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

src/metric/elementwise_metric.cu

@@ -104,7 +104,7 @@ class ElementWiseMetricsReduction {
 #endif  // XGBOOST_USE_CUDA
 
   PackedReduceResult Reduce(
-      const LearnerTrainParam &tparam,
+      const GenericParameter &tparam,
       GPUSet devices,
       const HostDeviceVector<bst_float>& weights,
       const HostDeviceVector<bst_float>& labels,

src/metric/metric.cc

@@ -12,7 +12,7 @@ DMLC_REGISTRY_ENABLE(::xgboost::MetricReg);
 }
 
 namespace xgboost {
-Metric* Metric::Create(const std::string& name, LearnerTrainParam const* tparam) {
+Metric* Metric::Create(const std::string& name, GenericParameter const* tparam) {
   std::string buf = name;
   std::string prefix = name;
   const char* param;

src/metric/multiclass_metric.cu

@@ -126,7 +126,7 @@ class MultiClassMetricsReduction {
 #endif  // XGBOOST_USE_CUDA
 
   PackedReduceResult Reduce(
-      const LearnerTrainParam &tparam,
+      const GenericParameter &tparam,
       GPUSet devices,
       size_t n_class,
       const HostDeviceVector<bst_float>& weights,