Replaced std::vector with HostDeviceVector in MetaInfo and SparsePage. (#3446)

* Replaced std::vector with HostDeviceVector in MetaInfo and SparsePage.

- added distributions to HostDeviceVector
- using HostDeviceVector for labels, weights and base margings in MetaInfo
- using HostDeviceVector for offset and data in SparsePage
- other necessary refactoring

* Added const version of HostDeviceVector API calls.

- const versions added to calls that can trigger data transfers, e.g. DevicePointer()
- updated the code that uses HostDeviceVector
- objective functions now accept const HostDeviceVector<bst_float>& for predictions

* Updated src/linear/updater_gpu_coordinate.cu.

* Added read-only state for HostDeviceVector sync.

- this means no copies are performed if both host and devices access
  the HostDeviceVector read-only

* Fixed linter and test errors.

- updated the lz4 plugin
- added ConstDeviceSpan to HostDeviceVector
- using device % dh::NVisibleDevices() for the physical device number,
  e.g. in calls to cudaSetDevice()

* Fixed explicit template instantiation errors for HostDeviceVector.

- replaced HostDeviceVector<unsigned int> with HostDeviceVector<int>

* Fixed HostDeviceVector tests that require multiple GPUs.

- added a mock set device handler; when set, it is called instead of cudaSetDevice()

plugin/example/custom_obj.cc

@@ -33,21 +33,22 @@ class MyLogistic : public ObjFunction {
   void Configure(const std::vector<std::pair<std::string, std::string> >& args) override {
     param_.InitAllowUnknown(args);
   }
-  void GetGradient(HostDeviceVector<bst_float> *preds,
+  void GetGradient(const HostDeviceVector<bst_float> &preds,
                    const MetaInfo &info,
                    int iter,
                    HostDeviceVector<GradientPair> *out_gpair) override {
-    out_gpair->Resize(preds->Size());
-    std::vector<bst_float>& preds_h = preds->HostVector();
+    out_gpair->Resize(preds.Size());
+    const std::vector<bst_float>& preds_h = preds.HostVector();
     std::vector<GradientPair>& out_gpair_h = out_gpair->HostVector();
+    const std::vector<bst_float>& labels_h = info.labels_.HostVector();
     for (size_t i = 0; i < preds_h.size(); ++i) {
       bst_float w = info.GetWeight(i);
       // scale the negative examples!
-      if (info.labels_[i] == 0.0f) w *= param_.scale_neg_weight;
+      if (labels_h[i] == 0.0f) w *= param_.scale_neg_weight;
       // logistic transformation
       bst_float p = 1.0f / (1.0f + std::exp(-preds_h[i]));
       // this is the gradient
-      bst_float grad = (p - info.labels_[i]) * w;
+      bst_float grad = (p - labels_h[i]) * w;
       // this is the second order gradient
       bst_float hess = p * (1.0f - p) * w;
       out_gpair_h.at(i) = GradientPair(grad, hess);