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Unify logging facilities. (#3982)

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* Unify logging facilities.

* Enhance `ConsoleLogger` to handle different verbosity.
* Override macros from `dmlc`.
* Don't use specialized gamma when building with GPU.
* Remove verbosity cache in monitor.
* Test monitor.
* Deprecate `silent`.
* Fix doc and messages.
* Fix python test.
* Fix silent tests.
This commit is contained in:
Jiaming Yuan
2018-12-14 19:29:58 +08:00
committed by GitHub
parent fd722d60cd
commit e0a279114e
28 changed files with 368 additions and 171 deletions
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7
src/gbm/gblinear.cc
View File

@@ -26,7 +26,6 @@ struct GBLinearTrainParam : public dmlc::Parameter<GBLinearTrainParam> {
std::string updater;
float tolerance;
size_t max_row_perbatch;
int debug_verbose;
DMLC_DECLARE_PARAMETER(GBLinearTrainParam) {
DMLC_DECLARE_FIELD(updater)
.set_default("shotgun")
@@ -38,10 +37,6 @@ struct GBLinearTrainParam : public dmlc::Parameter<GBLinearTrainParam> {
DMLC_DECLARE_FIELD(max_row_perbatch)
.set_default(std::numeric_limits<size_t>::max())
.describe("Maximum rows per batch.");
DMLC_DECLARE_FIELD(debug_verbose)
.set_lower_bound(0)
.set_default(0)
.describe("flag to print out detailed breakdown of runtime");
}
};
/*!
@@ -69,7 +64,7 @@ class GBLinear : public GradientBooster {
param_.InitAllowUnknown(cfg);
updater_.reset(LinearUpdater::Create(param_.updater));
updater_->Init(cfg);
monitor_.Init("GBLinear ", param_.debug_verbose);
monitor_.Init("GBLinear");
}
void Load(dmlc::Stream* fi) override {
model_.Load(fi);

19
src/gbm/gbtree.cc
View File

@@ -45,8 +45,6 @@ struct GBTreeTrainParam : public dmlc::Parameter<GBTreeTrainParam> {
std::string updater_seq;
/*! \brief type of boosting process to run */
int process_type;
// flag to print out detailed breakdown of runtime
int debug_verbose;
std::string predictor;
// declare parameters
DMLC_DECLARE_PARAMETER(GBTreeTrainParam) {
@@ -64,10 +62,6 @@ struct GBTreeTrainParam : public dmlc::Parameter<GBTreeTrainParam> {
.add_enum("update", kUpdate)
.describe("Whether to run the normal boosting process that creates new trees,"\
" or to update the trees in an existing model.");
DMLC_DECLARE_FIELD(debug_verbose)
.set_lower_bound(0)
.set_default(0)
.describe("flag to print out detailed breakdown of runtime");
// add alias
DMLC_DECLARE_ALIAS(updater_seq, updater);
DMLC_DECLARE_FIELD(predictor)
@@ -78,8 +72,6 @@ struct GBTreeTrainParam : public dmlc::Parameter<GBTreeTrainParam> {
/*! \brief training parameters */
struct DartTrainParam : public dmlc::Parameter<DartTrainParam> {
/*! \brief whether to not print info during training */
bool silent;
/*! \brief type of sampling algorithm */
int sample_type;
/*! \brief type of normalization algorithm */
@@ -94,9 +86,6 @@ struct DartTrainParam : public dmlc::Parameter<DartTrainParam> {
float learning_rate;
// declare parameters
DMLC_DECLARE_PARAMETER(DartTrainParam) {
DMLC_DECLARE_FIELD(silent)
.set_default(false)
.describe("Not print information during training.");
DMLC_DECLARE_FIELD(sample_type)
.set_default(0)
.add_enum("uniform", 0)
@@ -160,7 +149,7 @@ class GBTree : public GradientBooster {
// configure predictor
predictor_ = std::unique_ptr<Predictor>(Predictor::Create(tparam_.predictor));
predictor_->Init(cfg, cache_);
monitor_.Init("GBTree", tparam_.debug_verbose);
monitor_.Init("GBTree");
}
void Load(dmlc::Stream* fi) override {
@@ -488,10 +477,8 @@ class Dart : public GBTree {
model_.CommitModel(std::move(new_trees[gid]), gid);
}
size_t num_drop = NormalizeTrees(num_new_trees);
if (dparam_.silent != 1) {
LOG(INFO) << "drop " << num_drop << " trees, "
<< "weight = " << weight_drop_.back();
}
LOG(INFO) << "drop " << num_drop << " trees, "
<< "weight = " << weight_drop_.back();
}
// predict the leaf scores without dropped trees