De-duplicate GPU parameters. (#4454)

* Only define `gpu_id` and `n_gpus` in `LearnerTrainParam`
* Pass LearnerTrainParam through XGBoost vid factory method.
* Disable all GPU usage when GPU related parameters are not specified (fixes XGBoost choosing GPU over aggressively).
* Test learner train param io.
* Fix gpu pickling.

src/metric/elementwise_metric.cu

@@ -314,11 +314,6 @@ struct EvalEWiseBase : public Metric {
   explicit EvalEWiseBase(char const* policy_param) :
     policy_{policy_param}, reducer_{policy_} {}
 
-  void Configure(
-      const std::vector<std::pair<std::string, std::string> >& args) override {
-    param_.InitAllowUnknown(args);
-  }
-
   bst_float Eval(const HostDeviceVector<bst_float>& preds,
                  const MetaInfo& info,
                  bool distributed) override {
@@ -328,7 +323,7 @@ struct EvalEWiseBase : public Metric {
         << "hint: use merror or mlogloss for multi-class classification";
     const auto ndata = static_cast<omp_ulong>(info.labels_.Size());
     // Dealing with ndata < n_gpus.
-    GPUSet devices = GPUSet::All(param_.gpu_id, param_.n_gpus, ndata);
+    GPUSet devices = GPUSet::All(tparam_->gpu_id, tparam_->n_gpus, ndata);
 
     auto result =
         reducer_.Reduce(devices, info.weights_, info.labels_, preds);
@@ -347,8 +342,6 @@ struct EvalEWiseBase : public Metric {
  private:
   Policy policy_;
 
-  MetricParam param_;
-
   ElementWiseMetricsReduction<Policy> reducer_;
 };
 

src/metric/metric.cc

@@ -1,19 +1,18 @@
 /*!
- * Copyright 2015 by Contributors
+ * Copyright 2015-2019 by Contributors
  * \file metric_registry.cc
  * \brief Registry of objective functions.
  */
-#include <xgboost/metric.h>
 #include <dmlc/registry.h>
-
-#include "metric_common.h"
+#include <xgboost/metric.h>
+#include <xgboost/generic_parameters.h>
 
 namespace dmlc {
 DMLC_REGISTRY_ENABLE(::xgboost::MetricReg);
 }
 
 namespace xgboost {
-Metric* Metric::Create(const std::string& name) {
+Metric* Metric::Create(const std::string& name, LearnerTrainParam const* tparam) {
   std::string buf = name;
   std::string prefix = name;
   auto pos = buf.find('@');
@@ -22,21 +21,24 @@ Metric* Metric::Create(const std::string& name) {
     if (e == nullptr) {
       LOG(FATAL) << "Unknown metric function " << name;
     }
-    return (e->body)(nullptr);
+    auto p_metric = (e->body)(nullptr);
+    p_metric->tparam_ = tparam;
+    return p_metric;
   } else {
     std::string prefix = buf.substr(0, pos);
     auto *e = ::dmlc::Registry< ::xgboost::MetricReg>::Get()->Find(prefix.c_str());
     if (e == nullptr) {
       LOG(FATAL) << "Unknown metric function " << name;
     }
-    return (e->body)(buf.substr(pos + 1, buf.length()).c_str());
+    auto p_metric = (e->body)(buf.substr(pos + 1, buf.length()).c_str());
+    p_metric->tparam_ = tparam;
+    return p_metric;
   }
 }
 }  // namespace xgboost
 
 namespace xgboost {
 namespace metric {
-DMLC_REGISTER_PARAMETER(MetricParam);
 
 // List of files that will be force linked in static links.
 DMLC_REGISTRY_LINK_TAG(elementwise_metric);

src/metric/metric_common.h

@@ -11,20 +11,6 @@
 namespace xgboost {
 namespace metric {
 
-// Created exclusively for GPU.
-struct MetricParam : public dmlc::Parameter<MetricParam> {
-  int n_gpus;
-  int gpu_id;
-  DMLC_DECLARE_PARAMETER(MetricParam) {
-    DMLC_DECLARE_FIELD(n_gpus).set_default(1).set_lower_bound(GPUSet::kAll)
-        .describe("Number of GPUs to use for multi-gpu algorithms.");
-    DMLC_DECLARE_FIELD(gpu_id)
-        .set_lower_bound(0)
-        .set_default(0)
-        .describe("gpu to use for objective function evaluation");
-  };
-};
-
 class PackedReduceResult {
   double residue_sum_;
   double weights_sum_;

src/metric/multiclass_metric.cu

@@ -168,11 +168,6 @@ class MultiClassMetricsReduction {
  */
 template<typename Derived>
 struct EvalMClassBase : public Metric {
-  void Configure(
-      const std::vector<std::pair<std::string, std::string> >& args) override {
-    param_.InitAllowUnknown(args);
-  }
-
   bst_float Eval(const HostDeviceVector<bst_float> &preds,
                  const MetaInfo &info,
                  bool distributed) override {
@@ -185,7 +180,7 @@ struct EvalMClassBase : public Metric {
         << " use logloss for binary classification";
     const auto ndata = static_cast<bst_omp_uint>(info.labels_.Size());
 
-    GPUSet devices = GPUSet::All(param_.gpu_id, param_.n_gpus, ndata);
+    GPUSet devices = GPUSet::All(tparam_->gpu_id, tparam_->n_gpus, ndata);
     auto result = reducer_.Reduce(devices, nclass, info.weights_, info.labels_, preds);
     double dat[2] { result.Residue(), result.Weights() };
 
@@ -215,7 +210,6 @@ struct EvalMClassBase : public Metric {
 
  private:
   MultiClassMetricsReduction<Derived> reducer_;
-  MetricParam param_;
   // used to store error message
   const char *error_msg_;
 };