Python net specification

.gitignore

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

CMakeLists.txt

@@ -17,14 +17,16 @@ 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)
+caffe_option(BUILD_python_layer "Build the caffe python layer" ON)
 
 # ---[ 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

@@ -25,7 +25,7 @@ include(cmake/ProtoBuf.cmake)
 
 # ---[ HDF5
 find_package(HDF5 COMPONENTS HL REQUIRED)
-include_directories(SYSTEM ${HDF5_INCLUDE_DIRS})
+include_directories(SYSTEM ${HDF5_INCLUDE_DIRS} ${HDF5_HL_INCLUDE_DIR})
 list(APPEND Caffe_LINKER_LIBS ${HDF5_LIBRARIES})
 
 # ---[ LMDB
@@ -35,7 +35,7 @@ list(APPEND Caffe_LINKER_LIBS ${LMDB_LIBRARIES})
 
 # ---[ LevelDB
 find_package(LevelDB REQUIRED)
-include_directories(SYSTEM ${LEVELDB_INCLUDE})
+include_directories(SYSTEM ${LevelDB_INCLUDE})
 list(APPEND Caffe_LINKER_LIBS ${LevelDB_LIBRARIES})
 
 # ---[ Snappy
@@ -92,14 +92,46 @@ 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)
+    if(BUILD_python_layer)
+      add_definitions(-DWITH_PYTHON_LAYER)
+      include_directories(SYSTEM ${PYTHON_INCLUDE_DIRS} ${NUMPY_INCLUDE_DIR} ${Boost_INCLUDE_DIRS})
+      list(APPEND Caffe_LINKER_LIBS ${PYTHON_LIBRARIES} ${Boost_LIBRARIES})
+    endif()
   endif()
 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/install_osx.md

@@ -32,7 +32,7 @@ If using Anaconda Python, HDF5 is bundled and the `hdf5` formula can be skipped.
 
     # with Python pycaffe needs dependencies built from source
     brew install --build-from-source --with-python --fresh -vd protobuf
-    brew install --build-from-source --fresh -vd boost
+    brew install --build-from-source --fresh -vd boost boost-python
     # without Python the usual installation suffices
     brew install protobuf boost
 

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
 

docs/tutorial/layers.md

@@ -453,20 +453,20 @@ The `SLICE` layer is a utility layer that slices an input layer to multiple outp
 
 * Sample
 
-     layers {
-       name: "slicer_label"
-       type: SLICE
-       bottom: "label"
-       ## Example of label with a shape N x 3 x 1 x 1
-       top: "label1"
-       top: "label2"
-       top: "label3"
-       slice_param {
-           slice_dim: 1
-           slice_point: 1
-           slice_point: 2
-       }
-     }
+      layers {
+        name: "slicer_label"
+        type: SLICE
+        bottom: "label"
+        ## Example of label with a shape N x 3 x 1 x 1
+        top: "label1"
+        top: "label2"
+        top: "label3"
+        slice_param {
+            slice_dim: 1
+            slice_point: 1
+            slice_point: 2
+        }
+      }
 
 `slice_dim` indicates the target dimension and can assume only two values: 0 for num or 1 for channel; `slice_point` indicates indexes in the selected dimension (the number of indexes must be equal to the number of top blobs minus one). 
 

examples/classification.ipynb

@@ -4,7 +4,7 @@
   "example_name": "ImageNet classification",
   "include_in_docs": true,
   "priority": 1,
-  "signature": "sha256:918b797b1b7d78125c8f1e3c84756b0679120cbe1071ce7fee7aeafef0fbae55"
+  "signature": "sha256:a2b12abaa1eb252f436d59833c08ab97948c8a7a0513197f31afad0a0690e318"
  },
  "nbformat": 3,
  "nbformat_minor": 0,
@@ -18,9 +18,9 @@
       "Classifying ImageNet: the instant Caffe way\n",
       "===========================================\n",
       "\n",
-      "Caffe provides a general Python interface for models with `caffe.Net` in `python/caffe/pycaffe.py`, but to make off-the-shelf classification easy we provide a `caffe.Classifier` class and `classify.py` script. Both Python and MATLAB wrappers are provided. However, the Python wrapper has more features so we will describe it here. For MATLAB, refer to `matlab/caffe/matcaffe_demo.m`.\n",
+      "Caffe has a Python interface, pycaffe, with a `caffe.Net` interface for models. There are both Python and MATLAB interfaces. While this example uses the off-the-shelf Python `caffe.Classifier` interface there is also a MATLAB example at `matlab/caffe/matcaffe_demo.m`.\n",
       "\n",
-      "Before we begin, you must compile Caffe and install the python wrapper by setting your `PYTHONPATH`. If you haven't yet done so, please refer to the [installation instructions](installation.html). This example uses our pre-trained CaffeNet model, an ILSVRC12 image classifier. You can download it by running `./scripts/download_model_binary.py models/bvlc_reference_caffenet`.\n",
+      "Before we begin, you must compile Caffe. You should add the Caffe module to your `PYTHONPATH` although this example includes it automatically. If you haven't yet done so, please refer to the [installation instructions](http://caffe.berkeleyvision.org/installation.html). This example uses our pre-trained CaffeNet model, an ILSVRC12 image classifier. You can download it by running `./scripts/download_model_binary.py models/bvlc_reference_caffenet` or let the first step of this example download it for you.\n",
       "\n",
       "Ready? Let's start."
      ]
@@ -44,7 +44,12 @@
       "# and the image you would like to classify.\n",
       "MODEL_FILE = '../models/bvlc_reference_caffenet/deploy.prototxt'\n",
       "PRETRAINED = '../models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel'\n",
-      "IMAGE_FILE = 'images/cat.jpg'"
+      "IMAGE_FILE = 'images/cat.jpg'\n",
+      "\n",
+      "import os\n",
+      "if not os.path.isfile(PRETRAINED):\n",
+      "    print(\"Downloading pre-trained CaffeNet model...\")\n",
+      "    !../scripts/download_model_binary.py ../models/bvlc_reference_caffenet"
      ],
      "language": "python",
      "metadata": {},