Refactor configuration [Part II]. (#4577)

* Refactor configuration [Part II].

* General changes:
** Remove `Init` methods to avoid ambiguity.
** Remove `Configure(std::map<>)` to avoid redundant copying and prepare for
   parameter validation. (`std::vector` is returned from `InitAllowUnknown`).
** Add name to tree updaters for easier debugging.

* Learner changes:
** Make `LearnerImpl` the only source of configuration.

    All configurations are stored and carried out by `LearnerImpl::Configure()`.

** Remove booster in C API.

    Originally kept for "compatibility reason", but did not state why.  So here
    we just remove it.

** Add a `metric_names_` field in `LearnerImpl`.
** Remove `LazyInit`.  Configuration will always be lazy.
** Run `Configure` before every iteration.

* Predictor changes:
** Allocate both cpu and gpu predictor.
** Remove cpu_predictor from gpu_predictor.

    `GBTree` is now used to dispatch the predictor.

** Remove some GPU Predictor tests.

* IO

No IO changes.  The binary model format stability is tested by comparing
hashing value of save models between two commits

tests/cpp/tree/test_gpu_hist.cu

@@ -384,10 +384,11 @@ void TestHistogramIndexImpl(int n_gpus) {
     {"max_leaves", "0"}
   };
 
-  LearnerTrainParam learner_param(CreateEmptyGenericParam(0, n_gpus));
-  hist_maker.Init(training_params, &learner_param);
+  GenericParameter generic_param(CreateEmptyGenericParam(0, n_gpus));
+  hist_maker.Configure(training_params, &generic_param);
+
   hist_maker.InitDataOnce(hist_maker_dmat.get());
-  hist_maker_ext.Init(training_params, &learner_param);
+  hist_maker_ext.Configure(training_params, &generic_param);
   hist_maker_ext.InitDataOnce(hist_maker_ext_dmat.get());
 
   ASSERT_EQ(hist_maker.shards_.size(), hist_maker_ext.shards_.size());