diff options
| -rw-r--r-- | Makefile | 3 | ||||
| -rw-r--r-- | include/caffe/solver.hpp | 2 | ||||
| -rw-r--r-- | include/caffe/util/io.hpp | 2 | ||||
| -rw-r--r-- | include/caffe/vision_layers.hpp | 23 | ||||
| -rw-r--r-- | src/caffe/layer_factory.cpp | 2 | ||||
| -rw-r--r-- | src/caffe/layers/loss_layer.cu | 47 | ||||
| -rw-r--r-- | src/caffe/layers/pooling_layer.cu | 3 | ||||
| -rw-r--r-- | src/caffe/net.cpp | 2 | ||||
| -rw-r--r-- | src/caffe/util/io.cpp | 1 |
9 files changed, 80 insertions, 5 deletions
@@ -45,7 +45,8 @@ INCLUDE_DIRS := ./src ./include /usr/local/include $(CUDA_INCLUDE_DIR) \ $(MKL_INCLUDE_DIR) LIBRARY_DIRS := /usr/lib /usr/local/lib $(CUDA_LIB_DIR) $(MKL_LIB_DIR) LIBRARIES := cuda cudart cublas curand protobuf opencv_core opencv_highgui \ - glog mkl_rt mkl_intel_thread leveldb snappy pthread boost_system + glog mkl_rt mkl_intel_thread leveldb snappy pthread boost_system \ + opencv_imgproc WARNINGS := -Wall COMMON_FLAGS := -DNDEBUG $(foreach includedir,$(INCLUDE_DIRS),-I$(includedir)) diff --git a/include/caffe/solver.hpp b/include/caffe/solver.hpp index 2b402426..25ba3b68 100644 --- a/include/caffe/solver.hpp +++ b/include/caffe/solver.hpp @@ -16,6 +16,7 @@ class Solver { virtual void Solve(const char* resume_file = NULL); inline void Solve(const string resume_file) { Solve(resume_file.c_str()); } virtual ~Solver() {} + inline Net<Dtype>* net() { return net_.get(); } protected: // PreSolve is run before any solving iteration starts, allowing one to @@ -36,6 +37,7 @@ class Solver { // function that restores the state from a SolverState protocol buffer. void Restore(const char* resume_file); virtual void RestoreSolverState(const SolverState& state) = 0; + SolverParameter param_; int iter_; shared_ptr<Net<Dtype> > net_; diff --git a/include/caffe/util/io.hpp b/include/caffe/util/io.hpp index f14b1eee..3174fd0d 100644 --- a/include/caffe/util/io.hpp +++ b/include/caffe/util/io.hpp @@ -45,7 +45,7 @@ bool ReadImageToDatum(const string& filename, const int label, inline bool ReadImageToDatum(const string& filename, const int label, Datum* datum) { - ReadImageToDatum(filename, label, 0, 0, datum); + return ReadImageToDatum(filename, label, 0, 0, datum); } } // namespace caffe diff --git a/include/caffe/vision_layers.hpp b/include/caffe/vision_layers.hpp index 2e24beff..2290f0f5 100644 --- a/include/caffe/vision_layers.hpp +++ b/include/caffe/vision_layers.hpp @@ -345,6 +345,29 @@ class MultinomialLogisticLossLayer : public Layer<Dtype> { // const bool propagate_down, vector<Blob<Dtype>*>* bottom); }; +template <typename Dtype> +class InfogainLossLayer : public Layer<Dtype> { + public: + explicit InfogainLossLayer(const LayerParameter& param) + : Layer<Dtype>(param), infogain_() {} + virtual void SetUp(const vector<Blob<Dtype>*>& bottom, + vector<Blob<Dtype>*>* top); + + protected: + // The loss layer will do nothing during forward - all computation are + // carried out in the backward pass. + virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom, + vector<Blob<Dtype>*>* top) { return; } + virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom, + vector<Blob<Dtype>*>* top) { return; } + virtual Dtype Backward_cpu(const vector<Blob<Dtype>*>& top, + const bool propagate_down, vector<Blob<Dtype>*>* bottom); + // virtual Dtype Backward_gpu(const vector<Blob<Dtype>*>& top, + // const bool propagate_down, vector<Blob<Dtype>*>* bottom); + + Blob<Dtype> infogain_; +}; + // SoftmaxWithLossLayer is a layer that implements softmax and then computes // the loss - it is preferred over softmax + multinomiallogisticloss in the diff --git a/src/caffe/layer_factory.cpp b/src/caffe/layer_factory.cpp index 178607f4..b663cb2c 100644 --- a/src/caffe/layer_factory.cpp +++ b/src/caffe/layer_factory.cpp @@ -33,6 +33,8 @@ Layer<Dtype>* GetLayer(const LayerParameter& param) { return new EuclideanLossLayer<Dtype>(param); } else if (type == "im2col") { return new Im2colLayer<Dtype>(param); + } else if (type == "infogain_loss") { + return new InfogainLossLayer<Dtype>(param); } else if (type == "innerproduct") { return new InnerProductLayer<Dtype>(param); } else if (type == "lrn") { diff --git a/src/caffe/layers/loss_layer.cu b/src/caffe/layers/loss_layer.cu index 0a6f5ee9..ac05ba41 100644 --- a/src/caffe/layers/loss_layer.cu +++ b/src/caffe/layers/loss_layer.cu @@ -6,6 +6,7 @@ #include "caffe/layer.hpp" #include "caffe/vision_layers.hpp" #include "caffe/util/math_functions.hpp" +#include "caffe/util/io.hpp" using std::max; @@ -17,7 +18,7 @@ template <typename Dtype> void MultinomialLogisticLossLayer<Dtype>::SetUp( const vector<Blob<Dtype>*>& bottom, vector<Blob<Dtype>*>* top) { CHECK_EQ(bottom.size(), 2) << "Loss Layer takes two blobs as input."; - CHECK_EQ(top->size(), 0) << "Loss Layer takes no as output."; + CHECK_EQ(top->size(), 0) << "Loss Layer takes no output."; CHECK_EQ(bottom[0]->num(), bottom[1]->num()) << "The data and label should have the same number."; CHECK_EQ(bottom[1]->channels(), 1); @@ -50,6 +51,49 @@ Dtype MultinomialLogisticLossLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype> template <typename Dtype> +void InfogainLossLayer<Dtype>::SetUp( + const vector<Blob<Dtype>*>& bottom, vector<Blob<Dtype>*>* top) { + CHECK_EQ(bottom.size(), 2) << "Loss Layer takes two blobs as input."; + CHECK_EQ(top->size(), 0) << "Loss Layer takes no output."; + CHECK_EQ(bottom[0]->num(), bottom[1]->num()) + << "The data and label should have the same number."; + CHECK_EQ(bottom[1]->channels(), 1); + CHECK_EQ(bottom[1]->height(), 1); + CHECK_EQ(bottom[1]->width(), 1); + BlobProto blob_proto; + ReadProtoFromBinaryFile(this->layer_param_.source(), &blob_proto); + infogain_.FromProto(blob_proto); + CHECK_EQ(infogain_.num(), 1); + CHECK_EQ(infogain_.channels(), 1); + CHECK_EQ(infogain_.height(), infogain_.width()); +}; + + +template <typename Dtype> +Dtype InfogainLossLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top, + const bool propagate_down, + vector<Blob<Dtype>*>* bottom) { + const Dtype* bottom_data = (*bottom)[0]->cpu_data(); + const Dtype* bottom_label = (*bottom)[1]->cpu_data(); + const Dtype* infogain_mat = infogain_.cpu_data(); + Dtype* bottom_diff = (*bottom)[0]->mutable_cpu_diff(); + int num = (*bottom)[0]->num(); + int dim = (*bottom)[0]->count() / (*bottom)[0]->num(); + CHECK_EQ(infogain_.height(), dim); + Dtype loss = 0; + for (int i = 0; i < num; ++i) { + int label = static_cast<int>(bottom_label[i]); + for (int j = 0; j < dim; ++j) { + Dtype prob = max(bottom_data[i * dim + j], kLOG_THRESHOLD); + loss -= infogain_mat[label * dim + j] * log(prob); + bottom_diff[i * dim + j] = - infogain_mat[label * dim + j] / prob / num; + } + } + return loss / num; +} + + +template <typename Dtype> void EuclideanLossLayer<Dtype>::SetUp( const vector<Blob<Dtype>*>& bottom, vector<Blob<Dtype>*>* top) { CHECK_EQ(bottom.size(), 2) << "Loss Layer takes two blobs as input."; @@ -122,6 +166,7 @@ void AccuracyLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom, } INSTANTIATE_CLASS(MultinomialLogisticLossLayer); +INSTANTIATE_CLASS(InfogainLossLayer); INSTANTIATE_CLASS(EuclideanLossLayer); INSTANTIATE_CLASS(AccuracyLayer); diff --git a/src/caffe/layers/pooling_layer.cu b/src/caffe/layers/pooling_layer.cu index 1cbb4abe..4fd326cb 100644 --- a/src/caffe/layers/pooling_layer.cu +++ b/src/caffe/layers/pooling_layer.cu @@ -120,7 +120,8 @@ __global__ void StoPoolForwardTest(const int nthreads, int hend = min(hstart + ksize, height); int wstart = pw * stride; int wend = min(wstart + ksize, width); - Dtype cumsum = 0.; + // We set cumsum to be 0 to avoid divide-by-zero problems + Dtype cumsum = FLT_MIN; Dtype cumvalues = 0.; bottom_data += (n * channels + c) * height * width; // First pass: get sum diff --git a/src/caffe/net.cpp b/src/caffe/net.cpp index dec42036..3266064d 100644 --- a/src/caffe/net.cpp +++ b/src/caffe/net.cpp @@ -287,7 +287,7 @@ void Net<Dtype>::CopyTrainedLayersFrom(const NetParameter& param) { DLOG(INFO) << "Ignoring source layer " << source_layer_name; continue; } - DLOG(INFO) << "Loading source layer " << source_layer_name; + LOG(INFO) << "Copying source layer " << source_layer_name; vector<shared_ptr<Blob<Dtype> > >& target_blobs = layers_[target_layer_id]->blobs(); CHECK_EQ(target_blobs.size(), source_layer.blobs_size()) diff --git a/src/caffe/util/io.cpp b/src/caffe/util/io.cpp index c4682f52..ced807ae 100644 --- a/src/caffe/util/io.cpp +++ b/src/caffe/util/io.cpp @@ -7,6 +7,7 @@ #include <google/protobuf/io/coded_stream.h> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> +#include <opencv2/imgproc/imgproc.hpp> #include <algorithm> #include <string> |