From ccc4b30c04632416393ef261fcd17945e161aaee Mon Sep 17 00:00:00 2001
From: Jonathan L Long <jonlong@cs.berkeley.edu>
Date: Mon, 17 Feb 2014 16:35:38 -0800
Subject: [PATCH] add Net::Forward/Backward From/To

---
 include/caffe/net.hpp |  6 ++++++
 src/caffe/net.cpp     | 56 +++++++++++++++++++++++++++++++++++++++++----------
 2 files changed, 51 insertions(+), 11 deletions(-)

diff --git a/include/caffe/net.hpp b/include/caffe/net.hpp
index ce82e28..d7282f5 100644
--- a/include/caffe/net.hpp
+++ b/include/caffe/net.hpp
@@ -35,6 +35,9 @@ class Net {
   // Run forward with the input blobs already fed separately. You can get the
   // input blobs using input_blobs().
   const vector<Blob<Dtype>*>& ForwardPrefilled(Dtype* loss = NULL);
+  Dtype ForwardFromTo(int start, int end);
+  Dtype ForwardFrom(int start);
+  Dtype ForwardTo(int end);
   // Run forward using a set of bottom blobs, and return the result.
   const vector<Blob<Dtype>*>& Forward(const vector<Blob<Dtype>* > & bottom,
       Dtype* loss = NULL);
@@ -46,6 +49,9 @@ class Net {
   // computes the gradient w.r.t the parameters, and the data has already
   // been provided during the forward pass.
   void Backward();
+  void BackwardFromTo(int start, int end);
+  void BackwardFrom(int start);
+  void BackwardTo(int end);
 
   Dtype ForwardBackward(const vector<Blob<Dtype>* > & bottom) {
     Dtype loss;
diff --git a/src/caffe/net.cpp b/src/caffe/net.cpp
index aba4cc2..cadcdcd 100644
--- a/src/caffe/net.cpp
+++ b/src/caffe/net.cpp
@@ -335,16 +335,34 @@ void Net<Dtype>::GetLearningRateAndWeightDecay() {
 }
 
 template <typename Dtype>
-const vector<Blob<Dtype>*>& Net<Dtype>::ForwardPrefilled(Dtype* loss) {
-  if (loss != NULL) {
-    *loss = Dtype(0.);
-  }
-  for (int i = 0; i < layers_.size(); ++i) {
+Dtype Net<Dtype>::ForwardFromTo(int start, int end) {
+  CHECK_GE(start, 0);
+  CHECK_LT(end, layers_.size());
+  Dtype loss = 0;
+  for (int i = start; i <= end; ++i) {
     // LOG(ERROR) << "Forwarding " << layer_names_[i];
     Dtype layer_loss = layers_[i]->Forward(bottom_vecs_[i], &top_vecs_[i]);
-    if (loss != NULL) {
-      *loss += layer_loss;
-    }
+    loss += layer_loss;
+  }
+  return loss;
+}
+
+template <typename Dtype>
+Dtype Net<Dtype>::ForwardFrom(int start) {
+  return ForwardFromTo(start, layers_.size() - 1);
+}
+
+template <typename Dtype>
+Dtype Net<Dtype>::ForwardTo(int end) {
+  return ForwardFromTo(0, end);
+}
+
+template <typename Dtype>
+const vector<Blob<Dtype>*>& Net<Dtype>::ForwardPrefilled(Dtype* loss) {
+  if (loss != NULL) {
+    *loss = ForwardFromTo(0, layers_.size() - 1);
+  } else {
+    ForwardFromTo(0, layers_.size() - 1);
   }
   return net_output_blobs_;
 }
@@ -380,10 +398,11 @@ string Net<Dtype>::Forward(const string& input_blob_protos, Dtype* loss) {
   return output;
 }
 
-
 template <typename Dtype>
-void Net<Dtype>::Backward() {
-  for (int i = layers_.size() - 1; i >= 0; --i) {
+void Net<Dtype>::BackwardFromTo(int start, int end) {
+  CHECK_GE(end, 0);
+  CHECK_LT(start, layers_.size());
+  for (int i = start; i >= end; --i) {
     if (layer_need_backward_[i]) {
       layers_[i]->Backward(
           top_vecs_[i], bottom_need_backward_[i], &bottom_vecs_[i]);
@@ -423,6 +442,21 @@ void Net<Dtype>::ShareTrainedLayersWith(Net* other) {
 }
 
 template <typename Dtype>
+void Net<Dtype>::BackwardFrom(int start) {
+  BackwardFromTo(start, 0);
+}
+
+template <typename Dtype>
+void Net<Dtype>::BackwardTo(int end) {
+  BackwardFromTo(layers_.size() - 1, end);
+}
+
+template <typename Dtype>
+void Net<Dtype>::Backward() {
+  BackwardFromTo(layers_.size() - 1, 0);
+}
+
+template <typename Dtype>
 void Net<Dtype>::CopyTrainedLayersFrom(const NetParameter& param) {
   int num_source_layers = param.layers_size();
   for (int i = 0; i < num_source_layers; ++i) {
-- 
2.7.4