From 148535e6481b19876498ad160d9a18c04e1ba983 Mon Sep 17 00:00:00 2001
From: Yangqing Jia <jiayq84@gmail.com>
Date: Tue, 24 Sep 2013 20:08:56 -0700
Subject: [PATCH] data layer modification, and net header

---
 src/caffe/layers/data_layer.cpp    | 15 ++++++-----
 src/caffe/net.hpp                  | 53 ++++++++++++++++++++++++++++++++++++++
 src/caffe/proto/caffe.proto        |  8 ++++--
 src/caffe/test/test_data_layer.cpp | 16 +++++++-----
 4 files changed, 77 insertions(+), 15 deletions(-)
 create mode 100644 src/caffe/net.hpp

diff --git a/src/caffe/layers/data_layer.cpp b/src/caffe/layers/data_layer.cpp
index 3cd76d1..c4bb8cc 100644
--- a/src/caffe/layers/data_layer.cpp
+++ b/src/caffe/layers/data_layer.cpp
@@ -1,5 +1,7 @@
 // Copyright 2013 Yangqing Jia
 
+#include <stdint.h>
+#include <string>
 #include <vector>
 
 #include <leveldb/db.h>
@@ -7,6 +9,8 @@
 #include "caffe/layer.hpp"
 #include "caffe/vision_layers.hpp"
 
+using std::string;
+
 namespace caffe {
 
 template <typename Dtype>
@@ -28,15 +32,14 @@ void DataLayer<Dtype>::SetUp(const vector<Blob<Dtype>*>& bottom,
   // Read a data point, and use it to initialize the top blob.
   Datum datum;
   datum.ParseFromString(iter_->value().ToString());
-  const BlobProto& blob = datum.blob();
   // image
   (*top)[0]->Reshape(
-      this->layer_param_.batchsize(), blob.channels(), blob.height(),
-      blob.width());
+      this->layer_param_.batchsize(), datum.channels(), datum.height(),
+      datum.width());
   // label
   (*top)[1]->Reshape(this->layer_param_.batchsize(), 1, 1, 1);
   // datum size
-  datum_size_ = blob.data_size();
+  datum_size_ = datum.data().size();
 }
 
 template <typename Dtype>
@@ -48,9 +51,9 @@ void DataLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,
   for (int i = 0; i < this->layer_param_.batchsize(); ++i) {
     // get a blob
     datum.ParseFromString(iter_->value().ToString());
-    const BlobProto& blob = datum.blob();
+    const string& data = datum.data();
     for (int j = 0; j < datum_size_; ++j) {
-      top_data[i * datum_size_ + j] = blob.data(j);
+      top_data[i * datum_size_ + j] = (uint8_t)data[j];
     }
     top_label[i] = datum.label();
     // go to the next iter
diff --git a/src/caffe/net.hpp b/src/caffe/net.hpp
new file mode 100644
index 0000000..c8426ea
--- /dev/null
+++ b/src/caffe/net.hpp
@@ -0,0 +1,53 @@
+// Copyright 2013 Yangqing Jia
+
+#ifndef CAFFE_LAYER_H_
+#define CAFFE_LAYER_H_
+
+#include <map>
+#include <string>
+#include <vector>
+
+#include "caffe/blob.hpp"
+#include "caffe/common.hpp"
+#include "caffe/proto/caffe.pb.h"
+
+using std::map;
+using std::vector;
+using std::string;
+
+namespace caffe {
+
+template <typename Dtype>
+class Net {
+ public:
+  explicit Net(const NetParameter& param);
+  ~Net();
+  void Forward(const vector<Blob<Dtype*>> & bottom,
+      vector<Blob<Dtype*>* top);
+  Dtype Backward(const vector<Blob<Dtype*>> & bottom,
+      vector<Blob<Dtype*>* top);
+
+  // For an already initialized net, CopyTrainedLayersFrom() copies the already
+  // trained layers from another net parameter instance.
+  void CopyTrainedLayersFrom(const NetParameter& param);
+  // Writes the net to a proto.
+  void ToProto(NetParameter* param, bool write_diff = false);
+
+ protected:
+  // Individual layers in the net
+  vector<shared_ptr<Layer<Dtype> > > layers_;
+  vector<shared_ptr<Layer<Dtype> > > layer_names_;
+  // bottom_vecs stores the vectors containing the input for each layer
+  vector<vector<Blob<Dtype>*> > bottom_vecs_;
+  // top_vecs stores the vectors containing the output for each layer
+  vector<vector<Blob<Dtype>* > top_vecs_;
+  // blobs stores the blobs that store intermediate results between the
+  // layers.
+  vector<shared_ptr<Blob<Dtype> > blobs_;
+  vector<shared_ptr<Blob<Dtype> > blob_names_;
+};
+
+
+}  // namespace caffe
+
+#endif  // CAFFE_LAYER_H_
diff --git a/src/caffe/proto/caffe.proto b/src/caffe/proto/caffe.proto
index cb8c7c4..8f7e0c3 100644
--- a/src/caffe/proto/caffe.proto
+++ b/src/caffe/proto/caffe.proto
@@ -12,8 +12,12 @@ message BlobProto {
 }
 
 message Datum {
-  optional BlobProto blob = 1;
-  optional int32 label = 2;
+  optional int32 channels = 1;
+  optional int32 height = 2;
+  optional int32 width = 3;
+  // the actual image data, in bytes
+  optional bytes data = 4;
+  optional int32 label = 5;
 }
 
 message FillerParameter {
diff --git a/src/caffe/test/test_data_layer.cpp b/src/caffe/test/test_data_layer.cpp
index a080bc2..ce0d24e 100644
--- a/src/caffe/test/test_data_layer.cpp
+++ b/src/caffe/test/test_data_layer.cpp
@@ -1,9 +1,10 @@
 // Copyright 2013 Yangqing Jia
 
-#include <cstring>
 #include <cuda_runtime.h>
 #include <leveldb/db.h>
 
+#include <string>
+
 #include "gtest/gtest.h"
 #include "caffe/blob.hpp"
 #include "caffe/common.hpp"
@@ -12,6 +13,8 @@
 #include "caffe/proto/caffe.pb.h"
 #include "caffe/test/test_caffe_main.hpp"
 
+using std::string;
+
 namespace caffe {
 
 extern cudaDeviceProp CAFFE_TEST_CUDA_PROP;
@@ -38,13 +41,12 @@ class DataLayerTest : public ::testing::Test {
     for (int i = 0; i < 5; ++i) {
       Datum datum;
       datum.set_label(i);
-      BlobProto* blob = datum.mutable_blob();
-      blob->set_num(1);
-      blob->set_channels(2);
-      blob->set_height(3);
-      blob->set_width(4);
+      datum.set_channels(2);
+      datum.set_height(3);
+      datum.set_width(4);
+      std::string* data = datum.mutable_data();
       for (int j = 0; j < 24; ++j) {
-        blob->add_data(i);
+        data->push_back((uint8_t)i);
       }
       stringstream ss;
       ss << i;
-- 
2.7.4