diff --git a/src/learner/objective-inl.hpp b/src/learner/objective-inl.hpp
index e45250950..41af8b605 100644
--- a/src/learner/objective-inl.hpp
+++ b/src/learner/objective-inl.hpp
@@ -105,19 +105,22 @@ class RegLossObj : public IObjFunction{
       scale_pos_weight = static_cast<float>(atof(val));
     }
   }
-  virtual void GetGradient(const std::vector<float>& preds,
+  virtual void GetGradient(const std::vector<float> &preds,
                            const MetaInfo &info,
                            int iter,
                            std::vector<bst_gpair> *out_gpair) {
-    utils::Check(preds.size() == info.labels.size(),
+    utils::Check(info.labels.size() != 0, "label set cannot be empty");
+    utils::Check(preds.size() % info.labels.size() == 0,
                  "labels are not correctly provided");
     std::vector<bst_gpair> &gpair = *out_gpair;
     gpair.resize(preds.size());
     // start calculating gradient
+    const unsigned nstep = static_cast<unsigned>(info.labels.size());
     const unsigned ndata = static_cast<unsigned>(preds.size());
     #pragma omp parallel for schedule(static)
-    for (unsigned j = 0; j < ndata; ++j) {
-      float p = loss.PredTransform(preds[j]);
+    for (unsigned i = 0; i < ndata; ++i) {
+      const unsigned j = i % nstep;
+      float p = loss.PredTransform(preds[i]);
       float w = info.GetWeight(j);
       if (info.labels[j] == 1.0f) w *= scale_pos_weight;
       gpair[j] = bst_gpair(loss.FirstOrderGradient(p, info.labels[j]) * w,
@@ -155,25 +158,28 @@ class SoftmaxMultiClassObj : public IObjFunction {
   virtual void SetParam(const char *name, const char *val) {
     if (!strcmp( "num_class", name )) nclass = atoi(val);
   }
-  virtual void GetGradient(const std::vector<float>& preds,
+  virtual void GetGradient(const std::vector<float> &preds,
                            const MetaInfo &info,
                            int iter,
                            std::vector<bst_gpair> *out_gpair) {
     utils::Check(nclass != 0, "must set num_class to use softmax");
-    utils::Check(preds.size() == static_cast<size_t>(nclass) * info.labels.size(),
+    utils::Check(info.labels.size() != 0, "label set cannot be empty");
+    utils::Check(preds.size() % (static_cast<size_t>(nclass) * info.labels.size()) == 0,
                  "SoftmaxMultiClassObj: label size and pred size does not match");
     std::vector<bst_gpair> &gpair = *out_gpair;
     gpair.resize(preds.size());
-    const unsigned ndata = static_cast<unsigned>(info.labels.size());
+    const unsigned nstep = static_cast<unsigned>(info.labels.size() * nclass);
+    const unsigned ndata = static_cast<unsigned>(preds.size() / nclass);
     #pragma omp parallel
     {
       std::vector<float> rec(nclass);
       #pragma omp for schedule(static)
-      for (unsigned j = 0; j < ndata; ++j) {
+      for (unsigned i = 0; i < ndata; ++i) {
         for (int k = 0; k < nclass; ++k) {
-          rec[k] = preds[j * nclass + k];
+          rec[k] = preds[i * nclass + k];
         }
         Softmax(&rec);
+        const unsigned j = i % nstep;
         int label = static_cast<int>(info.labels[j]);
         utils::Check(label < nclass, "SoftmaxMultiClassObj: label exceed num_class");
         const float wt = info.GetWeight(j);
@@ -181,9 +187,9 @@ class SoftmaxMultiClassObj : public IObjFunction {
           float p = rec[k];
           const float h = 2.0f * p * (1.0f - p) * wt;
           if (label == k) {
-            gpair[j * nclass + k] = bst_gpair((p - 1.0f) * wt, h);
+            gpair[i * nclass + k] = bst_gpair((p - 1.0f) * wt, h);
           } else {
-            gpair[j * nclass + k] = bst_gpair(p* wt, h);
+            gpair[i * nclass + k] = bst_gpair(p* wt, h);
           }
         }
       }
@@ -203,7 +209,9 @@ class SoftmaxMultiClassObj : public IObjFunction {
   inline void Transform(std::vector<float> *io_preds, int prob) {
     utils::Check(nclass != 0, "must set num_class to use softmax");
     std::vector<float> &preds = *io_preds;
+    std::vector<float> tmp;
     const unsigned ndata = static_cast<unsigned>(preds.size()/nclass);
+    if (prob == 0) tmp.resize(ndata);
     #pragma omp parallel
     {
       std::vector<float> rec(nclass);
@@ -213,7 +221,7 @@ class SoftmaxMultiClassObj : public IObjFunction {
           rec[k] = preds[j * nclass + k];
         }
         if (prob == 0) {
-          preds[j] = FindMaxIndex(rec);
+          tmp[j] = FindMaxIndex(rec);
         } else {
           Softmax(&rec);
           for (int k = 0; k < nclass; ++k) {
@@ -222,9 +230,7 @@ class SoftmaxMultiClassObj : public IObjFunction {
         }
       }
     }
-    if (prob == 0) {
-      preds.resize(ndata);
-    }
+    if (prob == 0) preds = tmp;
   }
   // data field
   int nclass;
@@ -245,17 +251,17 @@ class LambdaRankObj : public IObjFunction {
     if (!strcmp( "fix_list_weight", name)) fix_list_weight = static_cast<float>(atof(val));
     if (!strcmp( "num_pairsample", name)) num_pairsample = atoi(val);
   }
-  virtual void GetGradient(const std::vector<float>& preds,
+  virtual void GetGradient(const std::vector<float> &preds,
                            const MetaInfo &info,
                            int iter,
                            std::vector<bst_gpair> *out_gpair) {
-    utils::Assert(preds.size() == info.labels.size(), "label size predict size not match");
+    utils::Check(preds.size() == info.labels.size(), "label size predict size not match");
     std::vector<bst_gpair> &gpair = *out_gpair;
     gpair.resize(preds.size());
     // quick consistency when group is not available
-    std::vector<unsigned> tgptr(2, 0); tgptr[1] = preds.size();
+    std::vector<unsigned> tgptr(2, 0); tgptr[1] = info.labels.size();
     const std::vector<unsigned> &gptr = info.group_ptr.size() == 0 ? tgptr : info.group_ptr;
-    utils::Check(gptr.size() != 0 && gptr.back() == preds.size(),
+    utils::Check(gptr.size() != 0 && gptr.back() == info.labels.size(),
                  "group structure not consistent with #rows");
     const unsigned ngroup = static_cast<unsigned>(gptr.size() - 1);
     #pragma omp parallel
diff --git a/src/learner/objective.h b/src/learner/objective.h
index 513219093..d741ba61f 100644
--- a/src/learner/objective.h
+++ b/src/learner/objective.h
@@ -27,7 +27,7 @@ class IObjFunction{
    * \param iter current iteration number
    * \param out_gpair output of get gradient, saves gradient and second order gradient in
    */
-  virtual void GetGradient(const std::vector<float>& preds,
+  virtual void GetGradient(const std::vector<float> &preds,
                            const MetaInfo &info,
                            int iter,
                            std::vector<bst_gpair> *out_gpair) = 0;