Back-merge documentation and historical PRs to master

diff --cc docs/index.md
Simple merge

diff --cc docs/installation.md
Simple merge

diff --cc include/caffe/vision_layers.hpp
index 51f5eae,7b0b77a..cb26c98
--- 1/include/caffe/vision_layers.hpp
--- 2/include/caffe/vision_layers.hpp
+++ b/include/caffe/vision_layers.hpp
@@@ -407,38 -377,46 +407,76 @@@ class DataLayer : public Layer<Dtype> 
    Blob<Dtype> data_mean_;
  };
  
+ // This function is used to create a pthread that prefetches the data.
+ template <typename Dtype>
+ void* ImagesLayerPrefetch(void* layer_pointer);
+ 
+ template <typename Dtype>
+ class ImagesLayer : public Layer<Dtype> {
+   // The function used to perform prefetching.
+  friend void* ImagesLayerPrefetch<Dtype>(void* layer_pointer);
+ 
+  public:
+   explicit ImagesLayer(const LayerParameter& param)
+       : Layer<Dtype>(param) {}
+   virtual ~ImagesLayer();
+   virtual void SetUp(const vector<Blob<Dtype>*>& bottom,
+       vector<Blob<Dtype>*>* top);
+ 
+  protected:
+   virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
+       vector<Blob<Dtype>*>* top);
+   virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom,
+       vector<Blob<Dtype>*>* top);
+   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);
+ 
+   vector<std::pair<std::string, int> > lines_;
+   int lines_id_;
+   int datum_channels_;
+   int datum_height_;
+   int datum_width_;
+   int datum_size_;
+   pthread_t thread_;
+   shared_ptr<Blob<Dtype> > prefetch_data_;
+   shared_ptr<Blob<Dtype> > prefetch_label_;
+   Blob<Dtype> data_mean_;
+ };
+ 
  
  template <typename Dtype>
 +class HDF5DataLayer : public Layer<Dtype> {
 + public:
 +  explicit HDF5DataLayer(const LayerParameter& param)
 +      : Layer<Dtype>(param) {}
 +  virtual ~HDF5DataLayer();
 +  virtual void SetUp(const vector<Blob<Dtype>*>& bottom,
 +      vector<Blob<Dtype>*>* top);
 +
 + protected:
 +  virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
 +      vector<Blob<Dtype>*>* top);
 +  virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom,
 +      vector<Blob<Dtype>*>* top);
 +  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);
 +  virtual void load_hdf5_file_data(const char* filename);
 +
 +  std::vector<std::string> hdf_filenames_;
 +  unsigned int num_files_;
 +  unsigned int current_file_;
 +  hsize_t current_row_;
 +
 +  Blob<Dtype> data_blob_;
 +  Blob<Dtype> label_blob_;
 +};
 +
 +
 +template <typename Dtype>
  class SoftmaxLayer : public Layer<Dtype> {
   public:
    explicit SoftmaxLayer(const LayerParameter& param)

diff --cc src/caffe/layer_factory.cpp
index d8d10f3,263baf5..be8cb7e
--- 1/src/caffe/layer_factory.cpp
--- 2/src/caffe/layer_factory.cpp
+++ b/src/caffe/layer_factory.cpp
@@@ -25,12 -25,10 +25,14 @@@ Layer<Dtype>* GetLayer(const LayerParam
      return new BNLLLayer<Dtype>(param);
    } else if (type == "conv") {
      return new ConvolutionLayer<Dtype>(param);
 +  } else if (type == "concat") {
 +    return new ConcatLayer<Dtype>(param);
    } else if (type == "data") {
      return new DataLayer<Dtype>(param);
 +  } else if (type == "hdf5_data") {
 +    return new HDF5DataLayer<Dtype>(param);
+   } else if (type == "images") {
+     return new ImagesLayer<Dtype>(param);
    } else if (type == "dropout") {
      return new DropoutLayer<Dtype>(param);
    } else if (type == "euclidean_loss") {

diff --cc src/caffe/proto/caffe.proto
index 06a7cd7,183cf62..75f958b
--- 1/src/caffe/proto/caffe.proto
--- 2/src/caffe/proto/caffe.proto
+++ b/src/caffe/proto/caffe.proto
@@@ -92,10 -92,16 +92,20 @@@ message LayerParameter 
    // be larger than the number of keys in the leveldb.
    optional uint32 rand_skip = 53 [ default = 0 ];
  
-   // Concat Layer need to specify the dimension along the concat will happen, 
-   // the other dimensions must be the same for all the bottom blobs
-   // By default it will concatenate blobs along channels dimension
+   // For the Reshape Layer one need to specify the new dimensions
 -  optional int32 new_num = 60 [default = 0];
 -  optional int32 new_channels = 61 [default = 0];
 -  optional int32 new_height = 62 [default = 0];
 -  optional int32 new_width = 63 [default = 0];
 -
 -  // Used by ImageLayer to shuffle the list of files at every epoch it will also
 -  // resize images if new_height or new_width are not zero
 -  optional bool shuffle_images = 64 [default = false];
 -
++  optional int32 new_num = 60 [ default = 0 ];
++  optional int32 new_channels = 61 [ default = 0 ];
++  optional int32 new_height = 62 [ default = 0 ];
++  optional int32 new_width = 63 [ default = 0 ];
++
++  // Used by ImageLayer to shuffle the list of files at every epoch.
++  // It will also resize images if new_height or new_width are not zero
++  optional bool shuffle_images = 64 [ default = false ];
++
++  // ConcatLayer needs the dimension along which to concatenate, and 
++  // the other dimensions must be the same for all the bottom blobs.
++  // By default it will concatenate blobs along the channels dimension.
 +  optional uint32 concat_dim = 65 [ default = 1 ]; 
  }
  
  message LayerConnection {