
-from test_pickling import build_dataset, model_path
+from test_gpu_pickling import build_dataset, model_path, load_pickle
 
 
 class TestLoadPickle(unittest.TestCase):
     def test_load_pkl(self):
-        assert os.environ['CUDA_VISIBLE_DEVICES'] == ''
-        with open(model_path, 'rb') as fd:
-            bst = pickle.load(fd)
+        '''Test whether prediction is correct.'''
+        assert os.environ['CUDA_VISIBLE_DEVICES'] == '-1'
+        bst = load_pickle(model_path)
         x, y = build_dataset()
         test_x = xgb.DMatrix(x)
         res = bst.predict(test_x)
         assert len(res) == 10
+
+    def test_predictor_type_is_auto(self):
+        '''Under invalid CUDA_VISIBLE_DEVICES, predictor should be set to
+        auto'''
+        assert os.environ['CUDA_VISIBLE_DEVICES'] == '-1'
+        bst = load_pickle(model_path)
+        config = bst.save_config()
+        config = json.loads(config)
+        assert config['learner']['gradient_booster']['gbtree_train_param'][
+            'predictor'] == 'auto'
+
+    def test_predictor_type_is_gpu(self):
+        '''When CUDA_VISIBLE_DEVICES is not specified, keep using
+        `gpu_predictor`'''
+        assert 'CUDA_VISIBLE_DEVICES' not in os.environ.keys()
+        bst = load_pickle(model_path)
+        config = bst.save_config()
+        config = json.loads(config)
+        assert config['learner']['gradient_booster']['gbtree_train_param'][
+            'predictor'] == 'gpu_predictor'