diff --git a/include/caffe/layers/softmax_loss_ohem_layer.hpp b/include/caffe/layers/softmax_loss_ohem_layer.hpp
index 5ad9ee9c..305c05c4 100644
--- a/include/caffe/layers/softmax_loss_ohem_layer.hpp
+++ b/include/caffe/layers/softmax_loss_ohem_layer.hpp
@@ -60,7 +60,7 @@ class SoftmaxWithLossOHEMLayer : public LossLayer<Dtype> {
   virtual void Reshape(const vector<Blob<Dtype>*>& bottom,
       const vector<Blob<Dtype>*>& top);
 
-  virtual inline const char* type() const { return "SoftmaxWithLoss"; }
+  virtual inline const char* type() const { return "SoftmaxWithLossOHEM"; }
   virtual inline int ExactNumTopBlobs() const { return -1; }
   virtual inline int MinTopBlobs() const { return 1; }
   virtual inline int MaxTopBlobs() const { return 3; }
diff --git a/src/caffe/layers/batch_norm_layer.cpp b/src/caffe/layers/batch_norm_layer.cpp
index bc19c53b..a69d8f99 100644
--- a/src/caffe/layers/batch_norm_layer.cpp
+++ b/src/caffe/layers/batch_norm_layer.cpp
@@ -48,9 +48,7 @@ void BatchNormLayer<Dtype>::Reshape(const vector<Blob<Dtype>*>& bottom,
   mean_.Reshape(sz);
   variance_.Reshape(sz);
   temp_.ReshapeLike(*bottom[0]);
-  if (use_global_stats_) {
-    x_norm_.ReshapeLike(*bottom[0]);
-  }
+  x_norm_.ReshapeLike(*bottom[0]);
   sz[0]=bottom[0]->shape(0);
   batch_sum_multiplier_.Reshape(sz);
 
diff --git a/src/caffe/layers/smooth_L1_loss_ohem_layer.cu b/src/caffe/layers/smooth_L1_loss_ohem_layer.cu
index 669a4f8e..515c340b 100644
--- a/src/caffe/layers/smooth_L1_loss_ohem_layer.cu
+++ b/src/caffe/layers/smooth_L1_loss_ohem_layer.cu
@@ -75,7 +75,7 @@ namespace caffe {
 
     // Output per-instance loss
     if (top.size() >= 2) {
-      kernel_channel_sum<Dtype> << <CAFFE_GET_BLOCKS(top[0]->count()),
+      kernel_channel_sum<Dtype> << <CAFFE_GET_BLOCKS(top[1]->count()),
         CAFFE_CUDA_NUM_THREADS >> > (outer_num_, bottom[0]->channels(),
         inner_num_, errors_.gpu_data(), top[1]->mutable_gpu_data());
     }