Blobs are N-D arrays (for N not necessarily equals 4)

.gitignore

@@ -44,6 +44,9 @@
 # QtCreator files
 *.user
 
+# PyCharm files
+.idea
+
 # OSX dir files
 .DS_Store
 

CMakeLists.txt

@@ -17,14 +17,15 @@ caffe_option(CPU_ONLY  "Build Caffe wihtout CUDA support" OFF) # TODO: rename to
 caffe_option(USE_CUDNN "Build Caffe with cuDNN libary support" ON IF NOT CPU_ONLY)
 caffe_option(BUILD_SHARED_LIBS "Build shared libraries" ON)
 caffe_option(BUILD_python "Build Python wrapper" ON)
+set(python_version "2" CACHE STRING "Specify which python version to use")
 caffe_option(BUILD_matlab "Build Matlab wrapper" OFF IF UNIX OR APPLE)
 caffe_option(BUILD_docs   "Build documentation" ON IF UNIX OR APPLE)
 
 # ---[ Dependencies
 include(cmake/Dependencies.cmake)
 
 # ---[ Flags
-if(UNIX OR APLE)
+if(UNIX OR APPLE)
   set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fPIC -Wall")
 endif()
 

Makefile

@@ -261,7 +261,8 @@ ifneq (,$(findstring clang++,$(CXX)))
 else ifneq (,$(findstring g++,$(CXX)))
 	STATIC_LINK_COMMAND := -Wl,--whole-archive $(STATIC_NAME) -Wl,--no-whole-archive
 else
-	$(error Cannot static link with the $(CXX) compiler.)
+  # The following line must not be indented with a tab, since we are not inside a target
+  $(error Cannot static link with the $(CXX) compiler)
 endif
 
 # Debugging
@@ -319,7 +320,7 @@ else
 		# 10.10 has accelerate while 10.9 has veclib
 		XCODE_CLT_VER := $(shell pkgutil --pkg-info=com.apple.pkg.CLTools_Executables | grep -o 'version: 6')
 		ifneq (,$(findstring version: 6,$(XCODE_CLT_VER)))
-			BLAS_INCLUDE ?= /Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.10.sdk/System/Library/Frameworks/Accelerate.framework/Versions/Current/Frameworks/vecLib.framework/Headers/
+			BLAS_INCLUDE ?= /System/Library/Frameworks/Accelerate.framework/Versions/Current/Frameworks/vecLib.framework/Headers/
 			LDFLAGS += -framework Accelerate
 		else
 			BLAS_INCLUDE ?= /System/Library/Frameworks/vecLib.framework/Versions/Current/Headers/
@@ -450,6 +451,7 @@ $(MAT$(PROJECT)_SO): $(MAT$(PROJECT)_SRC) $(STATIC_NAME)
 			CXXLIBS="\$$CXXLIBS $(STATIC_LINK_COMMAND) $(LDFLAGS)" -output $@
 
 runtest: $(TEST_ALL_BIN)
+	$(TOOL_BUILD_DIR)/caffe
 	$(TEST_ALL_BIN) $(TEST_GPUID) --gtest_shuffle $(TEST_FILTER)
 
 pytest: py
@@ -537,7 +539,12 @@ $(TOOL_BUILD_DIR)/%: $(TOOL_BUILD_DIR)/%.bin | $(TOOL_BUILD_DIR)
 	@ $(RM) $@
 	@ ln -s $(abspath $<) $@
 
-$(TOOL_BINS) $(EXAMPLE_BINS): %.bin : %.o | $(DYNAMIC_NAME)
+$(TOOL_BINS): %.bin : %.o | $(DYNAMIC_NAME)
+	@ echo CXX/LD -o $@
+	$(Q)$(CXX) $< -o $@ $(LINKFLAGS) -l$(PROJECT) $(LDFLAGS) \
+		-Wl,-rpath,$(ORIGIN)/../lib
+
+$(EXAMPLE_BINS): %.bin : %.o | $(DYNAMIC_NAME)
 	@ echo CXX/LD -o $@
 	$(Q)$(CXX) $< -o $@ $(LINKFLAGS) -l$(PROJECT) $(LDFLAGS) \
 		-Wl,-rpath,$(ORIGIN)/../../lib

cmake/Dependencies.cmake

@@ -92,12 +92,39 @@ endif()
 
 # ---[ Python
 if(BUILD_python)
-  # disable Python 3 search
-  find_package(PythonInterp 2.7)
-  find_package(PythonLibs 2.7)
-  find_package(NumPy 1.7.1)
-  find_package(Boost 1.46 COMPONENTS python)
-
+  if(NOT "${python_version}" VERSION_LESS "3.0.0")
+    # use python3
+    find_package(PythonInterp 3.0)
+    find_package(PythonLibs 3.0)
+    find_package(NumPy 1.7.1)
+    # Find the matching boost python implementation
+    set(version ${PYTHONLIBS_VERSION_STRING})
+
+    STRING( REPLACE "." "" boost_py_version ${version} )
+    find_package(Boost 1.46 COMPONENTS "python-py${boost_py_version}")
+    set(Boost_PYTHON_FOUND ${Boost_PYTHON-PY${boost_py_version}_FOUND})
+
+    while(NOT "${version}" STREQUAL "" AND NOT Boost_PYTHON_FOUND)
+      STRING( REGEX REPLACE "([0-9.]+).[0-9]+" "\\1" version ${version} )
+      STRING( REGEX MATCHALL "([0-9.]+).[0-9]+" has_more_version ${version} )
+      if("${has_more_version}" STREQUAL "")
+        break()
+      endif()
+
+      STRING( REPLACE "." "" boost_py_version ${version} )
+      find_package(Boost 1.46 COMPONENTS "python-py${boost_py_version}")
+      set(Boost_PYTHON_FOUND ${Boost_PYTHON-PY${boost_py_version}_FOUND})
+    endwhile()
+    if(NOT Boost_PYTHON_FOUND)
+      find_package(Boost 1.46 COMPONENTS python)
+    endif()
+  else()
+    # disable Python 3 search
+    find_package(PythonInterp 2.7)
+    find_package(PythonLibs 2.7)
+    find_package(NumPy 1.7.1)
+    find_package(Boost 1.46 COMPONENTS python)
+  endif()
   if(PYTHONLIBS_FOUND AND NUMPY_FOUND AND Boost_PYTHON_FOUND)
     set(HAVE_PYTHON TRUE)
   endif()

cmake/Misc.cmake

@@ -32,6 +32,11 @@ endif()
 set(CMAKE_INSTALL_RPATH_USE_LINK_PATH TRUE CACHE BOOLEAN "Use link paths for shared library rpath")
 set(CMAKE_MACOSX_RPATH TRUE)
 
+list(FIND CMAKE_PLATFORM_IMPLICIT_LINK_DIRECTORIES ${CMAKE_INSTALL_PREFIX}/lib __is_systtem_dir)
+if(${__is_systtem_dir} STREQUAL -1)
+  set(CMAKE_INSTALL_RPATH ${CMAKE_INSTALL_PREFIX}/lib)
+endif()
+
 # ---[ Funny target
 if(UNIX OR APPLE)
   add_custom_target(symlink_to_build COMMAND "ln" "-sf" "${PROJECT_BINARY_DIR}" "${PROJECT_SOURCE_DIR}/build"

cmake/Summary.cmake

@@ -107,17 +107,19 @@ function(caffe_print_configuration_summary)
   caffe_status("  C++ compiler      :   ${CMAKE_CXX_COMPILER}")
   caffe_status("  Release CXX flags :   ${__flags_rel}")
   caffe_status("  Debug CXX flags   :   ${__flags_deb}")
-  caffe_status("  BUILD_SHARED_LIBS :   ${BUILD_SHARED_LIBS}")
   caffe_status("  Build type        :   ${CMAKE_BUILD_TYPE}")
+  caffe_status("")
+  caffe_status("  BUILD_SHARED_LIBS :   ${BUILD_SHARED_LIBS}")
   caffe_status("  BUILD_python      :   ${BUILD_python}")
   caffe_status("  BUILD_matlab      :   ${BUILD_matlab}")
   caffe_status("  BUILD_docs        :   ${BUILD_docs}")
   caffe_status("  CPU_ONLY          :   ${CPU_ONLY}")
   caffe_status("")
   caffe_status("Dependencies:")
   caffe_status("  BLAS              : " APPLE THEN "Yes (vecLib)" ELSE "Yes (${BLAS})")
+  caffe_status("  Boost             :   Yes (ver. ${Boost_MAJOR_VERSION}.${Boost_MINOR_VERSION})")
   caffe_status("  glog              :   Yes")
-  caffe_status("  gflags            :   Yes")
+  caffe_status("  gflags            :   Yes")  
   caffe_status("  protobuf          : " PROTOBUF_FOUND THEN "Yes (ver. ${PROTOBUF_VERSION})" ELSE "No" )
   caffe_status("  lmdb              : " LMDB_FOUND THEN "Yes (ver. ${LMDB_VERSION})" ELSE "No")
   caffe_status("  Snappy            : " SNAPPY_FOUND THEN "Yes (ver. ${Snappy_VERSION})" ELSE "No" )

docs/installation.md

@@ -30,7 +30,7 @@ Caffe has several dependencies.
 
 Pycaffe and Matcaffe interfaces have their own natural needs.
 
-* For Python Caffe:  `Python 2.7`, `numpy (>= 1.7)`, boost-provided `boost.python`
+* For Python Caffe:  `Python 2.7` or `Python 3.3+`, `numpy (>= 1.7)`, boost-provided `boost.python`
 * For MATLAB Caffe: MATLAB with the `mex` compiler.
 
 **cuDNN Caffe**: for fastest operation Caffe is accelerated by drop-in integration of [NVIDIA cuDNN](https://developer.nvidia.com/cudnn). To speed up your Caffe models, install cuDNN then uncomment the `USE_CUDNN := 1` flag in `Makefile.config` when installing Caffe. Acceleration is automatic. For now cuDNN v1 is integrated but see [PR #1731](https://github.com/BVLC/caffe/pull/1731) for v2.
@@ -69,7 +69,7 @@ but we suggest first installing the [Anaconda](https://store.continuum.io/cshop/
 
 To import the `caffe` Python module after completing the installation, add the module directory to your `$PYTHONPATH` by `export PYTHONPATH=/path/to/caffe/python:$PYTHONPATH` or the like. You should not import the module in the `caffe/python/caffe` directory!
 
-*Caffe's Python interface works with Python 2.7. Python 3 or earlier Pythons are your own adventure.*
+*Caffe's Python interface works with Python 2.7. Python 3.3+ should work out of the box without protobuf support. For protobuf support please install protobuf 3.0 alpha (https://developers.google.com/protocol-buffers/). Earlier Pythons are your own adventure.*
 
 #### MATLAB
 

examples/imagenet/readme.md

@@ -26,7 +26,7 @@ We assume that you already have downloaded the ImageNet training data and valida
 
 You will first need to prepare some auxiliary data for training. This data can be downloaded by:
 
-    ./data/get_ilsvrc_aux.sh
+    ./data/ilsvrc12/get_ilsvrc_aux.sh
 
 The training and validation input are described in `train.txt` and `val.txt` as text listing all the files and their labels. Note that we use a different indexing for labels than the ILSVRC devkit: we sort the synset names in their ASCII order, and then label them from 0 to 999. See `synset_words.txt` for the synset/name mapping.
 

include/caffe/blob.hpp

@@ -1,6 +1,10 @@
 #ifndef CAFFE_BLOB_HPP_
 #define CAFFE_BLOB_HPP_
 
+#include <algorithm>
+#include <string>
+#include <vector>
+
 #include "caffe/common.hpp"
 #include "caffe/proto/caffe.pb.h"
 #include "caffe/syncedmem.hpp"
@@ -19,10 +23,16 @@ template <typename Dtype>
 class Blob {
  public:
   Blob()
-       : data_(), diff_(), num_(0), channels_(0), height_(0), width_(0),
-       count_(0), capacity_(0) {}
+       : data_(), diff_(), count_(0), capacity_(0) {}
+
+  /// @brief Deprecated; use <code>Blob(const vector<int>& shape)</code>.
   explicit Blob(const int num, const int channels, const int height,
-    const int width);
+      const int width);
+  explicit Blob(const vector<int>& shape);
+
+  /// @brief Deprecated; use <code>Reshape(const vector<int>& shape)</code>.
+  void Reshape(const int num, const int channels, const int height,
+      const int width);
   /**
    * @brief Change the dimensions of the blob, allocating new memory if
    *        necessary.
@@ -37,25 +47,114 @@ class Blob {
    * an error; either Net::Forward or Net::Reshape need to be called to
    * propagate the new input shape to higher layers.
    */
-  void Reshape(const int num, const int channels, const int height,
-    const int width);
+  void Reshape(const vector<int>& shape);
+  void Reshape(const BlobShape& shape);
   void ReshapeLike(const Blob& other);
-  inline int num() const { return num_; }
-  inline int channels() const { return channels_; }
-  inline int height() const { return height_; }
-  inline int width() const { return width_; }
+  inline string shape_string() const {
+    ostringstream stream;
+    for (int i = 0; i < shape_.size(); ++i) {
+      stream << shape_[i] << " ";
+    }
+    stream << "(" << count_ << ")";
+    return stream.str();
+  }
+  inline const vector<int>& shape() const { return shape_; }
+  /**
+   * @brief Returns the dimension of the index-th axis (or the negative index-th
+   *        axis from the end, if index is negative).
+   *
+   * @param index the axis index.
+   *        If 0 <= index < num_axes(), return the dim of the index-th axis.
+   *        If -num_axes <= index <= -1, return the dim of the
+   *        (num_axes() - index)-th axis; e.g., the last axis if index == -1,
+   *        the second to last if index == -2, etc.
+   *        Dies on out of range index.
+   */
+  inline int shape(int index) const {
+    CHECK_GE(index, -num_axes());
+    CHECK_LT(index, num_axes());
+    if (index < 0) {
+      index += num_axes();
+    }
+    return shape_[index];
+  }
+  inline int num_axes() const { return shape_.size(); }
   inline int count() const { return count_; }
+  /**
+   * @brief Compute the count for a range of dimensions.
+   *
+   * @param start_axis The first axis to include in the count.
+   *
+   * @param end_axis The first axis to exclude from the count.
+   */
+  inline int count(int start_axis, int end_axis) const {
+    CHECK_LE(start_axis, end_axis);
+    CHECK_GE(start_axis, 0);
+    CHECK_GE(end_axis, 0);
+    CHECK_LE(start_axis, num_axes());
+    CHECK_LE(end_axis, num_axes());
+    int count = 1;
+    for (int i = start_axis; i < end_axis; ++i) {
+      count *= shape(i);
+    }
+    return count;
+  }
+  /**
+   * @brief Compute the count from a specified starting dimension.
+   *
+   * @param start_axis The first axis to include in the count.
+   */
+  inline int count(int start_axis) const {
+    return count(start_axis, num_axes());
+  }
+
+  /// @brief Deprecated legacy shape accessor num: use shape(0) instead.
+  inline int num() const { return LegacyShape(0); }
+  /// @brief Deprecated legacy shape accessor channels: use shape(1) instead.
+  inline int channels() const { return LegacyShape(1); }
+  /// @brief Deprecated legacy shape accessor height: use shape(2) instead.
+  inline int height() const { return LegacyShape(2); }
+  /// @brief Deprecated legacy shape accessor width: use shape(3) instead.
+  inline int width() const { return LegacyShape(3); }
+  inline int LegacyShape(int index) const {
+    CHECK_LE(num_axes(), 4)
+        << "Cannot use legacy accessors on Blobs with > 4 axes.";
+    CHECK_LT(index, 4);
+    CHECK_GE(index, -4);
+    if (index >= num_axes() || index < -num_axes()) {
+      // Axis is out of range, but still in [0, 3] (or [-4, -1] for reverse
+      // indexing) -- this special case simulates the one-padding used to fill
+      // extraneous axes of legacy blobs.
+      return 1;
+    }
+    return shape(index);
+  }
+
   inline int offset(const int n, const int c = 0, const int h = 0,
       const int w = 0) const {
     CHECK_GE(n, 0);
-    CHECK_LE(n, num_);
-    CHECK_GE(channels_, 0);
-    CHECK_LE(c, channels_);
-    CHECK_GE(height_, 0);
-    CHECK_LE(h, height_);
-    CHECK_GE(width_, 0);
-    CHECK_LE(w, width_);
-    return ((n * channels_ + c) * height_ + h) * width_ + w;
+    CHECK_LE(n, num());
+    CHECK_GE(channels(), 0);
+    CHECK_LE(c, channels());
+    CHECK_GE(height(), 0);
+    CHECK_LE(h, height());
+    CHECK_GE(width(), 0);
+    CHECK_LE(w, width());
+    return ((n * channels() + c) * height() + h) * width() + w;
+  }
+
+  inline int offset(const vector<int>& indices) const {
+    CHECK_LE(indices.size(), num_axes());
+    int offset = 0;
+    for (int i = 0; i < num_axes(); ++i) {
+      offset *= shape(i);
+      if (indices.size() > i) {
+        CHECK_GE(indices[i], 0);
+        CHECK_LT(indices[i], shape(i));
+        offset += indices[i];
+      }
+    }
+    return offset;
   }
   /**
    * @brief Copy from a source Blob.
@@ -71,12 +170,20 @@ class Blob {
 
   inline Dtype data_at(const int n, const int c, const int h,
       const int w) const {
-    return *(cpu_data() + offset(n, c, h, w));
+    return cpu_data()[offset(n, c, h, w)];
   }
 
   inline Dtype diff_at(const int n, const int c, const int h,
       const int w) const {
-    return *(cpu_diff() + offset(n, c, h, w));
+    return cpu_diff()[offset(n, c, h, w)];
+  }
+
+  inline Dtype data_at(const vector<int>& index) const {
+    return cpu_data()[offset(index)];
+  }
+
+  inline Dtype diff_at(const vector<int>& index) const {
+    return cpu_diff()[offset(index)];
   }
 
   inline const shared_ptr<SyncedMemory>& data() const {
@@ -99,7 +206,7 @@ class Blob {
   Dtype* mutable_cpu_diff();
   Dtype* mutable_gpu_diff();
   void Update();
-  void FromProto(const BlobProto& proto);
+  void FromProto(const BlobProto& proto, bool reshape = true);
   void ToProto(BlobProto* proto, bool write_diff = false) const;
 
   /// @brief Compute the sum of absolute values (L1 norm) of the data.
@@ -135,13 +242,12 @@ class Blob {
    */
   void ShareDiff(const Blob& other);
 
+  bool ShapeEquals(const BlobProto& other);
+
  protected:
   shared_ptr<SyncedMemory> data_;
   shared_ptr<SyncedMemory> diff_;
-  int num_;
-  int channels_;
-  int height_;
-  int width_;
+  vector<int> shape_;
   int count_;
   int capacity_;