caffe 源码随便记录

一些打印代码：
caffe.proto里面关于LayerParameter的描述

message LayerParameter {
  optional string name = 1; // the layer name
  optional string type = 2; // the layer type
  repeated string bottom = 3; // the name of each bottom blob
  repeated string top = 4; // the name of each top blob

  // The train / test phase for computation.
  optional Phase phase = 10;

  // The amount of weight to assign each top blob in the objective.
  // Each layer assigns a default value, usually of either 0 or 1,
  // to each top blob.
  repeated float loss_weight = 5;
...
...
...

repeated就是相当于vector，所以访问：

vector<shared_ptr<Layer<Dtype> > > layers_;

    std::string layer_name_my = layers_[i]->layer_param().name();
    std::string layer_type_my = layers_[i]->layer_param().type();
    std::cout<<i<<"
   layer_name="<<layer_name_my<<"     type="<<layer_type_my<<std::endl;

    int bottom_name_size = layers_[i]->layer_param().bottom().size();
    if(bottom_name_size>0)
    {
      std::string name = layers_[i]->layer_param().bottom(0);
      int nnn=0;
      int a;
    }

    int top_name_size = layers_[i]->layer_param().top().size();
    if(top_name_size>0)
    {
      std::string name_top = layers_[i]->layer_param().top(0);
      int nnn=0;
      int a;
    }

打印blob数值

template <typename Dtype>
void prit_blob(Blob<Dtype>* blob_tmp)
{
  std::cout<<"-------------------------start print blob---------------------------"<<std::endl;
  std::cout<<"bottom shape="<<blob_tmp->shape_string()<<std::endl;
   Dtype * p = blob_tmp->mutable_cpu_data();
   for(int i=0;i<blob_tmp->count();i++)
   {
     std::cout<<p[i]<<std::endl;
   }

  std::cout<<"-------------------------end print blob---------------------------"<<std::endl;
}

net forward 添加打印，查看层与层之间的连接

template <typename Dtype>
void prit_blob(Blob<Dtype>* blob_tmp)
{
  std::cout<<"-------------------------start print blob---------------------------"<<std::endl;
  std::cout<<"bottom shape="<<blob_tmp->shape_string()<<std::endl;
   Dtype * p = blob_tmp->mutable_cpu_data();
   for(int i=0;i<blob_tmp->count();i++)
   {
     std::cout<<p[i]<<std::endl;
   }

  std::cout<<"-------------------------end print blob---------------------------"<<std::endl;
}

template <typename Dtype>
Dtype Net<Dtype>::ForwardFromTo(int start, int end) {
  CHECK_GE(start, 0);
  CHECK_LT(end, layers_.size());
  Dtype loss = 0;

  std::cout<<std::endl;
  std::cout<<"-------------------------start net---------------------------"<<std::endl;
  for (int i = start; i <= end; ++i) {
    for (int c = 0; c < before_forward_.size(); ++c) {
      before_forward_[c]->run(i);
    }

    ///////////////////////////////////////////////////////////////////////////////////////////////////
    std::string layer_name_my = layers_[i]->layer_param().name();
    std::string layer_type_my = layers_[i]->layer_param().type();
    std::cout<<"
-----------------------------------------------------------"<<std::endl;
    std::cout<<i<<"==== layer_name="<<layer_name_my<<"     type="<<layer_type_my<<std::endl;

    int bottom_name_size = layers_[i]->layer_param().bottom().size();
    if(bottom_name_size>0)
    {
      for(int ii=0;ii<bottom_name_size;ii++)
      {
        std::cout<<ii<<" ::bottom name="<<layers_[i]->layer_param().bottom(ii)<<std::endl;
        Blob<Dtype>* ptr_blob = bottom_vecs_[i][ii];
        std::cout<<"bottom shape="<<ptr_blob->shape_string()<<std::endl;
      }
    } else{
      std::cout<<"no bottom"<<std::endl;
    }


//    std::cout<<"bottom_size="<<bottom_vecs_[i].size()<<std::endl;
//    for(int j=0;j<bottom_vecs_[i].size();j++)
//    {
//      Blob<Dtype>* ptr_blob = bottom_vecs_[i][j];
//      std::cout<<"bottom shape="<<ptr_blob->shape_string()<<std::endl;
//    }
    ////////////////////////////////////////////////////////////////////////////////////////////////////

//    if("lstm1x_r2_"==layer_name_my && "Input"==layer_type_my)
//    {
//
//      for(int j=0;j<top_vecs_[i].size();j++)
//      {
//        Blob<Dtype>* ptr_blob = top_vecs_[i][j];
//        std::cout<<"--- input top shape="<<ptr_blob->shape_string()<<std::endl;
//
//        if(top_vecs_[i][j]->count()<327680-1)
//        {
//          prit_blob(ptr_blob);
//        }
//      }
//    }


    Dtype layer_loss = layers_[i]->Forward(bottom_vecs_[i], top_vecs_[i]);

//    if("lstm1x_r2_"==layer_name_my && "Input"==layer_type_my)
//    {
//
//      for(int j=0;j<top_vecs_[i].size();j++)
//      {
//        Blob<Dtype>* ptr_blob = top_vecs_[i][j];
//        std::cout<<"--- input top shape="<<ptr_blob->shape_string()<<std::endl;
//
//        if(top_vecs_[i][j]->count()<327680-1)
//        {
//          prit_blob(ptr_blob);
//        }
//      }
//    }


    int top_name_size = layers_[i]->layer_param().top().size();
    if(top_name_size>0)
    {
      for(int ii=0;ii<top_name_size;ii++)
      {
        std::cout<<ii<<" ::top name="<<layers_[i]->layer_param().top(ii)<<std::endl;
        Blob<Dtype>* ptr_blob = top_vecs_[i][ii];
        std::cout<<"top shape="<<ptr_blob->shape_string()<<std::endl;
      }
    } else{
      std::cout<<"no top"<<std::endl;
    }





//    std::cout<<"top_size="<<top_vecs_[i].size()<<std::endl;
//    for(int j=0;j<top_vecs_[i].size();j++)
//    {
//      Blob<Dtype>* ptr_blob = top_vecs_[i][j];
//      std::cout<<"top shape="<<ptr_blob->shape_string()<<std::endl;
//    }




    loss += layer_loss;
    if (debug_info_) { ForwardDebugInfo(i); }
    for (int c = 0; c < after_forward_.size(); ++c) {
      after_forward_[c]->run(i);
    }
  }
  std::cout<<"-------------------------end net---------------------------"<<std::endl;
  return loss;
}

打印的如下：

-----------------------------------------------------------
-----------------------------------------------------------
430==== layer_name=lstm1x_r2_h_conted_69     type=Scale
0 ::bottom name=h_69_lstm1x_r2_unit_69_1_split_0
bottom shape=1 1 100 (100)
1 ::bottom name=cont_70_lstm1x_r2_cont_slice_69_split_0
bottom shape=1 1 (1)
0 ::top name=h_conted_69
top shape=1 1 100 (100)

-----------------------------------------------------------
431==== layer_name=lstm1x_r2_transform_70     type=InnerProduct
0 ::bottom name=h_conted_69
bottom shape=1 1 100 (100)
0 ::top name=W_hc_h_69
top shape=1 1 400 (400)

-----------------------------------------------------------
432==== layer_name=lstm1x_r2_gate_input_70     type=Eltwise
0 ::bottom name=W_hc_h_69
bottom shape=1 1 400 (400)
1 ::bottom name=W_xc_x_70
bottom shape=1 1 400 (400)
0 ::top name=gate_input_70
top shape=1 1 400 (400)

-----------------------------------------------------------
433==== layer_name=lstm1x_r2_unit_70     type=LSTMUnit
0 ::bottom name=c_69
bottom shape=1 1 100 (100)
1 ::bottom name=gate_input_70
bottom shape=1 1 400 (400)
2 ::bottom name=cont_70_lstm1x_r2_cont_slice_69_split_1
bottom shape=1 1 (1)
0 ::top name=c_70
top shape=1 1 100 (100)
1 ::top name=h_70
top shape=1 1 100 (100)

-----------------------------------------------------------
434==== layer_name=h_70_lstm1x_r2_unit_70_1_split     type=Split
0 ::bottom name=h_70
bottom shape=1 1 100 (100)
0 ::top name=h_70_lstm1x_r2_unit_70_1_split_0
top shape=1 1 100 (100)
1 ::top name=h_70_lstm1x_r2_unit_70_1_split_1
top shape=1 1 100 (100)

-----------------------------------------------------------

这里主要是为了看LSTM算子的层与层之间的关系的。因为prototxt就显示一个LSTM，其实这个算子里面包含了太多了。。