lint

diff --git a/src/caffe/layers/mvn_layer.cpp b/src/caffe/layers/mvn_layer.cpp
index c9c075c..e0360b6 100644 (file)
--- a/src/caffe/layers/mvn_layer.cpp
+++ b/src/caffe/layers/mvn_layer.cpp
@@ -44,9 +44,9 @@ Dtype MVNLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
 
   // computes variance using var(X) = E(X^2) - (EX)^2
   caffe_cpu_gemv<Dtype>(CblasNoTrans, num, dim, 1. / dim, bottom_data,
-      sum_multiplier_.cpu_data(), 0., mean_.mutable_cpu_data()); // EX
+      sum_multiplier_.cpu_data(), 0., mean_.mutable_cpu_data());  // EX
   caffe_cpu_gemv<Dtype>(CblasNoTrans, num, dim, 1. / dim, temp_.cpu_data(),
-      sum_multiplier_.cpu_data(), 0., variance_.mutable_cpu_data()); // E(X^2)
+      sum_multiplier_.cpu_data(), 0., variance_.mutable_cpu_data());  // E(X^2)
   caffe_powx(mean_.count(), mean_.cpu_data(), Dtype(2),
       temp_.mutable_cpu_data());  // (EX)^2
   caffe_sub(mean_.count(), variance_.cpu_data(), temp_.cpu_data(),
@@ -111,9 +111,9 @@ void MVNLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,
 
   // computes variance using var(X) = E(X^2) - (EX)^2
   caffe_cpu_gemv<Dtype>(CblasNoTrans, num, dim, 1. / dim, bottom_data,
-      sum_multiplier_.cpu_data(), 0., mean_.mutable_cpu_data()); // EX
+      sum_multiplier_.cpu_data(), 0., mean_.mutable_cpu_data());  // EX
   caffe_cpu_gemv<Dtype>(CblasNoTrans, num, dim, 1. / dim, temp_.cpu_data(),
-      sum_multiplier_.cpu_data(), 0., variance_.mutable_cpu_data()); // E(X^2)
+      sum_multiplier_.cpu_data(), 0., variance_.mutable_cpu_data());  // E(X^2)
   caffe_powx(mean_.count(), mean_.cpu_data(), Dtype(2),
       temp_.mutable_cpu_data());  // (EX)^2
   caffe_sub(mean_.count(), variance_.cpu_data(), temp_.cpu_data(),

diff --git a/src/caffe/layers/mvn_layer.cu b/src/caffe/layers/mvn_layer.cu
index be5f25b..fb2380c 100644 (file)
--- a/src/caffe/layers/mvn_layer.cu
+++ b/src/caffe/layers/mvn_layer.cu
@@ -23,9 +23,9 @@ Dtype MVNLayer<Dtype>::Forward_gpu(const vector<Blob<Dtype>*>& bottom,
 
   // computes variance using var(X) = E(X^2) - (EX)^2
   caffe_gpu_gemv<Dtype>(CblasNoTrans, num, dim, 1. / dim, bottom_data,
-      sum_multiplier_.gpu_data(), 0., mean_.mutable_gpu_data()); // EX
+      sum_multiplier_.gpu_data(), 0., mean_.mutable_gpu_data());  // EX
   caffe_gpu_gemv<Dtype>(CblasNoTrans, num, dim, 1. / dim, temp_.gpu_data(),
-      sum_multiplier_.gpu_data(), 0., variance_.mutable_gpu_data()); // E(X^2)
+      sum_multiplier_.gpu_data(), 0., variance_.mutable_gpu_data());  // E(X^2)
   caffe_gpu_powx(mean_.count(), mean_.gpu_data(), Dtype(2),
       temp_.mutable_gpu_data());  // (EX)^2
   caffe_gpu_sub(mean_.count(), variance_.gpu_data(), temp_.gpu_data(),
@@ -93,9 +93,9 @@ void MVNLayer<Dtype>::Backward_gpu(const vector<Blob<Dtype>*>& top,
 
   // computes variance using var(X) = E(X^2) - (EX)^2
   caffe_gpu_gemv<Dtype>(CblasNoTrans, num, dim, 1. / dim, bottom_data,
-      sum_multiplier_.gpu_data(), 0., mean_.mutable_gpu_data()); // EX
+      sum_multiplier_.gpu_data(), 0., mean_.mutable_gpu_data());  // EX
   caffe_gpu_gemv<Dtype>(CblasNoTrans, num, dim, 1. / dim, temp_.gpu_data(),
-      sum_multiplier_.gpu_data(), 0., variance_.mutable_gpu_data()); // E(X^2)
+      sum_multiplier_.gpu_data(), 0., variance_.mutable_gpu_data());  // E(X^2)
   caffe_gpu_powx(mean_.count(), mean_.gpu_data(), Dtype(2),
       temp_.mutable_gpu_data());  // (EX)^2
   caffe_gpu_sub(mean_.count(), variance_.gpu_data(), temp_.gpu_data(),