ifdef engine default

diff --git a/src/caffe/layers/conv_layer.cpp b/src/caffe/layers/conv_layer.cpp
index 43ec6de..1a1248f 100644 (file)
--- a/src/caffe/layers/conv_layer.cpp
+++ b/src/caffe/layers/conv_layer.cpp
@@ -12,7 +12,6 @@ template <typename Dtype>
 void ConvolutionLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
       vector<Blob<Dtype>*>* top) {
   ConvolutionParameter conv_param = this->layer_param_.convolution_param();
-  // Check configuration.
   CHECK(!conv_param.has_kernel_size() !=
       !(conv_param.has_kernel_h() && conv_param.has_kernel_w()))
       << "Filter size is kernel_size OR kernel_h and kernel_w; not both";
@@ -113,12 +112,6 @@ void ConvolutionLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
     caffe_set(N_, Dtype(1), bias_multiplier_.mutable_cpu_data());
   }
   this->param_propagate_down_.resize(this->blobs_.size(), true);
-  // Default computation engine.
-#ifdef CAFFE_ENGINE
-  if (conv_param.engine() == ConvolutionParameter_Engine_DEFAULT) {
-    conv_param.set_engine(ConvolutionParameter_Engine_CAFFE);
-  }
-#endif
 }
 
 

diff --git a/src/caffe/layers/pooling_layer.cpp b/src/caffe/layers/pooling_layer.cpp
index fd13b1d..9e77fa2 100644 (file)
--- a/src/caffe/layers/pooling_layer.cpp
+++ b/src/caffe/layers/pooling_layer.cpp
@@ -96,12 +96,6 @@ void PoolingLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
     rand_idx_.Reshape(bottom[0]->num(), channels_, pooled_height_,
       pooled_width_);
   }
-  // Default computation engine.
-#ifdef CAFFE_ENGINE
-  if (pool_param.engine() == PoolingParameter_Engine_DEFAULT) {
-    pool_param.set_engine(PoolingParameter_Engine_CAFFE);
-  }
-#endif
 }
 
 // TODO(Yangqing): Is there a faster way to do pooling in the channel-first

diff --git a/src/caffe/layers/relu_layer.cpp b/src/caffe/layers/relu_layer.cpp
index 7b41f7a..b50352f 100644 (file)
--- a/src/caffe/layers/relu_layer.cpp
+++ b/src/caffe/layers/relu_layer.cpp
@@ -9,21 +9,14 @@ namespace caffe {
 template <typename Dtype>
 void ReLULayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
     vector<Blob<Dtype>*>* top) {
-  ReLUParameter relu_param = this->layer_param_.relu_param();
   const Dtype* bottom_data = bottom[0]->cpu_data();
   Dtype* top_data = (*top)[0]->mutable_cpu_data();
   const int count = bottom[0]->count();
-  Dtype negative_slope = relu_param.negative_slope();
+  Dtype negative_slope = this->layer_param_.relu_param().negative_slope();
   for (int i = 0; i < count; ++i) {
     top_data[i] = std::max(bottom_data[i], Dtype(0))
         + negative_slope * std::min(bottom_data[i], Dtype(0));
   }
-  // Default computation engine.
-#ifdef CAFFE_ENGINE
-  if (relu_param.engine() == ReLUParameter_Engine_DEFAULT) {
-    relu_param.set_engine(ReLUParameter_Engine_CAFFE);
-  }
-#endif
 }
 
 template <typename Dtype>

diff --git a/src/caffe/layers/sigmoid_layer.cpp b/src/caffe/layers/sigmoid_layer.cpp
index e045b7e..d7bba7f 100644 (file)
--- a/src/caffe/layers/sigmoid_layer.cpp
+++ b/src/caffe/layers/sigmoid_layer.cpp
@@ -15,19 +15,12 @@ inline Dtype sigmoid(Dtype x) {
 template <typename Dtype>
 void SigmoidLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
     vector<Blob<Dtype>*>* top) {
-  SigmoidParameter sigmoid_param = this->layer_param_.sigmoid_param();
   const Dtype* bottom_data = bottom[0]->cpu_data();
   Dtype* top_data = (*top)[0]->mutable_cpu_data();
   const int count = bottom[0]->count();
   for (int i = 0; i < count; ++i) {
     top_data[i] = sigmoid(bottom_data[i]);
   }
-  // Default computation engine.
-#ifdef CAFFE_ENGINE
-  if (sigmoid_param.engine() == SigmoidParameter_Engine_DEFAULT) {
-    sigmoid_param.set_engine(SigmoidParameter_Engine_CAFFE);
-  }
-#endif
 }
 
 template <typename Dtype>

diff --git a/src/caffe/layers/softmax_layer.cpp b/src/caffe/layers/softmax_layer.cpp
index bfc4116..29767ac 100644 (file)
--- a/src/caffe/layers/softmax_layer.cpp
+++ b/src/caffe/layers/softmax_layer.cpp
@@ -11,7 +11,6 @@ namespace caffe {
 template <typename Dtype>
 void SoftmaxLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
       vector<Blob<Dtype>*>* top) {
-  SoftmaxParameter softmax_param = this->layer_param_.softmax_param();
   (*top)[0]->Reshape(bottom[0]->num(), bottom[0]->channels(),
       bottom[0]->height(), bottom[0]->width());
   sum_multiplier_.Reshape(1, bottom[0]->channels(), 1, 1);
@@ -20,12 +19,6 @@ void SoftmaxLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
     multiplier_data[i] = 1.;
   }
   scale_.Reshape(bottom[0]->num(), 1, bottom[0]->height(), bottom[0]->width());
-  // Default computation engine.
-#ifdef CAFFE_ENGINE
-  if (softmax_param.engine() == SoftmaxParameter_Engine_DEFAULT) {
-    softmax_param.set_engine(SoftmaxParameter_Engine_CAFFE);
-  }
-#endif
 }
 
 template <typename Dtype>

diff --git a/src/caffe/layers/tanh_layer.cpp b/src/caffe/layers/tanh_layer.cpp
index 1ea0073..8dae005 100644 (file)
--- a/src/caffe/layers/tanh_layer.cpp
+++ b/src/caffe/layers/tanh_layer.cpp
@@ -12,7 +12,6 @@ namespace caffe {
 template <typename Dtype>
 void TanHLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
     vector<Blob<Dtype>*>* top) {
-  TanHParameter tanh_param = this->layer_param_.tanh_param();
   const Dtype* bottom_data = bottom[0]->cpu_data();
   Dtype* top_data = (*top)[0]->mutable_cpu_data();
   Dtype exp2x;
@@ -21,12 +20,6 @@ void TanHLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
     exp2x = exp(2 * bottom_data[i]);
     top_data[i] = (exp2x - Dtype(1)) / (exp2x + Dtype(1));
   }
-  // Default computation engine.
-#ifdef CAFFE_ENGINE
-  if (tanh_param.engine() == TanHParameter_Engine_DEFAULT) {
-    tanh_param.set_engine(TanHParameter_Engine_CAFFE);
-  }
-#endif
 }
 
 template <typename Dtype>