Use `UpdateAllowUnknown' for non-model related parameter.

include/xgboost/base.h

@@ -225,7 +225,7 @@ using GradientPairInteger = detail::GradientPairInternal<int64_t>;
 using Args = std::vector<std::pair<std::string, std::string> >;
 
 /*! \brief small eps gap for minimum split decision. */
-const bst_float kRtEps = 1e-6f;
+constexpr bst_float kRtEps = 1e-6f;
 
 /*! \brief define unsigned long for openmp loop */
 using omp_ulong = dmlc::omp_ulong;  // NOLINT

include/xgboost/generic_parameters.h

@@ -5,14 +5,13 @@
 #ifndef XGBOOST_GENERIC_PARAMETERS_H_
 #define XGBOOST_GENERIC_PARAMETERS_H_
 
-#include <dmlc/parameter.h>
 #include <xgboost/logging.h>
 #include <xgboost/parameter.h>
 
 #include <string>
 
 namespace xgboost {
-struct GenericParameter : public dmlc::Parameter<GenericParameter> {
+struct GenericParameter : public XGBoostParameter<GenericParameter> {
   // stored random seed
   int seed;
   // whether seed the PRNG each iteration

include/xgboost/json.h

@@ -5,6 +5,7 @@
 #define XGBOOST_JSON_H_
 
 #include <xgboost/logging.h>
+#include <xgboost/parameter.h>
 #include <string>
 
 #include <map>
@@ -533,7 +534,7 @@ using Null    = JsonNull;
 // Utils tailored for XGBoost.
 
 template <typename Type>
-Object toJson(dmlc::Parameter<Type> const& param) {
+Object toJson(XGBoostParameter<Type> const& param) {
   Object obj;
   for (auto const& kv : param.__DICT__()) {
     obj[kv.first] = kv.second;
@@ -542,13 +543,13 @@ Object toJson(dmlc::Parameter<Type> const& param) {
 }
 
 template <typename Type>
-void fromJson(Json const& obj, dmlc::Parameter<Type>* param) {
+void fromJson(Json const& obj, XGBoostParameter<Type>* param) {
   auto const& j_param = get<Object const>(obj);
   std::map<std::string, std::string> m;
   for (auto const& kv : j_param) {
     m[kv.first] = get<String const>(kv.second);
   }
-  param->InitAllowUnknown(m);
+  param->UpdateAllowUnknown(m);
 }
 }  // namespace xgboost
 #endif  // XGBOOST_JSON_H_

include/xgboost/logging.h

@@ -9,9 +9,10 @@
 #define XGBOOST_LOGGING_H_
 
 #include <dmlc/logging.h>
-#include <dmlc/parameter.h>
 #include <dmlc/thread_local.h>
+
 #include <xgboost/base.h>
+#include <xgboost/parameter.h>
 
 #include <sstream>
 #include <map>
@@ -35,7 +36,7 @@ class BaseLogger {
 };
 
 // Parsing both silent and debug_verbose is to provide backward compatibility.
-struct ConsoleLoggerParam : public dmlc::Parameter<ConsoleLoggerParam> {
+struct ConsoleLoggerParam : public XGBoostParameter<ConsoleLoggerParam> {
   bool silent;  // deprecated.
   int verbosity;
 

include/xgboost/tree_model.h

@@ -60,6 +60,7 @@ struct TreeParam : public dmlc::Parameter<TreeParam> {
     // other arguments are set by the algorithm.
     DMLC_DECLARE_FIELD(num_roots).set_lower_bound(1).set_default(1)
         .describe("Number of start root of trees.");
+    DMLC_DECLARE_FIELD(num_nodes).set_lower_bound(1).set_default(1);
     DMLC_DECLARE_FIELD(num_feature)
         .describe("Number of features used in tree construction.");
     DMLC_DECLARE_FIELD(size_leaf_vector).set_lower_bound(0).set_default(0)
@@ -83,7 +84,7 @@ struct RTreeNodeStat {
   /*! \brief weight of current node */
   bst_float base_weight;
   /*! \brief number of child that is leaf node known up to now */
-  int leaf_child_cnt;
+  int leaf_child_cnt {0};
   bool operator==(const RTreeNodeStat& b) const {
     return loss_chg == b.loss_chg && sum_hess == b.sum_hess &&
            base_weight == b.base_weight && leaf_child_cnt == b.leaf_child_cnt;
@@ -98,6 +99,7 @@ class RegTree : public Model {
  public:
   /*! \brief auxiliary statistics of node to help tree building */
   using SplitCondT = bst_float;
+  static constexpr int32_t kInvalidNodeId {-1};
   /*! \brief tree node */
   class Node {
    public:
@@ -106,6 +108,12 @@ class RegTree : public Model {
       static_assert(sizeof(Node) == 4 * sizeof(int) + sizeof(Info),
                     "Node: 64 bit align");
     }
+    Node(int32_t cleft, int32_t cright, int32_t parent,
+         uint32_t split_ind, float split_cond, bool default_left) :
+        parent_{parent}, cleft_{cleft}, cright_{cright} {
+      this->SetSplit(split_ind, split_cond, default_left);
+    }
+
     /*! \brief index of left child */
     XGBOOST_DEVICE int LeftChild() const {
       return this->cleft_;
@@ -219,11 +227,11 @@ class RegTree : public Model {
     };
     // pointer to parent, highest bit is used to
     // indicate whether it's a left child or not
-    int parent_;
+    int32_t parent_{kInvalidNodeId};
     // pointer to left, right
-    int cleft_, cright_;
+    int32_t cleft_{kInvalidNodeId}, cright_{kInvalidNodeId};
     // split feature index, left split or right split depends on the highest bit
-    unsigned sindex_{0};
+    uint32_t sindex_{0};
     // extra info
     Info info_;
   };

plugin/example/custom_obj.cc

@@ -5,7 +5,7 @@
  *  This plugin defines the additional metric function.
  */
 #include <xgboost/base.h>
-#include <dmlc/parameter.h>
+#include <xgboost/parameter.h>
 #include <xgboost/objective.h>
 #include <xgboost/json.h>
 
@@ -16,7 +16,7 @@ namespace obj {
 // You do not have to use it.
 // see http://dmlc-core.readthedocs.org/en/latest/parameter.html
 // for introduction of this module.
-struct MyLogisticParam : public dmlc::Parameter<MyLogisticParam> {
+struct MyLogisticParam : public XGBoostParameter<MyLogisticParam> {
   float scale_neg_weight;
   // declare parameters
   DMLC_DECLARE_PARAMETER(MyLogisticParam) {
@@ -32,7 +32,7 @@ DMLC_REGISTER_PARAMETER(MyLogisticParam);
 class MyLogistic : public ObjFunction {
  public:
   void Configure(const std::vector<std::pair<std::string, std::string> >& args) override {
-    param_.InitAllowUnknown(args);
+    param_.UpdateAllowUnknown(args);
   }
   void GetGradient(const HostDeviceVector<bst_float> &preds,
                    const MetaInfo &info,

plugin/lz4/sparse_page_lz4_format.cc

@@ -3,10 +3,11 @@
  * \file sparse_page_lz4_format.cc
  *  XGBoost Plugin to enable LZ4 compressed format on the external memory pages.
  */
+#include <dmlc/registry.h>
+
 #include <xgboost/data.h>
 #include <xgboost/logging.h>
-#include <dmlc/registry.h>
-#include <dmlc/parameter.h>
+#include <xgboost/parameter.h>
 #include <lz4.h>
 #include <lz4hc.h>
 #include "../../src/data/sparse_page_writer.h"

python-package/xgboost/compat.py

@@ -1,6 +1,6 @@
 # coding: utf-8
 # pylint: disable= invalid-name,  unused-import
-"""For compatibility"""
+"""For compatibility and optional dependencies."""
 
 from __future__ import absolute_import
 
@@ -16,22 +16,22 @@
     # pylint: disable=invalid-name, redefined-builtin
     STRING_TYPES = (str,)
 
-
     def py_str(x):
         """convert c string back to python string"""
         return x.decode('utf-8')
 else:
     STRING_TYPES = (basestring,)  # pylint: disable=undefined-variable
 
-
     def py_str(x):
         """convert c string back to python string"""
         return x
 
-########################################################################################
+
+###############################################################################
 # START NUMPY PATHLIB ATTRIBUTION
-########################################################################################
-# os.PathLike compatibility used in  Numpy: https://github.com/numpy/numpy/tree/v1.17.0
+###############################################################################
+# os.PathLike compatibility used in  Numpy:
+# https://github.com/numpy/numpy/tree/v1.17.0
 # Attribution:
 # https://github.com/numpy/numpy/blob/v1.17.0/numpy/compat/py3k.py#L188-L247
 # Backport os.fs_path, os.PathLike, and PurePath.__fspath__
@@ -56,7 +56,6 @@ def __subclasshook__(cls, subclass):
                 return True
             return hasattr(subclass, '__fspath__')
 
-
     def os_fspath(path):
         """Return the path representation of a path-like object.
         If str or bytes is passed in, it is returned unchanged. Otherwise the
@@ -84,9 +83,9 @@ def os_fspath(path):
         raise TypeError("expected {}.__fspath__() to return str or bytes, "
                         "not {}".format(path_type.__name__,
                                         type(path_repr).__name__))
-########################################################################################
+###############################################################################
 # END NUMPY PATHLIB ATTRIBUTION
-########################################################################################
+###############################################################################
 
 # pickle
 try:

src/cli_main.cc

@@ -12,6 +12,8 @@
 #include <xgboost/learner.h>
 #include <xgboost/data.h>
 #include <xgboost/logging.h>
+#include <xgboost/parameter.h>
+
 #include <dmlc/timer.h>
 #include <iomanip>
 #include <ctime>
@@ -30,7 +32,7 @@ enum CLITask {
   kPredict = 2
 };
 
-struct CLIParam : public dmlc::Parameter<CLIParam> {
+struct CLIParam : public XGBoostParameter<CLIParam> {
   /*! \brief the task name */
   int task;
   /*! \brief whether evaluate training statistics */
@@ -123,7 +125,7 @@ struct CLIParam : public dmlc::Parameter<CLIParam> {
   // customized configure function of CLIParam
   inline void Configure(const std::vector<std::pair<std::string, std::string> >& _cfg) {
     this->cfg = _cfg;
-    this->InitAllowUnknown(_cfg);
+    this->UpdateAllowUnknown(_cfg);
     for (const auto& kv : _cfg) {
       if (!strncmp("eval[", kv.first.c_str(), 5)) {
         char evname[256];

src/gbm/gblinear.cc

@@ -25,7 +25,7 @@ namespace gbm {
 DMLC_REGISTRY_FILE_TAG(gblinear);
 
 // training parameters
-struct GBLinearTrainParam : public dmlc::Parameter<GBLinearTrainParam> {
+struct GBLinearTrainParam : public XGBoostParameter<GBLinearTrainParam> {
   std::string updater;
   float tolerance;
   size_t max_row_perbatch;
@@ -64,7 +64,7 @@ class GBLinear : public GradientBooster {
     if (model_.weight.size() == 0) {
       model_.param.InitAllowUnknown(cfg);
     }
-    param_.InitAllowUnknown(cfg);
+    param_.UpdateAllowUnknown(cfg);
     updater_.reset(LinearUpdater::Create(param_.updater, learner_param_));
     updater_->Configure(cfg);
     monitor_.Init("GBLinear");

src/gbm/gbtree.cc

@@ -34,7 +34,7 @@ DMLC_REGISTRY_FILE_TAG(gbtree);
 
 void GBTree::Configure(const Args& cfg) {
   this->cfg_ = cfg;
-  tparam_.InitAllowUnknown(cfg);
+  tparam_.UpdateAllowUnknown(cfg);
 
   model_.Configure(cfg);
 
@@ -295,7 +295,7 @@ class Dart : public GBTree {
   void Configure(const Args& cfg) override {
     GBTree::Configure(cfg);
     if (model_.trees.size() == 0) {
-      dparam_.InitAllowUnknown(cfg);
+      dparam_.UpdateAllowUnknown(cfg);
     }
   }
 

src/gbm/gbtree.h

@@ -48,7 +48,7 @@ namespace xgboost {
 namespace gbm {
 
 /*! \brief training parameters */
-struct GBTreeTrainParam : public dmlc::Parameter<GBTreeTrainParam> {
+struct GBTreeTrainParam : public XGBoostParameter<GBTreeTrainParam> {
   /*!
    * \brief number of parallel trees constructed each iteration
    *  use this option to support boosted random forest
@@ -95,7 +95,7 @@ struct GBTreeTrainParam : public dmlc::Parameter<GBTreeTrainParam> {
 };
 
 /*! \brief training parameters */
-struct DartTrainParam : public dmlc::Parameter<DartTrainParam> {
+struct DartTrainParam : public XGBoostParameter<DartTrainParam> {
   /*! \brief type of sampling algorithm */
   int sample_type;
   /*! \brief type of normalization algorithm */

src/learner.cc

@@ -5,13 +5,8 @@
  * \author Tianqi Chen
  */
 #include <dmlc/io.h>
-#include <dmlc/timer.h>
-#include <dmlc/any.h>
-#include <xgboost/feature_map.h>
-#include <xgboost/learner.h>
-#include <xgboost/base.h>
-#include <xgboost/logging.h>
-#include <xgboost/generic_parameters.h>
+#include <dmlc/parameter.h>
+
 #include <algorithm>
 #include <iomanip>
 #include <limits>
@@ -21,6 +16,12 @@
 #include <utility>
 #include <vector>
 
+#include "xgboost/feature_map.h"
+#include "xgboost/learner.h"
+#include "xgboost/base.h"
+#include "xgboost/parameter.h"
+#include "xgboost/logging.h"
+#include "xgboost/generic_parameters.h"
 #include "xgboost/host_device_vector.h"
 #include "common/common.h"
 #include "common/io.h"
@@ -103,7 +104,7 @@ struct LearnerModelParam : public dmlc::Parameter<LearnerModelParam> {
   }
 };
 
-struct LearnerTrainParam : public dmlc::Parameter<LearnerTrainParam> {
+struct LearnerTrainParam : public XGBoostParameter<LearnerTrainParam> {
   // data split mode, can be row, col, or none.
   DataSplitMode dsplit;
   // flag to disable default metric
@@ -155,9 +156,9 @@ class LearnerImpl : public Learner {
     auto old_tparam = tparam_;
     Args args = {cfg_.cbegin(), cfg_.cend()};
 
-    tparam_.InitAllowUnknown(args);
+    tparam_.UpdateAllowUnknown(args);
 
-    generic_param_.InitAllowUnknown(args);
+    generic_param_.UpdateAllowUnknown(args);
     generic_param_.CheckDeprecated();
 
     ConsoleLogger::Configure(args);
@@ -208,7 +209,7 @@ class LearnerImpl : public Learner {
   }
 
   void Load(dmlc::Stream* fi) override {
-    generic_param_.InitAllowUnknown(Args{});
+    generic_param_.UpdateAllowUnknown(Args{});
     tparam_.Init(std::vector<std::pair<std::string, std::string>>{});
     // TODO(tqchen) mark deprecation of old format.
     common::PeekableInStream fp(fi);
@@ -314,7 +315,7 @@ class LearnerImpl : public Learner {
     cfg_.insert(n.cbegin(), n.cend());
 
     Args args = {cfg_.cbegin(), cfg_.cend()};
-    generic_param_.InitAllowUnknown(args);
+    generic_param_.UpdateAllowUnknown(args);
     gbm_->Configure(args);
     obj_->Configure({cfg_.begin(), cfg_.end()});
 

src/linear/coordinate_common.h

@@ -10,14 +10,15 @@
 #include <limits>
 
 #include "xgboost/data.h"
+#include "xgboost/parameter.h"
 #include "./param.h"
 #include "../gbm/gblinear_model.h"
 #include "../common/random.h"
 
 namespace xgboost {
 namespace linear {
 
-struct CoordinateParam : public dmlc::Parameter<CoordinateParam> {
+struct CoordinateParam : public XGBoostParameter<CoordinateParam> {
   int top_k;
   DMLC_DECLARE_PARAMETER(CoordinateParam) {
     DMLC_DECLARE_FIELD(top_k)