checkin continue training

src/learner/learner-inl.hpp

@@ -33,6 +33,7 @@ class BoostLearner {
     prob_buffer_row = 1.0f;
     part_load_col = 0;
     distributed_mode = 0;
+    pred_buffer_size = 0;
   }
   ~BoostLearner(void) {
     if (obj_ != NULL) delete obj_;
@@ -76,6 +77,7 @@ class BoostLearner {
     if (!silent) {
       utils::Printf("buffer_size=%ld\n", static_cast<long>(buffer_size));
     }
+    this->pred_buffer_size = buffer_size;
   }
   /*!
    * \brief set parameters from outside
@@ -139,8 +141,9 @@ class BoostLearner {
   /*!
    * \brief load model from stream
    * \param fi input stream
+   * \param keep_predbuffer whether to keep predict buffer
    */
-  inline void LoadModel(utils::IStream &fi) {
+  inline void LoadModel(utils::IStream &fi, bool keep_predbuffer = true) {
     utils::Check(fi.Read(&mparam, sizeof(ModelParam)) != 0,
                  "BoostLearner: wrong model format");
     utils::Check(fi.Read(&name_obj_), "BoostLearner: wrong model format");
@@ -150,6 +153,9 @@ class BoostLearner {
     if (gbm_ != NULL) delete gbm_;
     this->InitObjGBM();
     gbm_->LoadModel(fi);
+    if (keep_predbuffer && distributed_mode == 2 && sync::GetRank() != 0) {
+      gbm_->ResetPredBuffer(pred_buffer_size);
+    }
   }
   /*!
    * \brief load model from file
@@ -370,12 +376,14 @@ class BoostLearner {
   int distributed_mode;
   // randomly load part of data
   int part_load_col;
+  // cached size of predict buffer
+  size_t pred_buffer_size;
   // maximum buffred row value
   float prob_buffer_row;
   // evaluation set
   EvalSet evaluator_;
   // model parameter
-  ModelParam   mparam;
+  ModelParam  mparam;
   // gbm model that back everything
   gbm::IGradBooster *gbm_;
   // name of gbm model used for training