Merge conflicts

.gitignore

@@ -19,3 +19,9 @@ third_party/
 
 # clion workspace.
 cmake-build-*
+
+# generated while compiling
+python/paddle/v2/framework/core.so
+CMakeFiles
+cmake_install.cmake
+

.travis.yml

@@ -4,6 +4,7 @@ cache:
     - $HOME/.ccache
     - $HOME/.cache/pip
     - $TRAVIS_BUILD_DIR/build/third_party
+    - $TRAVIS_BUILD_DIR/build_android/third_party
 sudo: required
 dist: trusty
 os:
@@ -11,6 +12,7 @@ os:
 env:
   - JOB=build_doc
   - JOB=check_style
+  - JOB=build_android
 addons:
   apt:
     packages:

CMakeLists.txt

@@ -28,7 +28,9 @@ if(NOT CMAKE_CROSSCOMPILING)
 endif(NOT CMAKE_CROSSCOMPILING)
 find_package(Git REQUIRED)
 find_package(Threads REQUIRED)
-find_package(Boost QUIET)
+if(NOT ANDROID)
+    find_package(Boost QUIET)
+endif()
 
 include(simd)
 
@@ -97,6 +99,7 @@ include(external/swig)      # download, build, install swig
 include(external/warpctc)   # download, build, install warpctc
 include(external/any)       # download libn::any
 include(external/eigen)     # download eigen3
+include(external/pybind11)    # download pybind11
 
 include(cudnn)              # set cudnn libraries, must before configure
 include(configure)          # add paddle env configuration
@@ -139,6 +142,10 @@ endif(USE_NNPACK)
 
 add_subdirectory(proto)
 
+# "add_subdirectory(go)" should be placed after the following loine,
+# because it depends on paddle/optimizer.
+add_subdirectory(paddle/optimizer)
+
 # "add_subdirectory(paddle)" and "add_subdirectory(python)" should be
 # placed after this block, because they depends on it.
 if(WITH_GOLANG)
@@ -146,7 +153,9 @@ if(WITH_GOLANG)
 endif(WITH_GOLANG)
 
 add_subdirectory(paddle)
-add_subdirectory(python)
+if(WITH_PYTHON)
+  add_subdirectory(python)
+endif()
 if(WITH_DOC)
     add_subdirectory(doc)
 endif()

cmake/cross_compiling/android.cmake

@@ -106,6 +106,9 @@ IF("${CMAKE_VERSION}" VERSION_LESS "3.7.0")
                 SET(CMAKE_SYSTEM_PROCESSOR armv7-a)
             ENDIF()
         ENDIF()
+        IF(ANDROID_ABI STREQUAL "arm64-v8a")
+            SET(ANDROID_TOOLCHAIN_NAME aarch64-linux-android)
+        ENDIF()
         SET(ANDROID_TOOLCHAIN_PREFIX "${ANDROID_TOOLCHAIN_ROOT}/bin/${ANDROID_TOOLCHAIN_NAME}-")
     ENDIF()
 
@@ -162,6 +165,10 @@ IF("${CMAKE_VERSION}" VERSION_LESS "3.7.0")
         ENDIF()
     ENDIF()
 
+    IF(ANDROID_ABI STREQUAL "arm64-v8a")
+      LIST(APPEND ANDROID_COMPILER_FLAGS -march=armv8-a)
+    ENDIF()
+
     STRING(REPLACE ";" " " ANDROID_COMPILER_FLAGS "${ANDROID_COMPILER_FLAGS}")
     STRING(REPLACE ";" " " ANDROID_LINKER_FLAGS "${ANDROID_LINKER_FLAGS}")
 

cmake/external/glog.cmake

@@ -52,6 +52,7 @@ ExternalProject_Add(
 
 ADD_LIBRARY(glog STATIC IMPORTED GLOBAL)
 SET_PROPERTY(TARGET glog PROPERTY IMPORTED_LOCATION ${GLOG_LIBRARIES})
-ADD_DEPENDENCIES(glog extern_glog)
+ADD_DEPENDENCIES(glog extern_glog gflags)
+LINK_LIBRARIES(glog gflags)
 
 LIST(APPEND external_project_dependencies glog)

cmake/external/openblas.cmake

@@ -32,7 +32,12 @@ IF(NOT ${CBLAS_FOUND})
             # arm_soft_fp_abi branch of OpenBLAS to support softfp
             #   https://github.com/xianyi/OpenBLAS/tree/arm_soft_fp_abi
             SET(OPENBLAS_COMMIT "b5c96fcfcdc82945502a2303116a64d89985daf5")
-            SET(OPTIONAL_ARGS HOSTCC=${HOST_C_COMPILER} TARGET=ARMV7 ARM_SOFTFP_ABI=1 USE_THREAD=0)
+            IF(ANDROID_ABI MATCHES "^armeabi(-v7a)?$")
+                SET(TARGET "ARMV7")
+            ELSEIF(ANDROID_ABI STREQUAL "arm64-v8a")
+                SET(TARGET "ARMV8")
+            ENDIF()
+            SET(OPTIONAL_ARGS HOSTCC=${HOST_C_COMPILER} TARGET=${TARGET} ARM_SOFTFP_ABI=1 USE_THREAD=0)
         ELSEIF(RPI)
             # use hardfp
             SET(OPENBLAS_COMMIT "v0.2.19")

cmake/external/pybind11.cmake

+INCLUDE(ExternalProject)
+
+SET(PYBIND_SOURCE_DIR ${THIRD_PARTY_PATH}/pybind)
+
+INCLUDE_DIRECTORIES(${PYBIND_SOURCE_DIR}/src/extern_pybind/include)
+
+ExternalProject_Add(
+        extern_pybind
+        ${EXTERNAL_PROJECT_LOG_ARGS}
+        GIT_REPOSITORY  "https://github.com/pybind/pybind11.git"
+        GIT_TAG         "v2.1.1"
+        PREFIX          ${PYBIND_SOURCE_DIR}
+        UPDATE_COMMAND  ""
+        CONFIGURE_COMMAND ""
+        BUILD_COMMAND     ""
+        INSTALL_COMMAND   ""
+        TEST_COMMAND      ""
+)
+
+if (${CMAKE_VERSION} VERSION_LESS "3.3.0")
+    set(dummyfile ${CMAKE_CURRENT_BINARY_DIR}/pybind_dummy.c)
+    file(WRITE ${dummyfile} "const char * dummy_any = \"${dummyfile}\";")
+    add_library(pybind STATIC ${dummyfile})
+else()
+    add_library(pybind INTERFACE)
+endif()
+
+add_dependencies(pybind extern_pybind)
+
+LIST(APPEND external_project_dependencies pybind)

cmake/external/python.cmake

@@ -18,6 +18,9 @@ INCLUDE(python_module)
 FIND_PACKAGE(PythonInterp 2.7)
 IF(WITH_PYTHON)
     FIND_PACKAGE(PythonLibs 2.7)
+    # Fixme: Maybe find a static library. Get SHARED/STATIC by FIND_PACKAGE.
+    ADD_LIBRARY(python SHARED IMPORTED GLOBAL)
+    SET_PROPERTY(TARGET python PROPERTY IMPORTED_LOCATION ${PYTHON_LIBRARIES})
 ENDIF(WITH_PYTHON)
 
 SET(py_env "")

cmake/flags.cmake

@@ -109,7 +109,9 @@ set(COMMON_FLAGS
     -Wno-unused-function
     -Wno-error=literal-suffix
     -Wno-error=sign-compare
-    -Wno-error=unused-local-typedefs)
+    -Wno-error=unused-local-typedefs
+    -Wno-error=parentheses-equality # Warnings in Pybind11
+)
 
 set(GPU_COMMON_FLAGS
     -fPIC

cmake/generic.cmake

@@ -90,11 +90,11 @@
 # including binary directory for generated headers.
 include_directories(${CMAKE_CURRENT_BINARY_DIR})
 
-if(NOT APPLE)
+if(NOT APPLE AND NOT ANDROID)
     find_package(Threads REQUIRED)
     link_libraries(${CMAKE_THREAD_LIBS_INIT})
-    set(CMAKE_CXX_LINK_EXECUTABLE "${CMAKE_CXX_LINK_EXECUTABLE} -ldl")
-endif(NOT APPLE)
+    set(CMAKE_CXX_LINK_EXECUTABLE "${CMAKE_CXX_LINK_EXECUTABLE} -ldl -lrt")
+endif(NOT APPLE AND NOT ANDROID)
 
 function(merge_static_libs TARGET_NAME)
   set(libs ${ARGN})
@@ -302,7 +302,7 @@ function(go_library TARGET_NAME)
 
   file(GLOB GO_SOURCE RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "*.go")
   string(REPLACE "${PADDLE_GO_PATH}/" "" CMAKE_CURRENT_SOURCE_REL_DIR ${CMAKE_CURRENT_SOURCE_DIR})
-  # FIXME: link path
+
   add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
     COMMAND rm "${${TARGET_NAME}_LIB_PATH}"
     # Golang build source code
@@ -310,7 +310,7 @@ function(go_library TARGET_NAME)
     -o "${${TARGET_NAME}_LIB_PATH}"
     "./${CMAKE_CURRENT_SOURCE_REL_DIR}/${GO_SOURCE}"
     # must run under GOPATH
-  WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go")
+    WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go")
   add_dependencies(${TARGET_NAME} go_vendor)
 endfunction(go_library)
 
@@ -321,14 +321,11 @@ function(go_binary TARGET_NAME)
   cmake_parse_arguments(go_binary "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
   string(REPLACE "${PADDLE_GO_PATH}/" "" CMAKE_CURRENT_SOURCE_REL_DIR ${CMAKE_CURRENT_SOURCE_DIR})
 
-  # FIXME: link path
   add_custom_command(OUTPUT ${TARGET_NAME}_timestamp
-      COMMAND env LIBRARY_PATH=${CMAKE_BINARY_DIR}/go/pserver/client/c/:$ENV{LIBRARY_PATH}
-      GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build
+    COMMAND env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build
     -o "${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME}"
     "./${CMAKE_CURRENT_SOURCE_REL_DIR}/${go_binary_SRCS}"
     WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go")
-  # TODO: don't know what ${TARGET_NAME}_link does
   add_custom_target(${TARGET_NAME} ALL DEPENDS go_vendor ${TARGET_NAME}_timestamp ${go_binary_DEPS})
   install(PROGRAMS ${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME} DESTINATION bin)
 endfunction(go_binary)
@@ -336,15 +333,18 @@ endfunction(go_binary)
 function(go_test TARGET_NAME)
   set(options OPTIONAL)
   set(oneValueArgs "")
-  set(multiValueArgs SRCS DEPS)
+  set(multiValueArgs DEPS)
   cmake_parse_arguments(go_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
-  add_custom_command(OUTPUT ${TARGET_NAME}_timestamp
+  string(REPLACE "${PADDLE_GO_PATH}" "" CMAKE_CURRENT_SOURCE_REL_DIR ${CMAKE_CURRENT_SOURCE_DIR})
+  add_custom_target(${TARGET_NAME} ALL DEPENDS go_vendor ${go_test_DEPS})
+  add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
     COMMAND env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} test
     -c -o "${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME}"
-    ${go_test_SRCS}
+    ".${CMAKE_CURRENT_SOURCE_REL_DIR}"
+    WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go")
+  add_test(NAME ${TARGET_NAME}
+    COMMAND ${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME}
     WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
-  add_custom_target(${TARGET_NAME} ALL DEPENDS ${TARGET_NAME}_timestamp ${go_test_DEPS})
-  add_test(${TARGET_NAME} ${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME})
 endfunction(go_test)
 
 function(proto_library TARGET_NAME)

doc/howto/dev/new_layer_cn.rst

@@ -37,7 +37,7 @@
 
    \frac{\partial c(y)}{\partial x} = \frac{\partial c(y)}{\partial y} \frac{\partial y}{\partial x}
 
-假设 :math:`z = f(W^T x + b)` ，那么
+假设 :math:`z = W^T x + b` ，那么
 
 .. math::
 

doc/howto/dev/new_layer_en.rst

@@ -29,7 +29,7 @@ Fully connected layer takes a dense input vector with dimension :math:`D_i`. It
 
 where :math:`f(.)` is an nonlinear *activation* function, such as sigmoid, tanh, and Relu.
 
-The transformation matrix :math:`W` and bias vector :math:`b` are the *parameters* of the layer. The *parameters* of a layer are learned during training in the *backward pass*. The backward pass computes the gradients of the output function with respect to all parameters and inputs. The optimizer can use chain rule to compute the gradients of the loss function with respect to each parameter. 
+The transformation matrix :math:`W` and bias vector :math:`b` are the *parameters* of the layer. The *parameters* of a layer are learned during training in the *backward pass*. The backward pass computes the gradients of the output function with respect to all parameters and inputs. The optimizer can use chain rule to compute the gradients of the loss function with respect to each parameter.
 
 Suppose our loss function is :math:`c(y)`, then
 
@@ -37,7 +37,7 @@ Suppose our loss function is :math:`c(y)`, then
 
    \frac{\partial c(y)}{\partial x} = \frac{\partial c(y)}{\partial y} \frac{\partial y}{\partial x}
 
-Suppose :math:`z = f(W^T x + b)`, then
+Suppose :math:`z = W^T x + b`, then
 
 .. math::
 
@@ -48,7 +48,7 @@ This derivative can be automatically computed by our base layer class.
 Then, for fully connected layer, we need to compute:
 
 .. math::
-  
+
    \frac{\partial z}{\partial x} = W, \frac{\partial z_j}{\partial W_{ij}} = x_i, \frac{\partial z}{\partial b} = \mathbf 1
 
 where :math:`\mathbf 1` is an all one vector, :math:`W_{ij}` is the number at the i-th row and j-th column of the matrix :math:`W`, :math:`z_j` is the j-th component of the vector :math:`z`, and :math:`x_i` is the i-th component of the vector :math:`x`.
@@ -322,7 +322,7 @@ All the gradient check unit tests are located in :code:`paddle/gserver/tests/tes
                       /* weight */ true);
       }
     }
-    
+
 If you are creating a new file for the test, such as :code:`paddle/gserver/tests/testFCGrad.cpp`, you need to add the file to :code:`paddle/gserver/tests/CMakeLists.txt`. An example is given below. All the unit tests will run when you execute the command :code:`make tests`. Notice that some layers might need high accuracy for the gradient check unit tests to work well. You need to configure :code:`WITH_DOUBLE` to `ON` when configuring cmake.
 
 .. code-block:: bash

go/CMakeLists.txt

@@ -17,3 +17,7 @@ add_subdirectory(pserver/client/c)
 add_subdirectory(cmd/pserver)
 add_subdirectory(cmd/master)
 add_subdirectory(master/c)
+add_subdirectory(master)
+add_subdirectory(pserver)
+add_subdirectory(pserver/client)
+add_subdirectory(utils/networkhelper)

go/cmd/master/CMakeLists.txt

@@ -12,4 +12,4 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-go_binary(master SRC master.go DEPS paddle_go_optimizer)
+go_binary(master SRC master.go)

go/cmd/pserver/pserver.go

@@ -8,6 +8,7 @@ import (
 	"time"
 
 	"github.com/namsral/flag"
+	"github.com/topicai/candy"
 
 	"github.com/PaddlePaddle/Paddle/go/pserver"
 	log "github.com/sirupsen/logrus"
@@ -18,53 +19,47 @@ func main() {
 	index := flag.Int("index", -1, "index of this pserver, should be larger or equal than 0")
 	etcdEndpoint := flag.String("etcd-endpoint", "http://127.0.0.1:2379",
 		"comma separated endpoint string for pserver to connect to etcd")
-	etcdTimeout := flag.Int("etcd-timeout", 5, "timeout for etcd calls")
+	etcdTimeout := flag.Duration("etcd-timeout", 5*time.Second, "timeout for etcd calls")
 	numPservers := flag.Int("num-pservers", 1, "total pserver count in a training job")
 	checkpointPath := flag.String("checkpoint-path", "/checkpoints/", "save checkpoint path")
-	checkpointInterval := flag.Int("checkpoint-interval", 600, "save checkpoint per interval seconds")
+	checkpointInterval := flag.Duration("checkpoint-interval", 600*time.Second, "save checkpoint per interval seconds")
 	logLevel := flag.String("log-level", "info",
 		"log level, possible values: debug, info, warning, error, fatal, panic")
 	flag.Parse()
 
 	level, err := log.ParseLevel(*logLevel)
-	if err != nil {
-		panic(err)
-	}
+	candy.Must(err)
+
 	log.SetLevel(level)
 
 	var idx int
+
 	var cp pserver.Checkpoint
 	var e *pserver.EtcdClient
 	if *index >= 0 {
 		idx = *index
 	} else {
-		timeout := time.Second * time.Duration((*etcdTimeout))
-		e = pserver.NewEtcdClient(*etcdEndpoint, *numPservers, timeout)
+		e = pserver.NewEtcdClient(*etcdEndpoint, *numPservers, *etcdTimeout)
 		idx, err = e.Register()
+		candy.Must(err)
+
+		cp, err = pserver.NewCheckpointFromFile(*checkpointPath, idx, e)
 		if err != nil {
-			panic(err)
+			log.Errorf("Fetch checkpoint failed, %s", err)
 		}
 	}
 
 	s, err := pserver.NewService(idx, *checkpointInterval, *checkpointPath, e, cp)
-	if err != nil {
-		panic(err)
-	}
+	candy.Must(err)
+
 	err = rpc.Register(s)
-	if err != nil {
-		panic(err)
-	}
+	candy.Must(err)
 
 	rpc.HandleHTTP()
 	l, err := net.Listen("tcp", ":"+strconv.Itoa(*port))
-	if err != nil {
-		panic(err)
-	}
+	candy.Must(err)
 
 	log.Infof("start pserver at port %d", *port)
 	err = http.Serve(l, nil)
-
-	if err != nil {
-		panic(err)
-	}
+	candy.Must(err)
 }

go/glide.lock

-hash: b8f18ce6784bd3fadd9fed0b8443e7b658234ea785ae1f220723ae2c1f652aa7
-updated: 2017-06-27T14:05:48.925262819+08:00
+hash: a8faea3a363468a88917ddeb3b1c9ea36886fb2c622acbad42604fa9cb4d3855
+updated: 2017-07-11T10:04:40.786745417+08:00
 imports:
 - name: github.com/coreos/etcd
-  version: 61fc123e7a8b14a0a258aa3f5c4159861b1ec2e7
+  version: cb2a496c4ddd1c87a9f280e116649b599999ec79
   subpackages:
   - auth/authpb
   - clientv3
@@ -22,7 +22,9 @@ imports:
 - name: github.com/PaddlePaddle/recordio
   version: edfb82af0739c84f241c87390ec5649c7b28c129
 - name: github.com/sirupsen/logrus
-  version: 202f25545ea4cf9b191ff7f846df5d87c9382c2b
+  version: 7f976d3a76720c4c27af2ba716b85d2e0a7e38b1
+- name: github.com/topicai/candy
+  version: 1b9030d056fa9f8c4b1f9c91b52fe4b8ab4cd8cc
 - name: golang.org/x/net
   version: c8c74377599bd978aee1cf3b9b63a8634051cec2
   subpackages:
@@ -34,11 +36,11 @@ imports:
   - lex/httplex
   - trace
 - name: golang.org/x/sys
-  version: f7928cfef4d09d1b080aa2b6fd3ca9ba1567c733
+  version: abf9c25f54453410d0c6668e519582a9e1115027
   subpackages:
   - unix
 - name: golang.org/x/text
-  version: 4e9ab9ee170f2a39bd66c92b3e0a47ff47a4bc77
+  version: cfdf022e86b4ecfb646e1efbd7db175dd623a8fa
   subpackages:
   - secure/bidirule
   - transform

go/glide.yaml

@@ -10,3 +10,4 @@ import:
   version: ^1.7.4-pre
 - package: github.com/sirupsen/logrus
   version: ^1.0.0
+- package: github.com/topicai/candy

go/master/CMakeLists.txt

+if(WITH_TESTING)
+  go_test(master_test)
+endif()

go/master/client.go

@@ -68,7 +68,7 @@ func (c *Client) getRecords() {
 		// We treat a task as finished whenever the last data
 		// instance of the task is read. This is not exactly
 		// correct, but a reasonable approximation.
-		c.taskFinished(t.ID)
+		c.taskFinished(t.Meta.ID)
 	}
 }
 
@@ -118,6 +118,11 @@ func (c *Client) taskFinished(taskID int) error {
 	return c.conn.Call("Service.TaskFinished", taskID, nil)
 }
 
+// TaskFailed tell the master server as task is failed.
+func (c *Client) taskFailed(meta TaskMeta) error {
+	return c.conn.Call("Service.TaskFailed", meta, nil)
+}
+
 // NextRecord returns next record in the dataset.
 //
 // NextRecord will block until the next record is available. It is

go/master/client_internal_test.go

@@ -95,10 +95,16 @@ func TestGetFinishTask(t *testing.T) {
 			t.Fatalf("Should get error, pass: %d\n", i)
 		}
 
-		err = c.taskFinished(tasks[0].ID)
+		err = c.taskFinished(tasks[0].Meta.ID)
 		if err != nil {
 			t.Fatalf("Error: %v, pass: %d\n", err, i)
 		}
+
+		err = c.taskFailed(tasks[0].Meta)
+		if err != nil {
+			t.Fatalf("Error: %v, pass: %d\n", err, i)
+		}
+
 		tasks = tasks[1:]
 		task, err := c.getTask()
 		if err != nil {
@@ -107,7 +113,7 @@ func TestGetFinishTask(t *testing.T) {
 		tasks = append(tasks, task)
 
 		for _, task := range tasks {
-			err = c.taskFinished(task.ID)
+			err = c.taskFinished(task.Meta.ID)
 			if err != nil {
 				t.Fatalf("Error: %v, pass: %d\n", err, i)
 			}

go/master/service.go

@@ -31,30 +31,36 @@ type Chunk struct {
 	Index recordio.Index // chunk index
 }
 
+// TaskMeta is a struct which stores task's meta info.
+type TaskMeta struct {
+	ID    int
+	Epoch int
+}
+
 // Task is the basic unit of data instances assigned to trainers.
 type Task struct {
-	ID     int
+	Meta   TaskMeta
 	Chunks []Chunk
 }
 
 type taskEntry struct {
-	Epoch      int
-	NumTimeout int
-	Task       Task
+	Task Task
+	// A task fails if it's timeout or trainer reports it exits unnormally.
+	NumFailure int
 }
 
 type taskQueues struct {
 	Todo    []taskEntry
 	Pending map[int]taskEntry // map from task ID to task entry
 	Done    []taskEntry
-	Failed  []Task
+	Failed  []taskEntry
 }
 
 // Service is the master server service.
 type Service struct {
 	chunksPerTask int
 	timeoutDur    time.Duration
-	timeoutMax    int
+	failureMax    int
 	ready         chan struct{}
 	store         Store
 
@@ -73,7 +79,7 @@ func partition(chunks []Chunk, chunksPerTask int) []taskEntry {
 	var cur taskEntry
 	for i, c := range chunks {
 		if i%chunksPerTask == 0 && len(cur.Task.Chunks) > 0 {
-			cur.Task.ID = id
+			cur.Task.Meta.ID = id
 			id++
 			result = append(result, cur)
 			cur.Task.Chunks = nil
@@ -83,7 +89,7 @@ func partition(chunks []Chunk, chunksPerTask int) []taskEntry {
 	}
 
 	if len(cur.Task.Chunks) > 0 {
-		cur.Task.ID = id
+		cur.Task.Meta.ID = id
 		result = append(result, cur)
 	}
 
@@ -91,11 +97,11 @@ func partition(chunks []Chunk, chunksPerTask int) []taskEntry {
 }
 
 // NewService creates a new service.
-func NewService(store Store, chunksPerTask int, timeoutDur time.Duration, timeoutMax int) (*Service, error) {
+func NewService(store Store, chunksPerTask int, timeoutDur time.Duration, failureMax int) (*Service, error) {
 	s := &Service{}
 	s.chunksPerTask = chunksPerTask
 	s.timeoutDur = timeoutDur
-	s.timeoutMax = timeoutMax
+	s.failureMax = failureMax
 	s.taskQueues = taskQueues{}
 	s.taskQueues.Pending = make(map[int]taskEntry)
 	s.ready = make(chan struct{})
@@ -257,6 +263,34 @@ func (s *Service) SetDataset(globPaths []string, dummy *int) error {
 	return nil
 }
 
+func (s *Service) processFailedTask(t taskEntry, epoch int) {
+	if t.Task.Meta.Epoch != epoch {
+		// new epoch, task launched after the
+		// schedule of this timeout check or failed status report.
+		return
+	}
+
+	defer func() {
+		err := s.snapshot()
+		if err != nil {
+			log.Errorln(err)
+		}
+	}()
+
+	delete(s.taskQueues.Pending, t.Task.Meta.ID)
+
+	t.NumFailure++
+	if t.NumFailure > s.failureMax {
+		log.Warningf("Task %v failed %d times, discard.", t.Task, t.NumFailure)
+		s.taskQueues.Failed = append(s.taskQueues.Failed, t)
+		return
+	}
+
+	log.Warningf("Task %v failed %d times, discard.", t.Task, t.NumFailure)
+	s.taskQueues.Todo = append(s.taskQueues.Todo, t)
+	return
+}
+
 func (s *Service) checkTimeoutFunc(taskID int, epoch int) func() {
 	return func() {
 		s.mu.Lock()
@@ -267,30 +301,7 @@ func (s *Service) checkTimeoutFunc(taskID int, epoch int) func() {
 			return
 		}
 
-		if t.Epoch != epoch {
-			// new epoch, task launched after the
-			// schedule of this timeout check.
-			return
-		}
-
-		defer func() {
-			err := s.snapshot()
-			if err != nil {
-				log.Errorln(err)
-			}
-		}()
-
-		delete(s.taskQueues.Pending, t.Task.ID)
-
-		t.NumTimeout++
-		if t.NumTimeout > s.timeoutMax {
-			log.Warningf("Task %v timed out %d times, discard.", t.Task, t.NumTimeout)
-			s.taskQueues.Failed = append(s.taskQueues.Failed, t.Task)
-			return
-		}
-
-		log.Warningf("Task %v timed out %d times, retry.", t.Task, t.NumTimeout)
-		s.taskQueues.Todo = append(s.taskQueues.Todo, t)
+		s.processFailedTask(t, epoch)
 	}
 }
 
@@ -339,18 +350,18 @@ func (s *Service) GetTask(dummy int, task *Task) error {
 	}
 
 	t := s.taskQueues.Todo[0]
-	t.Epoch++
+	t.Task.Meta.Epoch++
 	s.taskQueues.Todo = s.taskQueues.Todo[1:]
-	s.taskQueues.Pending[t.Task.ID] = t
+	s.taskQueues.Pending[t.Task.Meta.ID] = t
 	err := s.snapshot()
 	if err != nil {
 		return err
 	}
 
 	*task = t.Task
-	log.WithFields(s.logFields()).Infof("Task #%d dispatched.", task.ID)
+	log.WithFields(s.logFields()).Infof("Task #%v dispatched.", t.Task.Meta)
 
-	time.AfterFunc(s.timeoutDur, s.checkTimeoutFunc(t.Task.ID, t.Epoch))
+	time.AfterFunc(s.timeoutDur, s.checkTimeoutFunc(t.Task.Meta.ID, t.Task.Meta.Epoch))
 	return nil
 }
 
@@ -365,13 +376,12 @@ func (s *Service) TaskFinished(taskID int, dummy *int) error {
 
 	t, ok := s.taskQueues.Pending[taskID]
 	if !ok {
-		err := errors.New("pending task not found")
 		log.WithFields(s.logFields()).Warningln("Pending task #%d not found.", taskID)
-		return err
+		return nil
 	}
 
 	// task finished, reset timeout
-	t.NumTimeout = 0
+	t.NumFailure = 0
 	s.taskQueues.Done = append(s.taskQueues.Done, t)
 	delete(s.taskQueues.Pending, taskID)
 
@@ -389,3 +399,22 @@ func (s *Service) TaskFinished(taskID int, dummy *int) error {
 	}
 	return err
 }
+
+// TaskFailed tells the service that a task is failed.
+func (s *Service) TaskFailed(meta TaskMeta, dummy *int) error {
+	select {
+	case <-s.ready:
+	}
+
+	s.mu.Lock()
+	defer s.mu.Unlock()
+
+	t, ok := s.taskQueues.Pending[meta.ID]
+	if !ok {
+		log.WithFields(s.logFields()).Warningln("TaskFailed:Pending task #%v not found.", t.Task.Meta)
+		return nil
+	}
+
+	s.processFailedTask(t, meta.Epoch)
+	return nil
+}

go/master/service_internal_test.go

@@ -30,7 +30,7 @@ func TestPartionIndex(t *testing.T) {
 	cs := make([]Chunk, 100)
 	ts := partition(cs, 20)
 	for i := range ts {
-		if ts[i].Task.ID != i {
+		if ts[i].Task.Meta.ID != i {
 			t.Error(ts[i], i)
 		}
 	}

go/pserver/CMakeLists.txt

+if(WITH_TESTING)
+  go_test(pserver_test DEPS paddle_go_optimizer)
+endif()

go/pserver/client/CMakeLists.txt

+if(WITH_TESTING)
+  go_test(pserver_client_test DEPS paddle_go_optimizer)
+endif()

go/pserver/client/c/.gitignore

+libpaddle_go_optimizer.a

go/pserver/client/c/CMakeLists.txt

 cc_library(paddle_go_optimizer DEPS paddle_optimizer paddle_proto glog gflags protobuf)
 target_link_libraries(paddle_go_optimizer stdc++ m)
+
+# Copy library to the required place.
+# See: go/pserver/optimizer.go:
+# // #cgo LDFLAGS: ${SRCDIR}/client/c/libpaddle_go_optimizer.a -lstdc++ -lm
+add_custom_command(TARGET paddle_go_optimizer POST_BUILD
+  COMMAND cp "${CMAKE_CURRENT_BINARY_DIR}/libpaddle_go_optimizer.a" "${CMAKE_CURRENT_SOURCE_DIR}"
+  )
+
 go_library(paddle_pserver_cclient STATIC DEPS paddle_go_optimizer)
 if(WITH_TESTING)
   # FIXME: this test requires pserver which is not managed by the test

go/pserver/client/c/test/test_train.py

@@ -19,7 +19,7 @@ def main():
     # create parameters
     parameters = paddle.parameters.create(cost)
 
-    # create optimizer
+    # create optimizer of new remote updater to pserver
     optimizer = paddle.optimizer.Momentum(momentum=0)
 
     #TODO(zhihong) : replace optimizer with new OptimizerConfig

go/pserver/client/client_test.go

@@ -3,11 +3,13 @@ package client_test
 import (
 	"context"
 	"io/ioutil"
+	"math/rand"
 	"net"
 	"net/http"
 	"net/rpc"
 	"strconv"
 	"strings"
+	"sync"
 	"testing"
 	"time"
 
@@ -42,7 +44,8 @@ func initClient() [numPserver]int {
 		ports[i] = p
 
 		go func(l net.Listener) {
-			s, err := pserver.NewService(0)
+			var cp pserver.Checkpoint
+			s, err := pserver.NewService(0, 1, "", nil, cp)
 			if err != nil {
 				panic(err)
 			}
@@ -99,27 +102,34 @@ func (l lister) List() []client.Server {
 	return l
 }
 
-func ClientTest(t *testing.T, c *client.Client) {
+func testClient(t *testing.T, c *client.Client) {
 	selected := c.BeginInitParams()
 	if !selected {
 		t.Fatal("should be selected.")
 	}
 
-	const numParameter = 100
+	const numParameter = 1000
 	config, err := ioutil.ReadFile("./c/test/testdata/optimizer.pb")
 	if err != nil {
 		t.Fatalf("read optimizer proto failed")
 	}
+
+	var wg sync.WaitGroup
 	for i := 0; i < numParameter; i++ {
-		var p pserver.Parameter
-		p.Name = "p_" + strconv.Itoa(i)
-		p.ElementType = pserver.Float32
-		p.Content = make([]byte, (i+1)*100)
-		err := c.InitParam(pserver.ParameterWithConfig{Param: p, Config: config})
-		if err != nil {
-			t.Fatal(err)
-		}
+		wg.Add(1)
+		go func(i int) {
+			var p pserver.Parameter
+			p.Name = "p_" + strconv.Itoa(i)
+			p.ElementType = pserver.Float32
+			p.Content = make([]byte, (i+1)*100)
+			err := c.InitParam(pserver.ParameterWithConfig{Param: p, Config: config})
+			if err != nil {
+				t.Fatal(err)
+			}
+			wg.Done()
+		}(i)
 	}
+	wg.Wait()
 
 	err = c.FinishInitParams()
 	if err != nil {
@@ -127,7 +137,7 @@ func ClientTest(t *testing.T, c *client.Client) {
 	}
 
 	var grads []pserver.Gradient
-	for i := 0; i < numParameter/2; i++ {
+	for i := 0; i < numParameter; i++ {
 		var g pserver.Gradient
 		g.Name = "p_" + strconv.Itoa(i)
 		g.ElementType = pserver.Float32
@@ -135,9 +145,31 @@ func ClientTest(t *testing.T, c *client.Client) {
 		grads = append(grads, g)
 	}
 
-	err = c.SendGrads(grads)
-	if err != nil {
-		t.Fatal(err)
+	const paramPerGroup = 10
+	const numGroups = numParameter / paramPerGroup
+
+	// shuffle send grads order
+	for i := range grads {
+		j := rand.Intn(i + 1)
+		grads[i], grads[j] = grads[j], grads[i]
+	}
+
+	for i := 0; i < numGroups; i++ {
+		var gs []pserver.Gradient
+		if i == numGroups-1 {
+			gs = grads[i*paramPerGroup:]
+		} else {
+			gs = grads[i*paramPerGroup : (i+1)*paramPerGroup]
+		}
+
+		wg.Add(1)
+		go func(gs []pserver.Gradient) {
+			err = c.SendGrads(gs)
+			if err != nil {
+				t.Fatal(err)
+			}
+			wg.Done()
+		}(gs)
 	}
 
 	names := make([]string, numParameter)
@@ -145,20 +177,35 @@ func ClientTest(t *testing.T, c *client.Client) {
 		names[i] = "p_" + strconv.Itoa(i)
 	}
 
-	params, err := c.GetParams(names)
-	if err != nil {
-		t.Fatal(err)
-	}
+	for i := 0; i < numGroups; i++ {
+		var ns []string
+		if i == numGroups-1 {
+			ns = names[i*paramPerGroup:]
+		} else {
+			ns = names[i*paramPerGroup : (i+1)*paramPerGroup]
+		}
 
-	if len(names) != len(params) {
-		t.Fatalf("parameter size not match, need: %d, have: %d", len(names), len(params))
-	}
+		wg.Add(1)
+		go func(ns []string) {
+			params, err := c.GetParams(ns)
+			if err != nil {
+				t.Fatal(err)
+			}
 
-	for i := range params {
-		if names[i] != params[i].Name {
-			t.Fatalf("order of returned parameter does not required: parameter name: %s, required name: %s", names[i], params[i].Name)
-		}
+			if len(ns) != len(params) {
+				t.Fatalf("parameter size not match, need: %d, have: %d", len(names), len(params))
+			}
+
+			for i := range params {
+				if ns[i] != params[i].Name {
+					t.Fatalf("order of returned parameter does not required: parameter name: %s, required name: %s", ns[i], params[i].Name)
+				}
+			}
+			wg.Done()
+		}(ns)
 	}
+
+	wg.Wait()
 }
 
 func TestNativeClient(t *testing.T) {
@@ -168,13 +215,14 @@ func TestNativeClient(t *testing.T) {
 		servers[i] = client.Server{Index: i, Addr: ":" + strconv.Itoa(pserverClientPorts[i])}
 	}
 	c1 := client.NewClient(lister(servers), len(servers), selector(true))
-	ClientTest(t, c1)
+	testClient(t, c1)
 }
 
-// TODO: tmperary disable etcdClient test for dependency of etcd)
+// EtcdClient is a disabled test, since we have not embedded etcd into
+// our test.
 func EtcdClient(t *testing.T) {
 	initEtcdClient()
-	etcd_client := client.NewEtcd(etcdEndpoints)
-	c2 := client.NewClient(etcd_client, etcd_client.Desired(), selector(true))
-	ClientTest(t, c2)
+	etcdClient := client.NewEtcd(etcdEndpoints)
+	c2 := client.NewClient(etcdClient, etcdClient.Desired(), selector(true))
+	testClient(t, c2)
 }

go/pserver/etcd_client.go

@@ -16,7 +16,7 @@ import (
 const (
 	// PsDesired is etcd path for store desired pserver count
 	PsDesired = "/ps_desired"
-	// PsAddr is the base dir for pserver to store their addr
+	// PsPath is the base dir for pserver to store their addr
 	PsPath = "/ps/"
 	// PsCheckpoint is the etcd path for store checkpoints information
 	PsCheckpoint = "/checkpoints/"
@@ -189,9 +189,25 @@ func (e *EtcdClient) registerPserverEtcd(ctx context.Context) (int, error) {
 	return idx, nil
 }
 
+// GetKey gets the value by the specified key
+func (e *EtcdClient) GetKey(key string, timeout time.Duration) ([]byte, error) {
+	ctx, cancel := context.WithTimeout(context.Background(), timeout)
+	resp, err := e.etcdClient.Get(ctx, key)
+	cancel()
+	if err != nil {
+		return []byte{}, err
+	}
+	kvs := resp.Kvs
+	if len(kvs) == 0 {
+		return []byte{}, nil
+	}
+	v := kvs[0].Value
+	return v, nil
+}
+
 // PutKey put into etcd with value by key specified
-func (e *EtcdClient) PutKey(key string, value []byte, timeout int) error {
-	ctx, cancel := context.WithTimeout(context.Background(), time.Second*time.Duration(timeout))
+func (e *EtcdClient) PutKey(key string, value []byte, timeout time.Duration) error {
+	ctx, cancel := context.WithTimeout(context.Background(), timeout)
 	_, err := e.etcdClient.Put(ctx, key, string(value))
 	cancel()
 	if err != nil {

go/pserver/optimizer.go

 package pserver
 
 // #cgo CFLAGS: -I ../../
-// //FIXME: ldflags contain "build" path
-// #cgo LDFLAGS: ${SRCDIR}/../../build/go/pserver/client/c/libpaddle_go_optimizer.a -lstdc++ -lm
+// #cgo LDFLAGS: ${SRCDIR}/client/c/libpaddle_go_optimizer.a -lstdc++ -lm
 // #include "paddle/optimizer/optimizer.h"
 // #include <stdlib.h>
 // #include <string.h>
@@ -20,6 +19,7 @@ var nullPtr = unsafe.Pointer(uintptr(0))
 type optimizer struct {
 	opt         *C.struct_paddle_optimizer
 	elementType ElementType
+	contentLen  int
 }
 
 func cArrayToSlice(p unsafe.Pointer, len int) []byte {
@@ -38,25 +38,28 @@ func cArrayToSlice(p unsafe.Pointer, len int) []byte {
 func newOptimizer(paramWithConfigs ParameterWithConfig, State []byte) *optimizer {
 	o := &optimizer{}
 	o.elementType = paramWithConfigs.Param.ElementType
+	o.contentLen = len(paramWithConfigs.Param.Content)
 	p := paramWithConfigs.Param
 	c := paramWithConfigs.Config
 	s := State
+	paramBufferSize := C.size_t(len(p.Content))
 	log.WithFields(log.Fields{
 		"ElementType": p.ElementType,
-		"ParamSize":   len(p.Content),
+		"ParamSize":   paramBufferSize,
 		"ConfigSize":  len(c),
 		"StateSize":   len(s),
 	}).Info("New Optimizer Created with config:")
 	var cbuffer unsafe.Pointer
-	cbuffer = C.malloc(C.size_t(len(p.Content)))
-	C.memcpy(cbuffer, unsafe.Pointer(&p.Content[0]), C.size_t(len(p.Content)))
+	cbuffer = C.malloc(paramBufferSize)
+
+	C.memcpy(cbuffer, unsafe.Pointer(&p.Content[0]), paramBufferSize)
 	var cstate unsafe.Pointer
 	if len(s) != 0 {
 		cstate = unsafe.Pointer(&s[0])
 	}
 
 	o.opt = C.paddle_create_optimizer((*C.uchar)(&c[0]), C.int(len(c)),
-		C.paddle_element_type(p.ElementType), cbuffer, C.int(len(p.Content)/C.sizeof_float), (*C.char)(cstate), C.int(len(s)))
+		C.paddle_element_type(p.ElementType), cbuffer, C.int(paramBufferSize), (*C.char)(cstate), C.int(len(s)))
 	return o
 }
 
@@ -68,8 +71,8 @@ func (o *optimizer) GetWeights() []byte {
 
 func (o *optimizer) GetStates() []byte {
 	var cbuffer *C.char
-	cbuffer_len := C.paddle_optimizer_get_state(o.opt, &cbuffer)
-	return cArrayToSlice(unsafe.Pointer(cbuffer), int(cbuffer_len))
+	cbufferLen := C.paddle_optimizer_get_state(o.opt, &cbuffer)
+	return cArrayToSlice(unsafe.Pointer(cbuffer), int(cbufferLen))
 }
 
 func (o *optimizer) UpdateParameter(g Gradient) error {
@@ -77,7 +80,11 @@ func (o *optimizer) UpdateParameter(g Gradient) error {
 		return fmt.Errorf("Name: %s, parameter and gradient element type not match, parameter: %v, gradient: %v", g.Name, o.elementType, g.ElementType)
 	}
 
-	r := C.paddle_update_parameter(o.opt, C.paddle_element_type(g.ElementType), unsafe.Pointer(&g.Content[0]), C.int(len(g.Content))/C.sizeof_float)
+	if o.contentLen != len(g.Content) {
+		return fmt.Errorf("Name: %s, parameter and gradient does not have same content len, parameter: %d, gradient: %d", g.Name, o.contentLen, len(g.Content))
+	}
+
+	r := C.paddle_update_parameter(o.opt, C.paddle_element_type(g.ElementType), unsafe.Pointer(&g.Content[0]), C.int(len(g.Content)))
 	if r != 0 {
 		return fmt.Errorf("optimizer update returned error code: %d", r)
 	}

go/pserver/service.go

@@ -9,6 +9,7 @@ import (
 	"encoding/json"
 	"errors"
 	"fmt"
+	"io/ioutil"
 	"os"
 	"path/filepath"
 	"strconv"
@@ -21,14 +22,14 @@ import (
 // ElementType is the type of elements of a Parameter.
 type ElementType int
 
+// RPC error message.
 const (
-	// AlreadyInitialized is true if pserver is initialized
-	AlreadyInitialized = "pserver already initialized"
-	// Uninitialized is true if pserver not fully initialized
-	Uninitialized = "pserver not fully initialized"
+	AlreadyInitialized  = "pserver already initialized"
+	Uninitialized       = "pserver not fully initialized"
+	CheckpointMD5Failed = "checkpoint file MD5 validation failed"
 )
 
-// Supported element types
+// Supported element types.
 const (
 	Int32 ElementType = iota
 	UInt32
@@ -51,21 +52,15 @@ type ParameterWithConfig struct {
 	Config []byte // parameter configuration in Proto Buffer format
 }
 
-// ParameterCheckpoint is Parameter and State checkpoint
-type ParameterCheckpoint struct {
-	ParamConfig ParameterWithConfig
-	State       []byte
-}
-
-// checkpoint signature
+// checkpointMeta saves checkpoint metadata
 type checkpointMeta struct {
 	UUID      string `json:"uuid"`
-	Md5sum    string `json:"md5sum"`
-	Timestamp string `json:"timestamp"`
+	MD5       string `json:"md5"`
+	Timestamp int64  `json:"timestamp"`
 }
 
 // Checkpoint is the pserver shard persist in file
-type Checkpoint []ParameterCheckpoint
+type Checkpoint []parameterCheckpoint
 
 // Gradient is the gradient of the parameter.
 type Gradient Parameter
@@ -81,12 +76,53 @@ type Service struct {
 	optMap             map[string]*optimizer
 }
 
+// parameterCheckpoint saves parameter checkpoint
+type parameterCheckpoint struct {
+	ParameterWithConfig
+	State []byte
+}
+
+// NewCheckpointFromFile loads parameters and state from checkpoint file
+func NewCheckpointFromFile(cpPath string, idx int, e *EtcdClient) (Checkpoint, error) {
+	v, err := e.GetKey(PsPath+string(idx), 3*time.Second)
+	if err != nil {
+		return nil, err
+	}
+
+	var cpMeta checkpointMeta
+	if err = json.Unmarshal(v, &cpMeta); err != nil {
+		return nil, err
+	}
+
+	fn := filepath.Join(cpPath, cpMeta.UUID)
+	if _, err = os.Stat(fn); os.IsNotExist(err) {
+		return nil, err
+	}
+	content, err := ioutil.ReadFile(fn)
+	if err != nil {
+		return nil, err
+	}
+
+	h := md5.New()
+	md5 := hex.EncodeToString(h.Sum(content))
+	if md5 != cpMeta.MD5 {
+		return nil, errors.New(CheckpointMD5Failed)
+	}
+
+	dec := gob.NewDecoder(bytes.NewReader(content))
+	cp := Checkpoint{}
+	if err = dec.Decode(cp); err != nil {
+		return nil, err
+	}
+	return cp, nil
+}
+
 // NewService creates a new service, will bypass etcd registration if no
-// endpoints specified.
-func NewService(idx int, seconds int, path string, client *EtcdClient, cp Checkpoint) (*Service, error) {
+// endpoints specified. It will recovery from checkpoint file if a exists a specified checkpoint.
+func NewService(idx int, interval time.Duration, path string, client *EtcdClient, cp Checkpoint) (*Service, error) {
 	s := &Service{
 		idx:                idx,
-		checkpointInterval: time.Second * time.Duration(seconds),
+		checkpointInterval: interval,
 		checkpointPath:     path,
 		client:             client,
 	}
@@ -95,9 +131,11 @@ func NewService(idx int, seconds int, path string, client *EtcdClient, cp Checkp
 
 	if cp != nil {
 		for _, item := range cp {
-			p := item.ParamConfig
-			st := item.State
-			s.optMap[p.Param.Name] = newOptimizer(p, st)
+			p := ParameterWithConfig{
+				Param:  item.Param,
+				Config: item.Config,
+			}
+			s.optMap[p.Param.Name] = newOptimizer(p, item.State)
 		}
 	}
 	return s, nil
@@ -186,13 +224,13 @@ func (s *Service) doCheckpoint() error {
 	s.mu.Lock()
 	defer s.mu.Unlock()
 
-	cp := make([]ParameterCheckpoint, 0, len(s.optMap))
+	cp := make([]parameterCheckpoint, len(s.optMap))
 	index := 0
 	for name, opt := range s.optMap {
-		var pc ParameterCheckpoint
-		pc.ParamConfig.Param.Name = name
-		pc.ParamConfig.Param.ElementType = opt.elementType
-		pc.ParamConfig.Param.Content = opt.GetWeights()
+		var pc parameterCheckpoint
+		pc.Param.Name = name
+		pc.Param.ElementType = opt.elementType
+		pc.Param.Content = opt.GetWeights()
 		pc.State = opt.GetStates()
 		cp[index] = pc
 		index++
@@ -206,12 +244,12 @@ func (s *Service) doCheckpoint() error {
 
 	cpMeta := checkpointMeta{}
 	cpMeta.UUID = s.checkpointPath + strconv.Itoa(s.idx)
-	cpMeta.Timestamp = time.Now().String()
+	cpMeta.Timestamp = time.Now().UnixNano()
 	h := md5.New()
-	cpMeta.Md5sum = hex.EncodeToString(h.Sum(buf.Bytes()))
+	cpMeta.MD5 = hex.EncodeToString(h.Sum(buf.Bytes()))
 
 	cpMetajson, _ := json.Marshal(cpMeta)
-	err = s.client.PutKey(filepath.Join(PsCheckpoint, strconv.Itoa(s.idx)), cpMetajson, 3)
+	err = s.client.PutKey(filepath.Join(PsCheckpoint, strconv.Itoa(s.idx)), cpMetajson, 3*time.Second)
 	if err != nil {
 		return err
 	}
@@ -219,7 +257,11 @@ func (s *Service) doCheckpoint() error {
 		log.Info("checkpoint does not exists.")
 	} else {
 		err = os.Remove(cpMeta.UUID)
-		log.Infof("checkpoint %s already exsits, removing ", cpMeta.UUID)
+		if err != nil {
+			log.Infof("Removing checkpoint %s failed", cpMeta.UUID)
+		} else {
+			log.Infof("checkpoint %s already exsits, removing ", cpMeta.UUID)
+		}
 	}
 	f, err := os.Create(cpMeta.UUID)
 	defer f.Close()

go/pserver/service_test.go

@@ -31,7 +31,7 @@ func TestServiceFull(t *testing.T) {
 
 	err = s.InitParam(pserver.ParameterWithConfig{Param: p, Config: config}, nil)
 	if err != nil {
-		t.FailNow()
+		t.Fatal(err)
 	}
 
 	var p1 pserver.Parameter
@@ -40,40 +40,40 @@ func TestServiceFull(t *testing.T) {
 	p1.ElementType = pserver.Float32
 	err = s.InitParam(pserver.ParameterWithConfig{Param: p1, Config: config}, nil)
 	if err != nil {
-		t.FailNow()
+		t.Fatal(err)
 	}
 
 	err = s.FinishInitParams(0, nil)
 	if err != nil {
-		t.FailNow()
+		t.Fatal(err)
 	}
 
 	var param pserver.Parameter
 	err = s.GetParam("param_b", &param)
 	if err != nil {
-		t.FailNow()
+		t.Fatal(err)
 	}
 
 	if !reflect.DeepEqual(param, p1) {
-		t.FailNow()
+		t.Fatal("not equal:", param, p1)
 	}
 
 	g1, g2 := pserver.Gradient(p1), pserver.Gradient(p)
 
 	err = s.SendGrad(g1, nil)
 	if err != nil {
-		t.FailNow()
+		t.Fatal(err)
 	}
 	err = s.SendGrad(g2, nil)
 
 	if err != nil {
-		t.FailNow()
+		t.Fatal(err)
 	}
 
 	var param1 pserver.Parameter
 	err = s.GetParam("param_a", &param1)
 	if err != nil {
-		t.FailNow()
+		t.Fatal(err)
 	}
 
 	// don't compare content, since it's already changed by
@@ -82,7 +82,7 @@ func TestServiceFull(t *testing.T) {
 	p.Content = nil
 
 	if !reflect.DeepEqual(param1, p) {
-		t.FailNow()
+		t.Fatal("not equal:", param1, p)
 	}
 }
 
@@ -90,16 +90,16 @@ func TestMultipleInit(t *testing.T) {
 	var cp pserver.Checkpoint
 	s, err := pserver.NewService(0, 1, "", nil, cp)
 	if err != nil {
-		t.Error(err)
+		t.Fatal(err)
 	}
 	err = s.FinishInitParams(0, nil)
 	if err != nil {
-		t.FailNow()
+		t.Fatal(err)
 	}
 
 	err = s.FinishInitParams(0, nil)
 	if err.Error() != pserver.AlreadyInitialized {
-		t.FailNow()
+		t.Fatal(err)
 	}
 }
 
@@ -108,7 +108,7 @@ func TestUninitialized(t *testing.T) {
 	s, err := pserver.NewService(0, 1, "", nil, cp)
 	err = s.SendGrad(pserver.Gradient{}, nil)
 	if err.Error() != pserver.Uninitialized {
-		t.FailNow()
+		t.Fatal(err)
 	}
 }
 
@@ -154,12 +154,12 @@ func TestBlockUntilInitialized(t *testing.T) {
 	err = s.InitParam(pserver.ParameterWithConfig{Param: p, Config: config}, nil)
 
 	if err != nil {
-		t.FailNow()
+		t.Fatal(err)
 	}
 
 	err = s.FinishInitParams(0, nil)
 	if err != nil {
-		t.FailNow()
+		t.Fatal(err)
 	}
 
 	wg.Wait()

go/utils/networkhelper/CMakeLists.txt

+if(WITH_TESTING)
+  go_test(network_helper_test)
+endif()

paddle/CMakeLists.txt

@@ -8,13 +8,14 @@ add_subdirectory(gserver)
 add_subdirectory(pserver)
 add_subdirectory(trainer)
 add_subdirectory(scripts)
-add_subdirectory(optimizer)
 add_subdirectory(string)
 
 if(Boost_FOUND)
   add_subdirectory(memory)
   add_subdirectory(platform)
   add_subdirectory(framework)
+  add_subdirectory(operators)
+  add_subdirectory(pybind)
 endif()
 
 if(WITH_C_API)

paddle/framework/CMakeLists.txt

@@ -11,7 +11,10 @@ proto_library(op_proto SRCS op_proto.proto DEPS attr_type)
 cc_test(op_proto_test SRCS op_proto_test.cc DEPS op_proto protobuf)
 proto_library(op_desc SRCS op_desc.proto DEPS attr_type)
 cc_test(op_desc_test SRCS op_desc_test.cc DEPS op_desc protobuf)
-cc_test(op_registry_test SRCS op_registry_test.cc DEPS op_proto op_desc)
+cc_library(operator SRCS operator.cc DEPS op_desc device_context)
+cc_test(operator_test SRCS operator_test.cc DEPS operator op_registry)
+cc_library(op_registry SRCS op_registry.cc DEPS op_proto op_desc)
+cc_test(op_registry_test SRCS op_registry_test.cc DEPS op_registry operator)
 py_proto_compile(framework_py_proto SRCS attr_type.proto op_proto.proto op_desc.proto)
 # Generate an empty __init__.py to make framework_py_proto as a valid python module.
 add_custom_target(framework_py_proto_init ALL COMMAND ${CMAKE_COMMAND} -E touch __init__.py)

paddle/framework/dim.h

@@ -266,29 +266,6 @@ HOSTDEVICE inline bool contained(const Dim<1>& idx, const Dim<1>& size) {
   return ((0 <= idx.head) && (idx.head < size.head));
 }
 
-/**
- * \brief Check if a size and a stride create a Fortran order contiguous
- * block of memory.
- */
-template <int i>
-HOST bool contiguous(const Dim<i>& size, const Dim<i>& stride, int mul = 1) {
-  if (product(size) == 0) return true;
-  int contiguous_stride = get<0>(size) == 1 ? 0 : mul;
-  return (get<0>(stride) == contiguous_stride &&
-          contiguous(size.tail, stride.tail, mul * get<0>(size)));
-}
-
-///\cond HIDDEN
-// Base case of contiguous, check the nth stride is the size of
-// the prefix multiply of n-1 dims.
-template <>
-inline bool contiguous(const Dim<1>& size, const Dim<1>& stride, int mul) {
-  if (get<0>(size) == 0) return true;
-  int contiguous_stride = get<0>(size) == 1 ? 0 : mul;
-  return get<0>(stride) == contiguous_stride;
-}
-///\endcond
-
 /**
  * \brief Compute exclusive prefix-multiply of a Dim.
  */
@@ -306,31 +283,6 @@ HOSTDEVICE inline Dim<1> ex_prefix_mul(const Dim<1>& src, int mul) {
 }
 ///\endcond
 
-/**
- * \brief Calculate strides of a contiguous array of the given size
- *
- * Sets the stride for any dimension with an extent of 1 to 0.
- * \param size Dim object containing the size of the array.
- * \param base The base stride to use.
- * \return Dim object the same size as \p size with the strides.
- */
-template <int i>
-HOSTDEVICE Dim<i> contiguous_strides(const Dim<i>& size, int base = 1) {
-  int stride = size.head == 1 ? 0 : base;
-  return Dim<i>(stride, contiguous_strides(size.tail, base * size.head));
-}
-
-///\cond HIDDEN
-
-// Base case of contiguous_strides
-template <>
-HOSTDEVICE inline Dim<1> contiguous_strides(const Dim<1>& size, int base) {
-  int stride = size.head == 1 ? 0 : base;
-  return Dim<1>(stride);
-}
-
-///\endcond
-
 /**
  * Add two dimensions together
  */

paddle/framework/dim_test.cu

@@ -58,24 +58,6 @@ TEST(Dim, Equality) {
     EXPECT_EQ(paddle::framework::get<1>(c), 3);
     EXPECT_EQ(paddle::framework::get<2>(c), 12);
 
-    // contiguous_strides
-    c = paddle::framework::contiguous_strides(paddle::framework::Dim<3>(10, 1, 10));
-    EXPECT_EQ(paddle::framework::get<0>(c), 1);
-    EXPECT_EQ(paddle::framework::get<1>(c), 0);
-    EXPECT_EQ(paddle::framework::get<2>(c), 10);
-    c = paddle::framework::contiguous_strides(paddle::framework::Dim<3>(10, 10, 1));
-    EXPECT_EQ(paddle::framework::get<0>(c), 1);
-    EXPECT_EQ(paddle::framework::get<1>(c), 10);
-    EXPECT_EQ(paddle::framework::get<2>(c), 0);
-    c = paddle::framework::contiguous_strides(paddle::framework::Dim<3>(1, 10, 10));
-    EXPECT_EQ(paddle::framework::get<0>(c), 0);
-    EXPECT_EQ(paddle::framework::get<1>(c), 1);
-    EXPECT_EQ(paddle::framework::get<2>(c), 10);
-    c = paddle::framework::contiguous_strides(paddle::framework::Dim<3>(2, 3, 4));
-    EXPECT_EQ(paddle::framework::get<0>(c), 1);
-    EXPECT_EQ(paddle::framework::get<1>(c), 2);
-    EXPECT_EQ(paddle::framework::get<2>(c), 6);
-
     // generate from an index
     auto size = paddle::framework::make_dim(4, 5, 2);
     c = paddle::framework::Dim<3>(14, size);
@@ -101,16 +83,6 @@ TEST(Dim, Bool) {
     EXPECT_TRUE(a == a);
     EXPECT_FALSE(a == b);
     EXPECT_TRUE(a == c);
-
-    // contiguous check
-    int x = 4, y = 5, z = 2;
-    paddle::framework::Dim<3> sizef(x, y, z);
-    paddle::framework::Dim<3> stridea(1, x, x*y);
-    paddle::framework::Dim<3> strideb(2, 2*x, 2*x*y);
-    paddle::framework::Dim<3> stridec(1, x, 2*x*y);
-    EXPECT_TRUE(paddle::framework::contiguous(sizef, stridea));
-    EXPECT_FALSE(paddle::framework::contiguous(sizef, strideb));
-    EXPECT_FALSE(paddle::framework::contiguous(sizef, stridec));
 }
 
 TEST(Dim, Print) {

paddle/framework/op_registry.cc

+#include <paddle/framework/op_registry.h>
+
+namespace paddle {
+namespace framework {
+
+template <>
+void AttrTypeHelper::SetAttrType<int>(AttrProto* attr) {
+  attr->set_type(paddle::framework::AttrType::INT);
+}
+
+template <>
+void AttrTypeHelper::SetAttrType<float>(AttrProto* attr) {
+  attr->set_type(paddle::framework::AttrType::FLOAT);
+}
+
+template <>
+void AttrTypeHelper::SetAttrType<std::string>(AttrProto* attr) {
+  attr->set_type(paddle::framework::AttrType::STRING);
+}
+
+template <>
+void AttrTypeHelper::SetAttrType<std::vector<int>>(AttrProto* attr) {
+  attr->set_type(paddle::framework::AttrType::INTS);
+}
+
+template <>
+void AttrTypeHelper::SetAttrType<std::vector<float>>(AttrProto* attr) {
+  attr->set_type(paddle::framework::AttrType::FLOATS);
+}
+
+template <>
+void AttrTypeHelper::SetAttrType<std::vector<std::string>>(AttrProto* attr) {
+  attr->set_type(paddle::framework::AttrType::STRINGS);
+}
+}  // namespace framework
+}  // namespace paddle
\ No newline at end of file

paddle/framework/op_registry.h

 #pragma once
 
+#include <algorithm>
+#include <type_traits>
 #include "paddle/framework/attr_checker.h"
-
-//#include "paddle/framework/op_base.h"
 #include "paddle/framework/op_desc.pb.h"
 #include "paddle/framework/op_proto.pb.h"
+#include "paddle/framework/operator.h"
 
 namespace paddle {
 namespace framework {
 
-//==================For test================//
-class OpBase {
- public:
-  std::vector<std::string> inputs_;
-  std::vector<std::string> outputs_;
-  AttributeMap attr_map_;
-
-  virtual std::string Run() const = 0;
-  virtual ~OpBase() {}
-};
-//=========================================//
-
 // helper class to set attribute type
 struct AttrTypeHelper {
   template <typename T>
@@ -64,36 +53,6 @@ struct AttrTypeHelper {
   }
 };
 
-template <>
-void AttrTypeHelper::SetAttrType<int>(AttrProto* attr) {
-  attr->set_type(paddle::framework::AttrType::INT);
-}
-
-template <>
-void AttrTypeHelper::SetAttrType<float>(AttrProto* attr) {
-  attr->set_type(paddle::framework::AttrType::FLOAT);
-}
-
-template <>
-void AttrTypeHelper::SetAttrType<std::string>(AttrProto* attr) {
-  attr->set_type(paddle::framework::AttrType::STRING);
-}
-
-template <>
-void AttrTypeHelper::SetAttrType<std::vector<int>>(AttrProto* attr) {
-  attr->set_type(paddle::framework::AttrType::INTS);
-}
-
-template <>
-void AttrTypeHelper::SetAttrType<std::vector<float>>(AttrProto* attr) {
-  attr->set_type(paddle::framework::AttrType::FLOATS);
-}
-
-template <>
-void AttrTypeHelper::SetAttrType<std::vector<std::string>>(AttrProto* attr) {
-  attr->set_type(paddle::framework::AttrType::STRINGS);
-}
-
 // this class not only make proto but also init attribute checkers.
 class OpProtoAndCheckerMaker {
  public:
@@ -103,28 +62,26 @@ class OpProtoAndCheckerMaker {
  protected:
   void AddInput(const std::string& name, const std::string& comment) {
     auto input = proto_->mutable_inputs()->Add();
-    *(input->mutable_name()) = name;
-    *(input->mutable_comment()) = comment;
+    *input->mutable_name() = name;
+    *input->mutable_comment() = comment;
   }
 
   void AddOutput(const std::string& name, const std::string& comment) {
     auto output = proto_->mutable_outputs()->Add();
-    *(output->mutable_name()) = name;
-    *(output->mutable_comment()) = comment;
+    *output->mutable_name() = name;
+    *output->mutable_comment() = comment;
   }
 
   template <typename T>
   TypedAttrChecker<T>& AddAttr(const std::string& name,
                                const std::string& comment) {
     auto attr = proto_->mutable_attrs()->Add();
-    *(attr->mutable_name()) = name;
-    *(attr->mutable_comment()) = comment;
+    *attr->mutable_name() = name;
+    *attr->mutable_comment() = comment;
     AttrTypeHelper::SetAttrType<T>(attr);
     return op_checker_->AddAttrChecker<T>(name);
   }
 
-  void AddType(const std::string& op_type) { proto_->set_type(op_type); }
-
   void AddComment(const std::string& comment) {
     *(proto_->mutable_comment()) = comment;
   }
@@ -134,120 +91,127 @@ class OpProtoAndCheckerMaker {
 };
 
 class OpRegistry {
-  typedef std::function<OpBase*()> OpCreator;
+  using OpCreator = std::function<OperatorBase*()>;
 
  public:
   template <typename OpType, typename ProtoMakerType>
   static void RegisterOp(const std::string& op_type) {
-    creators_[op_type] = []() { return new OpType; };
-    OpProto& op_proto = protos_[op_type];
-    OpAttrChecker& op_checker = op_checkers_[op_type];
+    creators()[op_type] = [] { return new OpType; };
+    OpProto& op_proto = protos()[op_type];
+    OpAttrChecker& op_checker = op_checkers()[op_type];
     ProtoMakerType(&op_proto, &op_checker);
-    PADDLE_ENFORCE(op_proto.IsInitialized() == true,
-                   "Fail to initialize %s's OpProto !", op_type);
+    *op_proto.mutable_type() = op_type;
+    PADDLE_ENFORCE(
+        op_proto.IsInitialized(),
+        "Fail to initialize %s's OpProto, because %s is not initialized",
+        op_type, op_proto.InitializationErrorString());
   }
 
-  static OpBase* CreateOp(const OpDesc& op_desc) {
+  static OperatorBase* CreateOp(const OpDesc& op_desc) {
     std::string op_type = op_desc.type();
-    OpBase* op = (creators_.at(op_type))();
-    (op->inputs_).resize(op_desc.inputs_size());
-    for (int i = 0; i < op_desc.inputs_size(); ++i) {
-      (op->inputs_)[i] = op_desc.inputs(i);
-    }
-    (op->outputs_).resize(op_desc.outputs_size());
-    for (int i = 0; i < op_desc.outputs_size(); ++i) {
-      (op->outputs_)[i] = op_desc.outputs(i);
+    OperatorBase* op = creators().at(op_type)();
+    op->desc_ = op_desc;
+    op->inputs_.reserve((size_t)op_desc.inputs_size());
+    std::copy(op_desc.inputs().begin(), op_desc.inputs().end(),
+              std::back_inserter(op->inputs_));
+    op->outputs_.reserve((size_t)op_desc.outputs_size());
+    std::copy(op_desc.outputs().begin(), op_desc.outputs().end(),
+              std::back_inserter(op->outputs_));
+    for (auto& attr : op_desc.attrs()) {
+      op->attrs_[attr.name()] = AttrTypeHelper::GetAttrValue(attr);
     }
-    for (int i = 0; i < op_desc.attrs_size(); ++i) {
-      const AttrDesc& ith_attr = op_desc.attrs(i);
-      std::string name = ith_attr.name();
-      (op->attr_map_)[name] = AttrTypeHelper::GetAttrValue(ith_attr);
-    }
-    const OpAttrChecker& op_checker = op_checkers_.at(op_type);
-    op_checker.Check(op->attr_map_);
+    op_checkers().at(op_type).Check(op->attrs_);
+    op->Init();
     return op;
   }
 
  private:
-  static std::unordered_map<std::string, OpCreator> creators_;
-  static std::unordered_map<std::string, OpProto> protos_;
-  static std::unordered_map<std::string, OpAttrChecker> op_checkers_;
-};
-
-std::unordered_map<std::string, std::function<OpBase*()>> OpRegistry::creators_;
-std::unordered_map<std::string, OpProto> OpRegistry::protos_;
-std::unordered_map<std::string, OpAttrChecker> OpRegistry::op_checkers_;
-
-template <typename OpType, typename ProtoMakerType>
-class OpRegisterHelper {
- public:
-  OpRegisterHelper(std::string op_type) {
-    OpRegistry::RegisterOp<OpType, ProtoMakerType>(op_type);
-  }
-};
-
-#define REGISTER_OP(__op_class, __op_maker_class, __op_type)         \
-  class __op_class##Register {                                       \
-   private:                                                          \
-    const static OpRegisterHelper<__op_class, __op_maker_class> reg; \
-  };                                                                 \
-  const OpRegisterHelper<__op_class, __op_maker_class>               \
-      __op_class##Register::reg(#__op_type);
-
-// Demos
-
-class CosineOp : public OpBase {
- public:
-  virtual std::string Run() const {
-    std::string msg = "CosineOp runs! scale = " +
-                      std::to_string(boost::get<float>(attr_map_.at("scale")));
-    return msg;
-  }
-};
-
-class CosineOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
- public:
-  CosineOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
-    AddInput("input", "input of cosine op");
-    AddOutput("output", "output of cosine op");
-    AddAttr<float>("scale", "scale of cosine op")
-        .SetDefault(1.0)
-        .LargerThan(0.0);
-    AddType("cos");
-    AddComment("This is cos op");
+  static std::unordered_map<std::string, OpCreator>& creators() {
+    static std::unordered_map<std::string, OpCreator> creators_;
+    return creators_;
   }
-};
 
-REGISTER_OP(CosineOp, CosineOpProtoAndCheckerMaker, cos_sim)
+  static std::unordered_map<std::string, OpProto>& protos() {
+    static std::unordered_map<std::string, OpProto> protos_;
+    return protos_;
+  };
 
-class MyTestOp : public OpBase {
- public:
-  virtual std::string Run() const {
-    std::string msg =
-        "MyTestOp runs! test_attr = " +
-        std::to_string(boost::get<int>(attr_map_.at("test_attr")));
-    return msg;
-  }
+  static std::unordered_map<std::string, OpAttrChecker>& op_checkers() {
+    static std::unordered_map<std::string, OpAttrChecker> op_checkers_;
+    return op_checkers_;
+  };
 };
 
-class MyTestOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
+template <typename OpType, typename ProtoMakerType>
+class OpRegisterHelper {
  public:
-  MyTestOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
-    AddInput("input", "input of cosine op");
-    AddOutput("output", "output of cosine op");
-    auto my_checker = [](int i) {
-      PADDLE_ENFORCE(i % 2 == 0, "'test_attr' must be even!");
-    };
-    AddAttr<int>("test_attr", "a simple test attribute")
-        .AddCustomChecker(my_checker);
-    AddType("my_test_op");
-    AddComment("This is my_test op");
+  OpRegisterHelper(const char* op_type) {
+    OpRegistry::RegisterOp<OpType, ProtoMakerType>(op_type);
   }
 };
 
-REGISTER_OP(MyTestOp, MyTestOpProtoAndCheckerMaker, my_test_op)
+#define STATIC_ASSERT_GLOBAL_NAMESPACE(uniq_name, msg)                        \
+  struct __test_global_namespace_##uniq_name##__ {};                          \
+  static_assert(std::is_same<::__test_global_namespace_##uniq_name##__,       \
+                             __test_global_namespace_##uniq_name##__>::value, \
+                msg)
+
+#define REGISTER_OP(__op_type, __op_class, __op_maker_class)                 \
+  STATIC_ASSERT_GLOBAL_NAMESPACE(__reg_op__##__op_type,                      \
+                                 "REGISTER_OP must be in global namespace"); \
+  static ::paddle::framework::OpRegisterHelper<__op_class, __op_maker_class> \
+      __op_register_##__op_type##__(#__op_type);                             \
+  int __op_register_##__op_type##_handle__() { return 0; }
+
+#define REGISTER_OP_KERNEL(type, GPU_OR_CPU, PlaceType, KernelType)       \
+  STATIC_ASSERT_GLOBAL_NAMESPACE(                                         \
+      __reg_op_kernel_##type##_##GPU_OR_CPU##__,                          \
+      "REGISTER_OP_KERNEL must be in global namespace");                  \
+  struct __op_kernel_register__##type##__ {                               \
+    __op_kernel_register__##type##__() {                                  \
+      ::paddle::framework::OperatorWithKernel::OpKernelKey key;           \
+      key.place_ = PlaceType();                                           \
+      ::paddle::framework::OperatorWithKernel::AllOpKernels()[#type][key] \
+          .reset(new KernelType());                                       \
+    }                                                                     \
+  };                                                                      \
+  static __op_kernel_register__##type##__ __reg_kernel_##type##__;        \
+  int __op_kernel_register_##type##_handle_##GPU_OR_CPU##__() { return 0; }
+
+#define REGISTER_OP_GPU_KERNEL(type, KernelType) \
+  REGISTER_OP_KERNEL(type, GPU, ::paddle::platform::GPUPlace, KernelType)
+
+#define REGISTER_OP_CPU_KERNEL(type, KernelType) \
+  REGISTER_OP_KERNEL(type, CPU, ::paddle::platform::CPUPlace, KernelType)
+
+#define USE_OP_WITHOUT_KERNEL(op_type)                      \
+  STATIC_ASSERT_GLOBAL_NAMESPACE(                           \
+      __use_op_without_kernel_##op_type,                    \
+      "USE_OP_WITHOUT_KERNEL must be in global namespace"); \
+  extern int __op_register_##op_type##_handle__();          \
+  static int __use_op_ptr_##op_type##_without_kernel__      \
+      __attribute__((unused)) = __op_register_##op_type##_handle__()
+
+#define USE_OP_KERNEL(op_type, DEVICE_TYPE)                               \
+  STATIC_ASSERT_GLOBAL_NAMESPACE(                                         \
+      __use_op_kernel_##op_type##_##DEVICE_TYPE##__,                      \
+      "USE_OP_KERNEL must be in global namespace");                       \
+  extern int __op_kernel_register_##op_type##_handle_##DEVICE_TYPE##__(); \
+  static int __use_op_ptr_##op_type##_##DEVICE_TYPE##_kernel__            \
+      __attribute__((unused)) =                                           \
+          __op_kernel_register_##op_type##_handle_##DEVICE_TYPE##__()
+
+#ifdef PADDLE_ONLY_CPU
+#define USE_OP(op_type)           \
+  USE_OP_WITHOUT_KERNEL(op_type); \
+  USE_OP_KERNEL(op_type, CPU);
+
+#else
+#define USE_OP(op_type)           \
+  USE_OP_WITHOUT_KERNEL(op_type); \
+  USE_OP_KERNEL(op_type, CPU);    \
+  USE_OP_KERNEL(op_type, GPU)
+#endif
 
 }  // namespace framework
 }  // namespace paddle

paddle/framework/op_registry_test.cc

 #include "paddle/framework/op_registry.h"
 #include <gtest/gtest.h>
 
+namespace paddle {
+namespace framework {
+class CosineOp : public OperatorBase {
+ public:
+  void Run(const std::shared_ptr<Scope>& scope,
+           const platform::DeviceContext& dev_ctx) const override {}
+  void InferShape(const std::shared_ptr<Scope>& scope) const override {}
+};
+
+class CosineOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
+ public:
+  CosineOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    AddInput("input", "input of cosine op");
+    AddOutput("output", "output of cosine op");
+    AddAttr<float>("scale", "scale of cosine op")
+        .SetDefault(1.0)
+        .LargerThan(0.0);
+    AddComment("This is cos op");
+  }
+};
+
+class MyTestOp : public OperatorBase {
+ public:
+  void InferShape(const std::shared_ptr<Scope>& scope) const override {}
+  void Run(const std::shared_ptr<Scope>& scope,
+           const platform::DeviceContext& dev_ctx) const override {}
+
+ public:
+};
+
+class MyTestOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
+ public:
+  MyTestOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    AddInput("input", "input of cosine op");
+    AddOutput("output", "output of cosine op");
+    auto my_checker = [](int i) {
+      PADDLE_ENFORCE(i % 2 == 0, "'test_attr' must be even!");
+    };
+    AddAttr<int>("test_attr", "a simple test attribute")
+        .AddCustomChecker(my_checker);
+    AddComment("This is my_test op");
+  }
+};
+}  // namespace framework
+}  // namespace paddle
+
+REGISTER_OP(cos_sim, paddle::framework::CosineOp,
+            paddle::framework::CosineOpProtoAndCheckerMaker);
+REGISTER_OP(my_test_op, paddle::framework::MyTestOp,
+            paddle::framework::MyTestOpProtoAndCheckerMaker);
+
 TEST(OpRegistry, CreateOp) {
   paddle::framework::OpDesc op_desc;
   op_desc.set_type("cos_sim");
   op_desc.add_inputs("aa");
   op_desc.add_outputs("bb");
 
+  float scale = 3.3;
   auto attr = op_desc.mutable_attrs()->Add();
   attr->set_name("scale");
   attr->set_type(paddle::framework::AttrType::FLOAT);
-  attr->set_f(3.3);
+  attr->set_f(scale);
 
-  paddle::framework::OpBase* op =
+  paddle::framework::OperatorBase* op =
       paddle::framework::OpRegistry::CreateOp(op_desc);
-  std::string debug_str = op->Run();
-  std::string str = "CosineOp runs! scale = " + std::to_string(3.3);
-  ASSERT_EQ(str.size(), debug_str.size());
-  for (size_t i = 0; i < debug_str.length(); ++i) {
-    ASSERT_EQ(debug_str[i], str[i]);
-  }
+  auto scope = std::make_shared<paddle::framework::Scope>();
+  paddle::platform::CPUDeviceContext dev_ctx;
+  op->Run(scope, dev_ctx);
+  float scale_get = op->GetAttr<float>("scale");
+  ASSERT_EQ(scale_get, scale);
 }
 
 TEST(OpRegistry, IllegalAttr) {
@@ -35,7 +88,7 @@ TEST(OpRegistry, IllegalAttr) {
 
   bool caught = false;
   try {
-    paddle::framework::OpBase* op __attribute__((unused)) =
+    paddle::framework::OperatorBase* op __attribute__((unused)) =
         paddle::framework::OpRegistry::CreateOp(op_desc);
   } catch (paddle::framework::EnforceNotMet err) {
     caught = true;
@@ -54,15 +107,14 @@ TEST(OpRegistry, DefaultValue) {
   op_desc.add_inputs("aa");
   op_desc.add_outputs("bb");
 
-  paddle::framework::OpBase* op =
+  ASSERT_TRUE(op_desc.IsInitialized());
+
+  paddle::framework::OperatorBase* op =
       paddle::framework::OpRegistry::CreateOp(op_desc);
-  std::string debug_str = op->Run();
-  float default_value = 1.0;
-  std::string str = "CosineOp runs! scale = " + std::to_string(default_value);
-  ASSERT_EQ(str.size(), debug_str.size());
-  for (size_t i = 0; i < debug_str.length(); ++i) {
-    ASSERT_EQ(debug_str[i], str[i]);
-  }
+  auto scope = std::make_shared<paddle::framework::Scope>();
+  paddle::platform::CPUDeviceContext dev_ctx;
+  op->Run(scope, dev_ctx);
+  ASSERT_EQ(op->GetAttr<float>("scale"), 1.0);
 }
 
 TEST(OpRegistry, CustomChecker) {
@@ -74,7 +126,7 @@ TEST(OpRegistry, CustomChecker) {
   // attr 'test_attr' is not set
   bool caught = false;
   try {
-    paddle::framework::OpBase* op __attribute__((unused)) =
+    paddle::framework::OperatorBase* op __attribute__((unused)) =
         paddle::framework::OpRegistry::CreateOp(op_desc);
   } catch (paddle::framework::EnforceNotMet err) {
     caught = true;
@@ -93,7 +145,7 @@ TEST(OpRegistry, CustomChecker) {
   attr->set_i(3);
   caught = false;
   try {
-    paddle::framework::OpBase* op __attribute__((unused)) =
+    paddle::framework::OperatorBase* op __attribute__((unused)) =
         paddle::framework::OpRegistry::CreateOp(op_desc);
   } catch (paddle::framework::EnforceNotMet err) {
     caught = true;
@@ -111,12 +163,11 @@ TEST(OpRegistry, CustomChecker) {
   attr->set_name("test_attr");
   attr->set_type(paddle::framework::AttrType::INT);
   attr->set_i(4);
-  paddle::framework::OpBase* op =
+  paddle::framework::OperatorBase* op =
       paddle::framework::OpRegistry::CreateOp(op_desc);
-  std::string debug_str = op->Run();
-  std::string str = "MyTestOp runs! test_attr = " + std::to_string(4);
-  ASSERT_EQ(str.size(), debug_str.size());
-  for (size_t i = 0; i < debug_str.length(); ++i) {
-    ASSERT_EQ(debug_str[i], str[i]);
-  }
+  paddle::platform::CPUDeviceContext dev_ctx;
+  auto scope = std::make_shared<paddle::framework::Scope>();
+  op->Run(scope, dev_ctx);
+  int test_attr = op->GetAttr<int>("test_attr");
+  ASSERT_EQ(test_attr, 4);
 }

paddle/framework/operator.cc

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/framework/operator.h"
+
+namespace paddle {
+namespace framework {
+
+std::string OperatorBase::DebugString() const {
+  std::stringstream ss;
+  ss << "=================\n";
+  ss << "type = " << desc_.type() << "\n";
+  ss << "inputs = [";
+  for (auto& ipt : inputs_) {
+    ss << ipt << ", ";
+  }
+  ss << "]\n";
+  ss << "outputs = [";
+  for (auto& opt : outputs_) {
+    ss << opt << ", ";
+  }
+  ss << "]\n";
+  ss << "attr_keys = [";
+  for (auto& attr : attrs_) {
+    ss << attr.first << ", ";
+  }
+  ss << "]\n";
+  return ss.str();
+}
+
+}  // namespace framework
+}  // namespace paddle
\ No newline at end of file

paddle/framework/operator.h

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#pragma once
+
+#include <paddle/framework/attr_checker.h>
+#include <paddle/framework/op_desc.pb.h>
+#include <paddle/framework/scope.h>
+#include <paddle/framework/tensor.h>
+#include <paddle/platform/device_context.h>
+#include <paddle/platform/place.h>
+#include <paddle/utils/Error.h>
+#include <boost/variant.hpp>
+#include <string>
+#include <unordered_map>
+#include <vector>
+
+namespace paddle {
+namespace framework {
+
+class OperatorBase;
+
+/**
+ * OperatorBase has the basic element that Net will call to do computation.
+ * Only CreateOperator from OpRegistry will new Operator directly. User
+ * should always construct a proto message OpDesc and call
+ * OpRegistry::CreateOp(op_desc) to get an Operator instance.
+ */
+class OperatorBase {
+ public:
+  virtual ~OperatorBase() {}
+
+  template <typename T>
+  inline const T& GetAttr(const std::string& name) const {
+    PADDLE_ENFORCE(attrs_.count(name) != 0, "%s should be in AttributeMap",
+                   name);
+    return boost::get<T>(attrs_.at(name));
+  }
+
+  std::string DebugString() const;
+
+  /// Init will be called after CreateOperator, you can put some initialization
+  /// logic here.
+  virtual void Init() {}
+
+  /// InferShape infer the size of Variables used by this Operator with
+  /// information inside scope
+  virtual void InferShape(const std::shared_ptr<Scope>& scope) const = 0;
+
+  /// Net will call this function to Run an op.
+  virtual void Run(const std::shared_ptr<Scope>& scope,
+                   const platform::DeviceContext& dev_ctx) const = 0;
+
+ protected:
+  std::string Type() const { return desc_.type(); }
+
+ public:
+  OpDesc desc_;
+  std::vector<std::string> inputs_;
+  std::vector<std::string> outputs_;
+  AttributeMap attrs_;
+};
+
+class OpKernel {
+ public:
+  /**
+   * KernelContext is the only parameter of Kernel Run function.
+   * Run will get input/output variables, state such as momentum and
+   * device resource such as CUDA stream, cublas handle, etc. from
+   * KernelContext. User should construct it before run the Operator.
+   */
+  class KernelContext {
+   public:
+    KernelContext(const OperatorBase* op, const std::shared_ptr<Scope>& scope,
+                  const platform::DeviceContext& device_context)
+        : op_(*op), scope_(scope), device_context_(device_context) {}
+
+    const Variable* Input(int index) const {
+      return scope_->GetVariable(op_.inputs_[index]);
+    }
+
+    Variable* Output(int index) const {
+      return scope_->GetVariable(op_.outputs_[index]);
+    }
+
+    const OperatorBase& op_;
+    const std::shared_ptr<Scope>& scope_;
+    const platform::DeviceContext& device_context_;
+  };
+
+  virtual void Compute(const KernelContext& context) const = 0;
+
+  virtual ~OpKernel() {}
+};
+
+template <typename T>
+struct VarToTensor {};
+
+template <>
+struct VarToTensor<Tensor*> {
+  Tensor* operator()(Variable* var) { return var->GetMutable<Tensor>(); }
+};
+
+template <>
+struct VarToTensor<const Tensor*> {
+  const Tensor* operator()(Variable* var) { return &var->Get<Tensor>(); }
+};
+
+class OperatorWithKernel : public OperatorBase {
+ public:
+  struct OpKernelKey {
+    platform::Place place_;
+
+    OpKernelKey() = default;
+    OpKernelKey(const platform::DeviceContext& dev_ctx) {
+      place_ = dev_ctx.GetPlace();
+    }
+
+    bool operator==(const OpKernelKey& o) const { return place_ == o.place_; }
+  };
+
+  struct OpKernelHash {
+    std::hash<bool> hash_;
+    size_t operator()(const OpKernelKey& key) const {
+      return hash_(platform::is_gpu_place(key.place_));
+    }
+  };
+
+  using OpKernelMap =
+      std::unordered_map<OpKernelKey, std::unique_ptr<OpKernel>, OpKernelHash>;
+
+  void Run(const std::shared_ptr<Scope>& scope,
+           const platform::DeviceContext& dev_ctx) const final {
+    auto& opKernel = AllOpKernels().at(Type()).at(OpKernelKey(dev_ctx));
+    opKernel->Compute(OpKernel::KernelContext(this, scope, dev_ctx));
+  }
+
+  static std::unordered_map<std::string /* op_type */, OpKernelMap>&
+  AllOpKernels() {
+    static std::unordered_map<std::string, OpKernelMap> g_all_op_kernels;
+    return g_all_op_kernels;
+  }
+  void InferShape(const std::shared_ptr<Scope>& scope) const final {
+    std::vector<const Tensor*> ins;
+    VarNamesToTensors(scope, inputs_, &ins);
+    std::vector<Tensor*> outs;
+    VarNamesToTensors(scope, outputs_, &outs);
+    InferShape(ins, outs);
+  };
+
+ private:
+  template <typename T>
+  void VarNamesToTensors(const std::shared_ptr<Scope>& scope,
+                         const std::vector<std::string>& var_names,
+                         std::vector<T>* container) const {
+    container->reserve(var_names.size());
+    VarToTensor<T> convert;
+    for (auto& name : var_names) {
+      auto var = scope->GetVariable(name);
+      if (var != nullptr) {
+        container->push_back(convert(var));
+      } else {
+        container->push_back(nullptr);
+      }
+    }
+  }
+
+ protected:
+  virtual void InferShape(const std::vector<const Tensor*>& inputs,
+                          const std::vector<Tensor*>& outputs) const = 0;
+};
+
+}  // namespace framework
+}  // namespace paddle

paddle/framework/operator_test.cc

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/framework/operator.h"
+#include "gtest/gtest.h"
+#include "paddle/framework/op_registry.h"
+
+namespace paddle {
+namespace framework {
+
+class OperatorTest : public OperatorBase {
+ public:
+  void Init() override { x = 1; }
+  void InferShape(const std::shared_ptr<Scope>& scope) const override {}
+  void Run(const std::shared_ptr<Scope>& scope,
+           const platform::DeviceContext& dev_ctx) const override {
+    float scale = GetAttr<float>("scale");
+    ASSERT_NEAR(scale, 3.14, 1e-5);
+    ASSERT_EQ(scope->GetVariable(inputs_[0]), nullptr);
+    ASSERT_EQ(x, 1);
+    ASSERT_NE(scope->GetVariable(outputs_[0]), nullptr);
+  }
+
+ public:
+  float x = 0;
+};
+
+class OpKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
+ public:
+  OpKernelTestProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    AddInput("input", "input of test op");
+    AddOutput("output", "output of test op");
+    AddAttr<float>("scale", "scale of cosine op")
+        .SetDefault(1.0)
+        .LargerThan(0.0);
+    AddComment("This is test op");
+  }
+};
+
+class OpWithKernelTest : public OperatorWithKernel {
+ protected:
+  void InferShape(const std::vector<const Tensor*>& inputs,
+                  const std::vector<Tensor*>& outputs) const override {}
+};
+
+class CPUKernelTest : public OpKernel {
+ public:
+  void Compute(const KernelContext& context) const {
+    float scale = context.op_.GetAttr<float>("scale");
+    ASSERT_NEAR(scale, 3.14, 1e-5);
+    std::cout << "this is cpu kernel" << std::endl;
+    std::cout << context.op_.DebugString() << std::endl;
+  }
+};
+
+}  // namespace framework
+}  // namespace paddle
+
+REGISTER_OP(op_with_kernel, paddle::framework::OpWithKernelTest,
+            paddle::framework::OpKernelTestProtoAndCheckerMaker);
+REGISTER_OP_CPU_KERNEL(op_with_kernel, paddle::framework::CPUKernelTest);
+
+TEST(OpKernel, all) {
+  using namespace paddle::framework;
+
+  OpDesc op_desc;
+  op_desc.set_type("op_with_kernel");
+  *op_desc.mutable_inputs()->Add() = "IN1";
+  *op_desc.mutable_outputs()->Add() = "OUT1";
+  auto attr = op_desc.mutable_attrs()->Add();
+  attr->set_name("scale");
+  attr->set_type(paddle::framework::AttrType::FLOAT);
+  attr->set_f(3.14);
+
+  paddle::platform::CPUDeviceContext cpu_device_context;
+  auto scope = std::make_shared<Scope>();
+
+  OperatorBase* op = paddle::framework::OpRegistry::CreateOp(op_desc);
+  op->Run(scope, cpu_device_context);
+
+  delete op;
+}

paddle/framework/tensor.h

@@ -14,6 +14,7 @@ limitations under the License. */
 
 #pragma once
 
+#include <cstdint>
 #include <memory>
 #include <type_traits>
 #include "paddle/framework/ddim.h"
@@ -26,31 +27,65 @@ namespace framework {
 
 class Tensor {
  public:
+  Tensor() : offset_(0) {}
+
+  explicit Tensor(const DDim& dims) : dims_(dims), offset_(0) {}
+
   template <typename T>
   const T* data() const {
-    PADDLE_ENFORCE(holder_ != nullptr,
-                   "Tensor::data must be called after Tensor::mutable_data.");
-    return static_cast<const T*>(holder_->Ptr());
+    PADDLE_ENFORCE(
+        holder_ != nullptr,
+        "Tenosr has not been initialized. Call Tensor::mutable_data first.");
+    return reinterpret_cast<const T*>(
+        reinterpret_cast<uintptr_t>(holder_->Ptr()) + offset_);
   }
 
   template <typename T,  // must be POD types
             typename std::enable_if<std::is_pod<T>::value>::type* = nullptr>
   T* mutable_data(DDim dims, paddle::platform::Place place) {
+    dims_ = dims;
     if (holder_ == nullptr ||
         !(holder_->Place() ==
           place) /* some versions of boost::variant don't have operator!= */
-        || holder_->Size() < product(dims) * sizeof(T)) {
+        || holder_->Size() < product(dims) * sizeof(T) + offset_) {
       holder_.reset(new PlaceholderImpl<T>(place, product(dims) * sizeof(T)));
+      offset_ = 0;
     }
-    return static_cast<T*>(holder_->Ptr());
+    return reinterpret_cast<T*>(reinterpret_cast<uintptr_t>(holder_->Ptr()) +
+                                offset_);
   }
 
-  template <typename T,  // must be POD types
-            typename std::enable_if<std::is_pod<T>::value>::type* = nullptr>
-  T* mutable_data(DDim dims) {
-    return mutable_data<T>(dims, paddle::platform::get_place());
+  void ShareDataFrom(const Tensor& src) {
+    PADDLE_ENFORCE(src.holder_ != nullptr,
+                   "Can not share data from an uninitialized tensor.");
+    holder_ = src.holder_;
+    dims_ = src.dims_;
+    offset_ = src.offset_;
   }
 
+  Tensor Slice(const int& begin_idx, const int& end_idx) const {
+    PADDLE_ENFORCE(holder_ != nullptr,
+                   "The sliced tenosr has not been initialized.");
+    PADDLE_ENFORCE(begin_idx >= 0 && end_idx <= dims_[0],
+                   "Slice index is less than zero or out of bound.");
+    PADDLE_ENFORCE(begin_idx < end_idx,
+                   "Begin index must be less than end index.");
+    PADDLE_ENFORCE(dims_[0] != 1, "Can not slice a tensor with dims_[0] = 1.");
+    std::vector<int> d = vectorize(dims_);
+    int base = 1;
+    for (size_t i = 1; i < d.size(); ++i) {
+      base *= d[i];
+    }
+    Tensor dst;
+    dst.holder_ = holder_;
+    dst.dims_ = dims_;
+    dst.dims_[0] = end_idx - begin_idx;
+    dst.offset_ = offset_ + begin_idx * base * holder_->TypeSize();
+    return dst;
+  }
+
+  DDim dims() const { return dims_; }
+
  private:
   // Placeholder hides type T, so it doesn't appear as a template
   // parameter of Variable.
@@ -59,6 +94,7 @@ class Tensor {
     virtual void* Ptr() const = 0;
     virtual paddle::platform::Place Place() const = 0;
     virtual size_t Size() const = 0;
+    virtual size_t TypeSize() const = 0;
   };
 
   template <typename T>
@@ -85,6 +121,7 @@ class Tensor {
     virtual void* Ptr() const { return static_cast<void*>(ptr_.get()); }
     virtual size_t Size() const { return size_; }
     virtual paddle::platform::Place Place() const { return place_; }
+    virtual size_t TypeSize() const { return sizeof(T); }
 
     std::unique_ptr<T, Deleter> ptr_;
     paddle::platform::Place place_;  // record the place of ptr_.
@@ -92,6 +129,8 @@ class Tensor {
   };
 
   std::shared_ptr<Placeholder> holder_;  // holds the memory block if allocated.
+  DDim dims_;
+  size_t offset_;  // marks the begin of tensor data area.
 };
 
 }  // namespace framework

paddle/framework/tensor_test.cc

@@ -15,15 +15,27 @@
 #include <gtest/gtest.h>
 #include <string>
 
-TEST(Tensor, ASSERT) {
-  paddle::framework::Tensor cpu_tensor;
+TEST(Tensor, Dims) {
+  using namespace paddle::framework;
+  using namespace paddle::platform;
+  Tensor tt(make_ddim({2, 3, 4}));
+  DDim dims = tt.dims();
+  ASSERT_EQ(arity(dims), 3);
+  for (int i = 0; i < 3; ++i) {
+    EXPECT_EQ(i + 2, dims[i]);
+  }
+}
+
+TEST(Tensor, DataAssert) {
+  paddle::framework::Tensor src_tensor;
 
   bool caught = false;
   try {
-    const double* p __attribute__((unused)) = cpu_tensor.data<double>();
+    src_tensor.data<double>();
   } catch (paddle::framework::EnforceNotMet err) {
     caught = true;
-    std::string msg = "Tensor::data must be called after Tensor::mutable_data.";
+    std::string msg =
+        "Tenosr has not been initialized. Call Tensor::mutable_data first.";
     const char* what = err.what();
     for (size_t i = 0; i < msg.length(); ++i) {
       ASSERT_EQ(what[i], msg[i]);
@@ -32,54 +44,138 @@ TEST(Tensor, ASSERT) {
   ASSERT_TRUE(caught);
 }
 
-/* mutable_data() is not tested at present
+/* following tests are not available at present
    because Memory::Alloc() and Memory::Free() have not been ready.
 
 TEST(Tensor, MutableData) {
   using namespace paddle::framework;
   using namespace paddle::platform;
   {
-    Tensor cpu_tensor;
+    Tensor src_tensor;
     float* p1 = nullptr;
     float* p2 = nullptr;
     // initialization
-    p1 = cpu_tensor.mutable_data<float>(make_ddim({1, 2, 3}), CPUPlace());
+    p1 = src_tensor.mutable_data<float>(make_ddim({1, 2, 3}), CPUPlace());
     EXPECT_NE(p1, nullptr);
-    // set cpu_tensor a new dim with large size
+    // set src_tensor a new dim with large size
     // momery is supposed to be re-allocated
-    p2 = cpu_tensor.mutable_data<float>(make_ddim({3, 4}));
+    p2 = src_tensor.mutable_data<float>(make_ddim({3, 4}), CPUPlace());
     EXPECT_NE(p2, nullptr);
     EXPECT_NE(p1, p2);
-    // set cpu_tensor a new dim with same size
+    // set src_tensor a new dim with same size
     // momery block is supposed to be unchanged
-    p1 = cpu_tensor.mutable_data<float>(make_ddim({2, 2, 3}));
+    p1 = src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), CPUPlace());
     EXPECT_EQ(p1, p2);
-    // set cpu_tensor a new dim with smaller size
+    // set src_tensor a new dim with smaller size
     // momery block is supposed to be unchanged
-    p2 = cpu_tensor.mutable_data<float>(make_ddim({2, 2}));
+    p2 = src_tensor.mutable_data<float>(make_ddim({2, 2}), CPUPlace());
     EXPECT_EQ(p1, p2);
   }
 
   {
-    Tensor gpu_tensor;
+    Tensor src_tensor;
     float* p1 = nullptr;
     float* p2 = nullptr;
     // initialization
-    p1 = gpu_tensor.mutable_data<float>(make_ddim({1, 2, 3}), GPUPlace());
+    p1 = src_tensor.mutable_data<float>(make_ddim({1, 2, 3}), GPUPlace());
     EXPECT_NE(p1, nullptr);
-    // set gpu_tensor a new dim with large size
+    // set src_tensor a new dim with large size
     // momery is supposed to be re-allocated
-    p2 = gpu_tensor.mutable_data<float>(make_ddim({3, 4}));
+    p2 = src_tensor.mutable_data<float>(make_ddim({3, 4}), GPUPlace());
     EXPECT_NE(p2, nullptr);
     EXPECT_NE(p1, p2);
-    // set gpu_tensor a new dim with same size
+    // set src_tensor a new dim with same size
     // momery block is supposed to be unchanged
-    p1 = gpu_tensor.mutable_data<float>(make_ddim({2, 2, 3}));
+    p1 = src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), GPUPlace());
     EXPECT_EQ(p1, p2);
-    // set gpu_tensor a new dim with smaller size
+    // set src_tensor a new dim with smaller size
     // momery block is supposed to be unchanged
-    p2 = gpu_tensor.mutable_data<float>(make_ddim({2, 2}));
+    p2 = src_tensor.mutable_data<float>(make_ddim({2, 2}), GPUPlace());
     EXPECT_EQ(p1, p2);
   }
 }
-*/
+
+TEST(Tensor, ShareDataFrom) {
+  using namespace paddle::framework;
+  using namespace paddle::platform;
+  {
+    Tensor src_tensor;
+    Tensor dst_tensor;
+    // Try to share data form uninitialized tensor
+    bool caught = false;
+    try {
+      dst_tensor.ShareDataFrom(src_tensor);
+    } catch (EnforceNotMet err) {
+      caught = true;
+      std::string msg = "Can not share data from an uninitialized tensor.";
+      const char* what = err.what();
+      for (size_t i = 0; i < msg.length(); ++i) {
+        ASSERT_EQ(what[i], msg[i]);
+      }
+    }
+    ASSERT_TRUE(caught);
+
+    src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), CPUPlace());
+    dst_tensor.ShareDataFrom(src_tensor);
+    ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
+  }
+
+  {
+    Tensor src_tensor;
+    Tensor dst_tensor;
+    src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), GPUPlace());
+    dst_tensor.ShareDataFrom(src_tensor);
+    ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
+  }
+}
+
+TEST(Tensor, Slice) {
+  using namespace paddle::framework;
+  using namespace paddle::platform;
+  {
+    Tensor src_tensor;
+    src_tensor.mutable_data<int>(make_ddim({5, 3, 4}), CPUPlace());
+    Tensor slice_tensor = src_tensor.Slice(1, 3);
+    DDim slice_dims = slice_tensor.dims();
+    ASSERT_EQ(arity(slice_dims), 3);
+    EXPECT_EQ(slice_dims[0], 2);
+    EXPECT_EQ(slice_dims[1], 3);
+    EXPECT_EQ(slice_dims[2], 4);
+
+    uintptr_t src_data_address =
+        reinterpret_cast<uintptr_t>(src_tensor.data<int>());
+    uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
+        src_tensor.mutable_data<int>(src_tensor.dims(), CPUPlace()));
+    uintptr_t slice_data_address =
+        reinterpret_cast<uintptr_t>(slice_tensor.data<int>());
+    uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
+        slice_tensor.mutable_data<int>(slice_tensor.dims(), CPUPlace()));
+    EXPECT_EQ(src_data_address, src_mutable_data_address);
+    EXPECT_EQ(slice_data_address, slice_mutable_data_address);
+    EXPECT_EQ(src_data_address + 3 * 4 * 1 * sizeof(int), slice_data_address);
+  }
+
+  {
+    Tensor src_tensor;
+    src_tensor.mutable_data<double>(make_ddim({6, 9}), GPUPlace());
+    Tensor slice_tensor = src_tensor.Slice(2, 6);
+    DDim slice_dims = slice_tensor.dims();
+    ASSERT_EQ(arity(slice_dims), 2);
+    EXPECT_EQ(slice_dims[0], 4);
+    EXPECT_EQ(slice_dims[1], 9);
+
+    uintptr_t src_data_address =
+        reinterpret_cast<uintptr_t>(src_tensor.data<double>());
+    uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
+        src_tensor.mutable_data<double>(src_tensor.dims(), GPUPlace()));
+    uintptr_t slice_data_address =
+        reinterpret_cast<uintptr_t>(slice_tensor.data<double>());
+    uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
+        slice_tensor.mutable_data<double>(slice_tensor.dims(), GPUPlace()));
+    EXPECT_EQ(src_data_address, src_mutable_data_address);
+    EXPECT_EQ(slice_data_address, slice_mutable_data_address);
+    EXPECT_EQ(src_data_address + 9 * 2 * sizeof(double), slice_data_address);
+  }
+}
+
+*/
\ No newline at end of file

paddle/operators/CMakeLists.txt

+if(WITH_GPU)
+    nv_library(add_op SRCS add_op.cc add_op.cu DEPS operator op_registry glog ddim)
+else()
+    cc_library(add_op SRCS add_op.cc DEPS operator op_registry glog ddim)
+endif()
+cc_test(add_op_test SRCS add_op_test.cc DEPS add_op)

paddle/operators/add_op.cc

+#include <paddle/framework/op_registry.h>
+#include <paddle/framework/tensor.h>
+#include <paddle/operators/add_op.h>
+
+namespace paddle {
+namespace operators {
+
+class AddOp : public framework::OperatorWithKernel {
+protected:
+  void InferShape(
+      const std::vector<const framework::Tensor *> &inputs,
+      const std::vector<framework::Tensor *> &outputs) const override {
+    PADDLE_ENFORCE(inputs.size() == 2, "Input size of AddOp must be two");
+    PADDLE_ENFORCE(outputs.size() == 1, "Output size of AddOp must be one");
+    PADDLE_ENFORCE(
+        inputs[0] != nullptr && inputs[1] != nullptr && outputs[0] != nullptr,
+        "Inputs/Outputs of AddOp must all be set");
+    PADDLE_ENFORCE(inputs[0]->dims() == inputs[1]->dims(),
+                   "Two input of Add Op's dimension must be same.");
+    // Need set dims in Tensor
+    // outputs[0]->set_dims(inputs[0]->dims())
+  }
+};
+
+class AddOpMaker : public framework::OpProtoAndCheckerMaker {
+public:
+  AddOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+    AddInput("X", "The first input of add op");
+    AddInput("Y", "The second input of add op");
+    AddOutput("Out", "The output of add op");
+    AddComment(R"DOC(
+Two Element Add Operator.
+
+The equation is: Out = X + Y
+)DOC");
+  }
+};
+}  // namespace op
+}  // namespace paddle
+
+REGISTER_OP(add_two, paddle::operators::AddOp, paddle::operators::AddOpMaker);
+REGISTER_OP_CPU_KERNEL(
+    add_two, ::paddle::operators::AddKernel<::paddle::platform::CPUPlace>);
\ No newline at end of file

paddle/operators/add_op.cu

+#include <paddle/operators/add_op.h>
+#include <paddle/framework/op_registry.h>
+
+REGISTER_OP_GPU_KERNEL(add_two,
+                       paddle::operators::AddKernel<paddle::platform::GPUPlace>);
\ No newline at end of file

paddle/operators/add_op.h

+#pragma once
+#include <glog/logging.h>
+#include <paddle/framework/operator.h>
+
+namespace paddle {
+namespace operators {
+
+template <typename Place>
+class AddKernel : public framework::OpKernel {
+public:
+  void Compute(const KernelContext &context) const override {
+    LOG(INFO) << "Add kernel in " << typeid(Place).name();
+  }
+};
+
+}  // namespace op
+}  // namespace paddle

paddle/operators/add_op_test.cc

+#include <gtest/gtest.h>
+#define private public
+#include <paddle/framework/op_registry.h>
+USE_OP(add_two);
+TEST(AddOp, GetOpProto) {
+  auto& protos = paddle::framework::OpRegistry::protos();
+  auto it = protos.find("add_two");
+  ASSERT_NE(it, protos.end());
+}
\ No newline at end of file

paddle/optimizer/optimizer.cc

@@ -44,8 +44,8 @@ paddle_optimizer* paddle_create_optimizer(const unsigned char* config_proto,
                                           const int state_len) {
   paddle_optimizer* optimizer = new paddle_optimizer;
   std::string config(config_proto, config_proto + config_proto_len);
-  Tensor* parameter =
-      new Tensor(reinterpret_cast<float*>(param_buffer), num_bytes);
+  Tensor* parameter = new Tensor(reinterpret_cast<float*>(param_buffer),
+                                 num_bytes / sizeof(float));
   optimizer->impl = ParameterOptimizer::Create(config, parameter);
   if (state != nullptr) {
     std::string s(state, state + state_len);
@@ -65,7 +65,8 @@ int paddle_update_parameter(paddle_optimizer* o,
                             int num_bytes) {
   // TOOD(zhihong): datatype not work. need to add the runtime datatype
   auto grad_type = reinterpret_cast<const float*>(grad_buffer);
-  Tensor* gradient = new Tensor(const_cast<float*>(grad_type), num_bytes);
+  Tensor* gradient =
+      new Tensor(const_cast<float*>(grad_type), num_bytes / sizeof(float));
   o->impl->Update(gradient);
   return PADDLE_SUCCESS;
 }

paddle/platform/CMakeLists.txt

@@ -6,6 +6,13 @@ nv_library(gpu_info SRCS gpu_info.cc DEPS gflags)
 cc_library(place SRCS place.cc)
 cc_test(place_test SRCS place_test.cc DEPS place glog gflags)
 
-cc_library(dynamic_loader SRCS dynload/dynamic_loader.cc DEPS gflags glog)
+add_subdirectory(dynload)
 
-nv_test(device_context_test SRCS device_context_test.cc DEPS dynamic_loader place eigen3 gpu_info)
+IF(WITH_GPU)
+    set(GPU_CTX_DEPS dynload_cuda dynamic_loader)
+ELSE()
+    set(GPU_CTX_DEPS)
+ENDIF()
+
+cc_library(device_context SRCS device_context.cc DEPS place eigen3 ${GPU_CTX_DEPS})
+nv_test(device_context_test SRCS device_context_test.cc DEPS device_context gpu_info)

paddle/platform/device_context.cc

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+    http://www.apache.org/licenses/LICENSE-2.0
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/platform/device_context.h"
+
+namespace paddle {
+namespace platform {
+
+template <>
+Eigen::DefaultDevice* DeviceContext::get_eigen_device<Eigen::DefaultDevice>() {
+  return reinterpret_cast<CPUDeviceContext*>(this)->eigen_device();
+}
+
+#ifndef PADDLE_ONLY_CPU
+template <>
+Eigen::GpuDevice* DeviceContext::get_eigen_device<Eigen::GpuDevice>() {
+  return reinterpret_cast<CUDADeviceContext*>(this)->eigen_device();
+}
+#endif
+
+}  // namespace platform
+}  // namespace paddle

paddle/platform/device_context.h

 /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
-
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
 You may obtain a copy of the License at
-
     http://www.apache.org/licenses/LICENSE-2.0
-
 Unless required by applicable law or agreed to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
@@ -23,8 +20,9 @@ limitations under the License. */
 #include "paddle/platform/gpu_info.h"
 #define EIGEN_USE_GPU
 #endif
-#include "paddle/platform/place.h"
-#include "unsupported/Eigen/CXX11/Tensor"
+#include <paddle/platform/place.h>
+#include <memory>
+#include <unsupported/Eigen/CXX11/Tensor>
 
 namespace paddle {
 namespace platform {
@@ -32,9 +30,29 @@ namespace platform {
 class DeviceContext {
  public:
   virtual ~DeviceContext() {}
+  virtual Place GetPlace() const = 0;
+
+  template <typename DeviceType>
+  DeviceType* get_eigen_device();
 };
 
-class CPUDeviceContext : public DeviceContext {};
+class CPUDeviceContext : public DeviceContext {
+ public:
+  Eigen::DefaultDevice* eigen_device() {
+    if (!eigen_device_) {
+      eigen_device_.reset(new Eigen::DefaultDevice());
+    }
+    return eigen_device_.get();
+  }
+
+  Place GetPlace() const override {
+    Place retv = CPUPlace();
+    return retv;
+  }
+
+ private:
+  std::unique_ptr<Eigen::DefaultDevice> eigen_device_;
+};
 
 #ifndef PADDLE_ONLY_CPU
 
@@ -58,8 +76,13 @@ class CUDADeviceContext : public DeviceContext {
     GPUPlaceGuard guard(gpu_place_);
     paddle::platform::throw_on_error(cudaStreamCreate(&stream_),
                                      "cudaStreamCreate failed");
-    eigen_stream_ = new Eigen::CudaStreamDevice(&stream_);
-    eigen_device_ = new Eigen::GpuDevice(eigen_stream_);
+    eigen_stream_.reset(new Eigen::CudaStreamDevice(&stream_));
+    eigen_device_.reset(new Eigen::GpuDevice(eigen_stream_.get()));
+  }
+
+  Place GetPlace() const override {
+    Place retv = GPUPlace();
+    return retv;
   }
 
   void Wait() {
@@ -69,7 +92,7 @@ class CUDADeviceContext : public DeviceContext {
 
   cudaStream_t stream() { return stream_; }
 
-  Eigen::GpuDevice eigen_device() { return *eigen_device_; }
+  Eigen::GpuDevice* eigen_device() { return eigen_device_.get(); }
 
   cublasHandle_t cublas_handle() {
     if (!blas_handle_) {
@@ -134,10 +157,8 @@ class CUDADeviceContext : public DeviceContext {
                          rand_generator_) == CURAND_STATUS_SUCCESS,
                      "curandDestroyGenerator failed");
     }
-
-    delete eigen_stream_;
-    delete eigen_device_;
-
+    eigen_stream_.reset();
+    eigen_device_.reset();
     paddle::platform::throw_on_error(cudaStreamDestroy(stream_),
                                      "cudaStreamDestroy failed");
   }
@@ -146,8 +167,8 @@ class CUDADeviceContext : public DeviceContext {
   GPUPlace gpu_place_;
   cudaStream_t stream_;
 
-  Eigen::CudaStreamDevice* eigen_stream_;
-  Eigen::GpuDevice* eigen_device_;
+  std::unique_ptr<Eigen::CudaStreamDevice> eigen_stream_;
+  std::unique_ptr<Eigen::GpuDevice> eigen_device_;
 
   cublasHandle_t blas_handle_{nullptr};
 
@@ -156,6 +177,8 @@ class CUDADeviceContext : public DeviceContext {
   int random_seed_;
   curandGenerator_t rand_generator_{nullptr};
 };
+
 #endif
+
 }  // namespace platform
 }  // namespace paddle

paddle/platform/device_context_test.cc

@@ -15,13 +15,26 @@ limitations under the License. */
 #include "paddle/platform/device_context.h"
 #include "gtest/gtest.h"
 
-TEST(CUDADeviceContext, Init) {
+using DEVICE_GPU = Eigen::GpuDevice;
+TEST(Device, Init) {
+  int count = paddle::platform::GetDeviceCount();
+  for (int i = 0; i < count; i++) {
+    paddle::platform::DeviceContext* device_context =
+        new paddle::platform::CUDADeviceContext(i);
+    Eigen::GpuDevice* gpu_device =
+        device_context->template get_eigen_device<DEVICE_GPU>();
+    ASSERT_NE(nullptr, gpu_device);
+    delete device_context;
+  }
+}
+
+TEST(Device, CUDADeviceContext) {
   int count = paddle::platform::GetDeviceCount();
   for (int i = 0; i < count; i++) {
     paddle::platform::CUDADeviceContext* device_context =
         new paddle::platform::CUDADeviceContext(i);
-    Eigen::GpuDevice gpu_device = device_context->eigen_device();
-    ASSERT_NE(nullptr, gpu_device.stream());
+    Eigen::GpuDevice* gpu_device = device_context->eigen_device();
+    ASSERT_NE(nullptr, gpu_device);
     cudnnHandle_t cudnn_handle = device_context->cudnn_handle();
     ASSERT_NE(nullptr, cudnn_handle);
     cublasHandle_t cublas_handle = device_context->cublas_handle();

paddle/platform/dynload/CMakeLists.txt

+cc_library(dynamic_loader SRCS dynamic_loader.cc DEPS glog gflags)
+nv_library(dynload_cuda SRCS cublas.cc cudnn.cc curand.cc)

paddle/platform/dynload/cublas.cc

+#include <paddle/platform/dynload/cublas.h>
+
+namespace paddle {
+namespace platform {
+namespace dynload {
+std::once_flag cublas_dso_flag;
+void *cublas_dso_handle = nullptr;
+
+#define DEFINE_WRAP(__name) DynLoad__##__name __name
+
+CUBLAS_BLAS_ROUTINE_EACH(DEFINE_WRAP);
+
+}  // namespace dynload
+}  // namespace platform
+}  // namespace paddle

paddle/platform/dynload/cublas.h

@@ -23,8 +23,8 @@ namespace paddle {
 namespace platform {
 namespace dynload {
 
-std::once_flag cublas_dso_flag;
-void *cublas_dso_handle = nullptr;
+extern std::once_flag cublas_dso_flag;
+extern void *cublas_dso_handle;
 
 /**
  * The following macro definition can generate structs
@@ -34,10 +34,10 @@ void *cublas_dso_handle = nullptr;
  * note: default dynamic linked libs
  */
 #ifdef PADDLE_USE_DSO
-#define DYNAMIC_LOAD_CUBLAS_WRAP(__name)                            \
+#define DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP(__name)                    \
   struct DynLoad__##__name {                                        \
     template <typename... Args>                                     \
-    cublasStatus_t operator()(Args... args) {                       \
+    inline cublasStatus_t operator()(Args... args) {                \
       typedef cublasStatus_t (*cublasFunc)(Args...);                \
       std::call_once(cublas_dso_flag,                               \
                      paddle::platform::dynload::GetCublasDsoHandle, \
@@ -45,62 +45,46 @@ void *cublas_dso_handle = nullptr;
       void *p_##__name = dlsym(cublas_dso_handle, #__name);         \
       return reinterpret_cast<cublasFunc>(p_##__name)(args...);     \
     }                                                               \
-  } __name;  // struct DynLoad__##__name
+  };                                                                \
+  extern DynLoad__##__name __name
 #else
-#define DYNAMIC_LOAD_CUBLAS_WRAP(__name)      \
-  struct DynLoad__##__name {                  \
-    template <typename... Args>               \
-    cublasStatus_t operator()(Args... args) { \
-      return __name(args...);                 \
-    }                                         \
-  } __name;  // struct DynLoad__##__name
+#define DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP(__name) \
+  struct DynLoad__##__name {                     \
+    inline template <typename... Args>           \
+    cublasStatus_t operator()(Args... args) {    \
+      return __name(args...);                    \
+    }                                            \
+  };                                             \
+  extern DynLoad__##__name __name
 #endif
 
-#define DYNAMIC_LOAD_CUBLAS_V2_WRAP(__name) DYNAMIC_LOAD_CUBLAS_WRAP(__name)
+#define DECLARE_DYNAMIC_LOAD_CUBLAS_V2_WRAP(__name) \
+  DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP(__name)
 
-// include all needed cublas functions in HPPL
-// clang-format off
 #define CUBLAS_BLAS_ROUTINE_EACH(__macro) \
-  __macro(cublasSgemv)                    \
-  __macro(cublasDgemv)                    \
-  __macro(cublasSgemm)                    \
-  __macro(cublasDgemm)                    \
-  __macro(cublasSgeam)                    \
-  __macro(cublasDgeam)                    \
+  __macro(cublasSgemv);                   \
+  __macro(cublasDgemv);                   \
+  __macro(cublasSgemm);                   \
+  __macro(cublasDgemm);                   \
+  __macro(cublasSgeam);                   \
+  __macro(cublasDgeam);                   \
+  __macro(cublasCreate_v2);               \
+  __macro(cublasDestroy_v2);              \
+  __macro(cublasSetStream_v2);            \
+  __macro(cublasSetPointerMode_v2);       \
+  __macro(cublasGetPointerMode_v2);       \
+  __macro(cublasSgemmBatched);            \
+  __macro(cublasDgemmBatched);            \
+  __macro(cublasCgemmBatched);            \
+  __macro(cublasZgemmBatched);            \
+  __macro(cublasSgetrfBatched);           \
+  __macro(cublasSgetriBatched);           \
+  __macro(cublasDgetrfBatched);           \
+  __macro(cublasDgetriBatched)
 
-DYNAMIC_LOAD_CUBLAS_V2_WRAP(cublasCreate)
-DYNAMIC_LOAD_CUBLAS_V2_WRAP(cublasDestroy)
-DYNAMIC_LOAD_CUBLAS_V2_WRAP(cublasSetStream)
-DYNAMIC_LOAD_CUBLAS_V2_WRAP(cublasSetPointerMode)
-DYNAMIC_LOAD_CUBLAS_V2_WRAP(cublasGetPointerMode)
-DYNAMIC_LOAD_CUBLAS_WRAP(cublasSgemmBatched)
-DYNAMIC_LOAD_CUBLAS_WRAP(cublasDgemmBatched)
-DYNAMIC_LOAD_CUBLAS_WRAP(cublasCgemmBatched)
-DYNAMIC_LOAD_CUBLAS_WRAP(cublasZgemmBatched)
-DYNAMIC_LOAD_CUBLAS_WRAP(cublasSgetrfBatched)
-DYNAMIC_LOAD_CUBLAS_WRAP(cublasSgetriBatched)
-DYNAMIC_LOAD_CUBLAS_WRAP(cublasDgetrfBatched)
-DYNAMIC_LOAD_CUBLAS_WRAP(cublasDgetriBatched)
-CUBLAS_BLAS_ROUTINE_EACH(DYNAMIC_LOAD_CUBLAS_V2_WRAP)
+CUBLAS_BLAS_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP);
 
-#undef DYNAMIC_LOAD_CUBLAS_WRAP
-#undef DYNAMIC_LOAD_CUBLAS_V2_WRAP
-#undef CUBLAS_BLAS_ROUTINE_EACH
-
-// clang-format on
-#ifndef PADDLE_TYPE_DOUBLE
-#define CUBLAS_GEAM paddle::platform::dynload::cublasSgeam
-#define CUBLAS_GEMV paddle::platform::dynload::cublasSgemv
-#define CUBLAS_GEMM paddle::platform::dynload::cublasSgemm
-#define CUBLAS_GETRF paddle::platform::dynload::cublasSgetrfBatched
-#define CUBLAS_GETRI paddle::platform::dynload::cublasSgetriBatched
-#else
-#define CUBLAS_GEAM paddle::platform::dynload::cublasDgeam
-#define CUBLAS_GEMV paddle::platform::dynload::cublasDgemv
-#define CUBLAS_GEMM paddle::platform::dynload::cublasDgemm
-#define CUBLAS_GETRF paddle::platform::dynload::cublasDgetrfBatched
-#define CUBLAS_GETRI paddle::platform::dynload::cublasDgetriBatched
-#endif
+#undef DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP
 }  // namespace dynload
 }  // namespace platform
 }  // namespace paddle

paddle/platform/dynload/cudnn.cc

+#include <paddle/platform/dynload/cudnn.h>
+
+namespace paddle {
+namespace platform {
+namespace dynload {
+std::once_flag cudnn_dso_flag;
+void* cudnn_dso_handle = nullptr;
+
+#define DEFINE_WRAP(__name) DynLoad__##__name __name
+
+CUDNN_DNN_ROUTINE_EACH(DEFINE_WRAP);
+CUDNN_DNN_ROUTINE_EACH_R2(DEFINE_WRAP);
+
+#ifdef CUDNN_DNN_ROUTINE_EACH_AFTER_R3
+CUDNN_DNN_ROUTINE_EACH_AFTER_R3(DEFINE_WRAP);
+#endif
+
+#ifdef CUDNN_DNN_ROUTINE_EACH_AFTER_R4
+CUDNN_DNN_ROUTINE_EACH_AFTER_R4(DEFINE_WRAP);
+#endif
+
+#ifdef CUDNN_DNN_ROUTINE_EACH_R5
+CUDNN_DNN_ROUTINE_EACH_R5(DEFINE_WRAP);
+#endif
+
+}  // namespace dynload
+}  // namespace platform
+}  // namespace paddle
\ No newline at end of file

paddle/platform/dynload/cudnn.h

@@ -23,12 +23,12 @@ namespace paddle {
 namespace platform {
 namespace dynload {
 
-std::once_flag cudnn_dso_flag;
-void* cudnn_dso_handle = nullptr;
+extern std::once_flag cudnn_dso_flag;
+extern void* cudnn_dso_handle;
 
 #ifdef PADDLE_USE_DSO
 
-#define DYNAMIC_LOAD_CUDNN_WRAP(__name)                            \
+#define DECLARE_DYNAMIC_LOAD_CUDNN_WRAP(__name)                    \
   struct DynLoad__##__name {                                       \
     template <typename... Args>                                    \
     auto operator()(Args... args) -> decltype(__name(args...)) {   \
@@ -39,17 +39,19 @@ void* cudnn_dso_handle = nullptr;
       void* p_##__name = dlsym(cudnn_dso_handle, #__name);         \
       return reinterpret_cast<cudnn_func>(p_##__name)(args...);    \
     }                                                              \
-  } __name; /* struct DynLoad__##__name */
+  };                                                               \
+  extern struct DynLoad__##__name __name
 
 #else
 
-#define DYNAMIC_LOAD_CUDNN_WRAP(__name)                          \
+#define DECLARE_DYNAMIC_LOAD_CUDNN_WRAP(__name)                  \
   struct DynLoad__##__name {                                     \
     template <typename... Args>                                  \
     auto operator()(Args... args) -> decltype(__name(args...)) { \
       return __name(args...);                                    \
     }                                                            \
-  } __name; /* struct DynLoad__##__name */
+  };                                                             \
+  extern DynLoad__##__name __name
 
 #endif
 
@@ -57,80 +59,73 @@ void* cudnn_dso_handle = nullptr;
  * include all needed cudnn functions in HPPL
  * different cudnn version has different interfaces
  **/
-// clang-format off
-#define CUDNN_DNN_ROUTINE_EACH(__macro)                   \
-  __macro(cudnnSetTensor4dDescriptor)                     \
-  __macro(cudnnSetTensor4dDescriptorEx)                   \
-  __macro(cudnnGetConvolutionNdForwardOutputDim)          \
-  __macro(cudnnGetConvolutionForwardAlgorithm)            \
-  __macro(cudnnCreateTensorDescriptor)                    \
-  __macro(cudnnDestroyTensorDescriptor)                   \
-  __macro(cudnnCreateFilterDescriptor)                    \
-  __macro(cudnnSetFilter4dDescriptor)                     \
-  __macro(cudnnSetPooling2dDescriptor)                    \
-  __macro(cudnnDestroyFilterDescriptor)                   \
-  __macro(cudnnCreateConvolutionDescriptor)               \
-  __macro(cudnnCreatePoolingDescriptor)                   \
-  __macro(cudnnDestroyPoolingDescriptor)                  \
-  __macro(cudnnSetConvolution2dDescriptor)                \
-  __macro(cudnnDestroyConvolutionDescriptor)              \
-  __macro(cudnnCreate)                                    \
-  __macro(cudnnDestroy)                                   \
-  __macro(cudnnSetStream)                                 \
-  __macro(cudnnActivationForward)                         \
-  __macro(cudnnConvolutionForward)                        \
-  __macro(cudnnConvolutionBackwardBias)                   \
-  __macro(cudnnGetConvolutionForwardWorkspaceSize)        \
-  __macro(cudnnTransformTensor)                           \
-  __macro(cudnnPoolingForward)                            \
-  __macro(cudnnPoolingBackward)                           \
-  __macro(cudnnSoftmaxBackward)                           \
-  __macro(cudnnSoftmaxForward)                            \
-  __macro(cudnnGetVersion)                                \
-  __macro(cudnnGetErrorString)
-CUDNN_DNN_ROUTINE_EACH(DYNAMIC_LOAD_CUDNN_WRAP)
-
-#define CUDNN_DNN_ROUTINE_EACH_R2(__macro)                \
-  __macro(cudnnAddTensor)                                 \
-  __macro(cudnnConvolutionBackwardData)                   \
-  __macro(cudnnConvolutionBackwardFilter)
-CUDNN_DNN_ROUTINE_EACH_R2(DYNAMIC_LOAD_CUDNN_WRAP)
+#define CUDNN_DNN_ROUTINE_EACH(__macro)             \
+  __macro(cudnnSetTensor4dDescriptor);              \
+  __macro(cudnnSetTensor4dDescriptorEx);            \
+  __macro(cudnnGetConvolutionNdForwardOutputDim);   \
+  __macro(cudnnGetConvolutionForwardAlgorithm);     \
+  __macro(cudnnCreateTensorDescriptor);             \
+  __macro(cudnnDestroyTensorDescriptor);            \
+  __macro(cudnnCreateFilterDescriptor);             \
+  __macro(cudnnSetFilter4dDescriptor);              \
+  __macro(cudnnSetPooling2dDescriptor);             \
+  __macro(cudnnDestroyFilterDescriptor);            \
+  __macro(cudnnCreateConvolutionDescriptor);        \
+  __macro(cudnnCreatePoolingDescriptor);            \
+  __macro(cudnnDestroyPoolingDescriptor);           \
+  __macro(cudnnSetConvolution2dDescriptor);         \
+  __macro(cudnnDestroyConvolutionDescriptor);       \
+  __macro(cudnnCreate);                             \
+  __macro(cudnnDestroy);                            \
+  __macro(cudnnSetStream);                          \
+  __macro(cudnnActivationForward);                  \
+  __macro(cudnnConvolutionForward);                 \
+  __macro(cudnnConvolutionBackwardBias);            \
+  __macro(cudnnGetConvolutionForwardWorkspaceSize); \
+  __macro(cudnnTransformTensor);                    \
+  __macro(cudnnPoolingForward);                     \
+  __macro(cudnnPoolingBackward);                    \
+  __macro(cudnnSoftmaxBackward);                    \
+  __macro(cudnnSoftmaxForward);                     \
+  __macro(cudnnGetVersion);                         \
+  __macro(cudnnGetErrorString);
+CUDNN_DNN_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
+
+#define CUDNN_DNN_ROUTINE_EACH_R2(__macro) \
+  __macro(cudnnAddTensor);                 \
+  __macro(cudnnConvolutionBackwardData);   \
+  __macro(cudnnConvolutionBackwardFilter);
+CUDNN_DNN_ROUTINE_EACH_R2(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
 
 // APIs available after R3:
 #if CUDNN_VERSION >= 3000
-#define CUDNN_DNN_ROUTINE_EACH_AFTER_R3(__macro)              \
-  __macro(cudnnGetConvolutionBackwardFilterWorkspaceSize)     \
-  __macro(cudnnGetConvolutionBackwardDataAlgorithm)           \
-  __macro(cudnnGetConvolutionBackwardFilterAlgorithm)         \
-  __macro(cudnnGetConvolutionBackwardDataWorkspaceSize)
-CUDNN_DNN_ROUTINE_EACH_AFTER_R3(DYNAMIC_LOAD_CUDNN_WRAP)
-#undef CUDNN_DNN_ROUTINE_EACH_AFTER_R3
+#define CUDNN_DNN_ROUTINE_EACH_AFTER_R3(__macro)           \
+  __macro(cudnnGetConvolutionBackwardFilterWorkspaceSize); \
+  __macro(cudnnGetConvolutionBackwardDataAlgorithm);       \
+  __macro(cudnnGetConvolutionBackwardFilterAlgorithm);     \
+  __macro(cudnnGetConvolutionBackwardDataWorkspaceSize);
+CUDNN_DNN_ROUTINE_EACH_AFTER_R3(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
 #endif
 
-
 // APIs available after R4:
 #if CUDNN_VERSION >= 4007
-#define CUDNN_DNN_ROUTINE_EACH_AFTER_R4(__macro)             \
-  __macro(cudnnBatchNormalizationForwardTraining)            \
-  __macro(cudnnBatchNormalizationForwardInference)           \
-  __macro(cudnnBatchNormalizationBackward)
-CUDNN_DNN_ROUTINE_EACH_AFTER_R4(DYNAMIC_LOAD_CUDNN_WRAP)
-#undef CUDNN_DNN_ROUTINE_EACH_AFTER_R4
+#define CUDNN_DNN_ROUTINE_EACH_AFTER_R4(__macro)    \
+  __macro(cudnnBatchNormalizationForwardTraining);  \
+  __macro(cudnnBatchNormalizationForwardInference); \
+  __macro(cudnnBatchNormalizationBackward);
+CUDNN_DNN_ROUTINE_EACH_AFTER_R4(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
 #endif
 
 // APIs in R5
 #if CUDNN_VERSION >= 5000
-#define CUDNN_DNN_ROUTINE_EACH_R5(__macro)                    \
-  __macro(cudnnCreateActivationDescriptor)                    \
-  __macro(cudnnSetActivationDescriptor)                       \
-  __macro(cudnnGetActivationDescriptor)                       \
-  __macro(cudnnDestroyActivationDescriptor)
-CUDNN_DNN_ROUTINE_EACH_R5(DYNAMIC_LOAD_CUDNN_WRAP)
-#undef CUDNN_DNN_ROUTINE_EACH_R5
+#define CUDNN_DNN_ROUTINE_EACH_R5(__macro)  \
+  __macro(cudnnCreateActivationDescriptor); \
+  __macro(cudnnSetActivationDescriptor);    \
+  __macro(cudnnGetActivationDescriptor);    \
+  __macro(cudnnDestroyActivationDescriptor);
+CUDNN_DNN_ROUTINE_EACH_R5(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
 #endif
 
-#undef CUDNN_DNN_ROUTINE_EACH
-// clang-format on
 }  // namespace dynload
 }  // namespace platform
 }  // namespace paddle

paddle/platform/dynload/curand.cc

+#include <paddle/platform/dynload/curand.h>
+
+namespace paddle {
+namespace platform {
+namespace dynload {
+
+std::once_flag curand_dso_flag;
+void *curand_dso_handle;
+
+#define DEFINE_WRAP(__name) DynLoad__##__name __name
+
+CURAND_RAND_ROUTINE_EACH(DEFINE_WRAP);
+}
+}
+}
\ No newline at end of file

paddle/platform/dynload/curand.h

@@ -22,10 +22,10 @@ limitations under the License. */
 namespace paddle {
 namespace platform {
 namespace dynload {
-std::once_flag curand_dso_flag;
-void *curand_dso_handle = nullptr;
+extern std::once_flag curand_dso_flag;
+extern void *curand_dso_handle;
 #ifdef PADDLE_USE_DSO
-#define DYNAMIC_LOAD_CURAND_WRAP(__name)                            \
+#define DECLARE_DYNAMIC_LOAD_CURAND_WRAP(__name)                    \
   struct DynLoad__##__name {                                        \
     template <typename... Args>                                     \
     curandStatus_t operator()(Args... args) {                       \
@@ -36,32 +36,29 @@ void *curand_dso_handle = nullptr;
       void *p_##__name = dlsym(curand_dso_handle, #__name);         \
       return reinterpret_cast<curandFunc>(p_##__name)(args...);     \
     }                                                               \
-  } __name; /* struct DynLoad__##__name */
+  };                                                                \
+  extern DynLoad__##__name __name
 #else
-#define DYNAMIC_LOAD_CURAND_WRAP(__name)      \
-  struct DynLoad__##__name {                  \
-    template <typename... Args>               \
-    curandStatus_t operator()(Args... args) { \
-      return __name(args...);                 \
-    }                                         \
-  } __name; /* struct DynLoad__##__name */
+#define DECLARE_DYNAMIC_LOAD_CURAND_WRAP(__name) \
+  struct DynLoad__##__name {                     \
+    template <typename... Args>                  \
+    curandStatus_t operator()(Args... args) {    \
+      return __name(args...);                    \
+    }                                            \
+  };                                             \
+  extern DynLoad__##__name __name
 #endif
 
-/* include all needed curand functions in HPPL */
-// clang-format off
-#define CURAND_RAND_ROUTINE_EACH(__macro)    \
-  __macro(curandCreateGenerator)             \
-  __macro(curandSetStream)                   \
-  __macro(curandSetPseudoRandomGeneratorSeed)\
-  __macro(curandGenerateUniform)             \
-  __macro(curandGenerateUniformDouble)       \
-  __macro(curandDestroyGenerator)
-// clang-format on
+#define CURAND_RAND_ROUTINE_EACH(__macro)      \
+  __macro(curandCreateGenerator);              \
+  __macro(curandSetStream);                    \
+  __macro(curandSetPseudoRandomGeneratorSeed); \
+  __macro(curandGenerateUniform);              \
+  __macro(curandGenerateUniformDouble);        \
+  __macro(curandDestroyGenerator);
 
-CURAND_RAND_ROUTINE_EACH(DYNAMIC_LOAD_CURAND_WRAP)
+CURAND_RAND_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CURAND_WRAP);
 
-#undef CURAND_RAND_ROUTINE_EACH
-#undef DYNAMIC_LOAD_CURAND_WRAP
 }  // namespace dynload
 }  // namespace platform
 }  // namespace paddle

paddle/pybind/CMakeLists.txt

+cc_library(paddle_pybind SHARED SRCS pybind.cc DEPS pybind python)

paddle/pybind/pybind.cc

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include <Python.h>
+#include <paddle/framework/scope.h>
+#include <pybind11/pybind11.h>
+
+namespace py = pybind11;
+namespace pd = paddle::framework;
+
+PYBIND11_PLUGIN(core) {
+  py::module m("core", "C++ core of Paddle Paddle");
+
+  py::class_<pd::Variable>(m, "Variable", R"DOC(Variable Class.
+
+All parameter, weight, gradient are variables in Paddle.
+)DOC")
+      .def("is_int", [](const pd::Variable& var) { return var.IsType<int>(); })
+      .def("set_int",
+           [](pd::Variable& var, int val) -> void {
+             *var.GetMutable<int>() = val;
+           })
+      .def("get_int",
+           [](const pd::Variable& var) -> int { return var.Get<int>(); });
+
+  py::class_<pd::Scope, std::shared_ptr<pd::Scope>>(m, "Scope")
+      .def(py::init<const std::shared_ptr<pd::Scope>&>())
+      .def("get_var",
+           &pd::Scope::GetVariable,
+           py::return_value_policy::reference)
+      .def("create_var",
+           &pd::Scope::CreateVariable,
+           py::return_value_policy::reference);
+
+  return m.ptr();
+}

paddle/scripts/travis/build_android.sh

+#!/bin/bash
+set -e
+
+ANDROID_STANDALONE_TOOLCHAIN=$HOME/android-toolchain-gcc
+TMP_DIR=$HOME/$JOB/tmp
+mkdir -p $TMP_DIR
+cd $TMP_DIR
+wget -q https://dl.google.com/android/repository/android-ndk-r14b-linux-x86_64.zip
+unzip -q android-ndk-r14b-linux-x86_64.zip
+chmod +x $TMP_DIR/android-ndk-r14b/build/tools/make-standalone-toolchain.sh
+$TMP_DIR/android-ndk-r14b/build/tools/make-standalone-toolchain.sh --force --arch=arm --platform=android-21 --install-dir=$ANDROID_STANDALONE_TOOLCHAIN
+cd $HOME
+rm -rf $TMP_DIR
+
+# Create the build directory for CMake.
+mkdir -p $TRAVIS_BUILD_DIR/build_android
+cd $TRAVIS_BUILD_DIR/build_android
+
+# Compile paddle binaries
+cmake -DCMAKE_SYSTEM_NAME=Android \
+      -DANDROID_STANDALONE_TOOLCHAIN=$ANDROID_STANDALONE_TOOLCHAIN \
+      -DANDROID_ABI=armeabi-v7a \
+      -DANDROID_ARM_NEON=ON \
+      -DANDROID_ARM_MODE=ON \
+      -DWITH_C_API=ON \
+      -DWITH_SWIG_PY=OFF \
+      -DWITH_STYLE_CHECK=OFF \
+      ..
+
+make -j `nproc`

paddle/trainer/NewRemoteParameterUpdater.cpp

@@ -22,7 +22,8 @@ DECLARE_string(save_dir);
 namespace paddle {
 NewRemoteParameterUpdater::NewRemoteParameterUpdater(
     const OptimizationConfig &config, const std::string pserverSpec)
-    : parameterClient_(-1),
+    : trainerConfig_(config),
+      parameterClient_(-1),
       newParameters_(nullptr),
       newGradients_(nullptr),
       pserverSpec_(pserverSpec) {}
@@ -51,7 +52,22 @@ void NewRemoteParameterUpdater::init(
     LOG(INFO) << "paddle_begin_init_params start";
     for (int i = 0; i < parameterSize(); ++i) {
       auto paramConfig = parameters_[i]->getConfig();
-      std::string bytes = paramConfig.SerializeAsString();
+      LOG(INFO) << "old param config: " << paramConfig.DebugString();
+      // FIXME(typhoonzero): convert old paramConfig to optimizerConfig
+      OptimizerConfig optimizeConfigV2;
+      auto sgdConfigV2 = optimizeConfigV2.mutable_sgd();
+      sgdConfigV2->set_momentum(paramConfig.momentum());
+      sgdConfigV2->set_decay(paramConfig.decay_rate());
+      optimizeConfigV2.set_lr_policy(paddle::OptimizerConfig::Const);
+      auto constlr = optimizeConfigV2.mutable_const_lr();
+      constlr->set_learning_rate(paramConfig.learning_rate());
+      if (trainerConfig_.algorithm() == "sgd") {
+        optimizeConfigV2.set_optimizer(paddle::OptimizerConfig::SGD);
+        // FIXME: config all algorithms
+      } else {
+        optimizeConfigV2.set_optimizer(paddle::OptimizerConfig::SGD);
+      }
+      std::string bytes = optimizeConfigV2.SerializeAsString();
       const char *array = bytes.data();
       int size = (int)bytes.size();
       paddle_init_param(
@@ -83,4 +99,4 @@ void NewRemoteParameterUpdater::finishBatch(real cost) {
 void NewRemoteParameterUpdater::startPass() {}
 
 bool NewRemoteParameterUpdater::finishPass() { return true; }
-}
+}  // namespace paddle

paddle/trainer/NewRemoteParameterUpdater.h

@@ -16,6 +16,7 @@ limitations under the License. */
 
 #include <functional>
 #include <thread>
+#include "OptimizerConfig.pb.h"
 #include "ParameterUpdater.h"
 #include "libpaddle_pserver_cclient.h"
 #include "paddle/pserver/ParameterClient2.h"
@@ -101,6 +102,7 @@ private:
   }
 
 protected:
+  const OptimizationConfig& trainerConfig_;
   /// internal parameter client object for exchanging data with pserver
   paddle_pserver_client parameterClient_;
   /// the parameters for new pserver client

python/CMakeLists.txt

@@ -26,10 +26,17 @@ endif(WITH_GOLANG)
 configure_file(${CMAKE_CURRENT_SOURCE_DIR}/setup.py.in
     ${CMAKE_CURRENT_BINARY_DIR}/setup.py)
 
+
+add_custom_command(OUTPUT ${PROJ_ROOT}/python/paddle/v2/framework/core.so
+        COMMAND cmake -E copy $<TARGET_FILE:paddle_pybind> ${PROJ_ROOT}/python/paddle/v2/framework/core.so
+        DEPENDS paddle_pybind)
+add_custom_target(copy_paddle_pybind ALL DEPENDS ${PROJ_ROOT}/python/paddle/v2/framework/core.so)
+
+
 add_custom_command(OUTPUT ${OUTPUT_DIR}/.timestamp
     COMMAND env ${py_env} ${PYTHON_EXECUTABLE} setup.py bdist_wheel
     COMMAND ${CMAKE_COMMAND} -E touch ${OUTPUT_DIR}/.timestamp
-    DEPENDS gen_proto_py framework_py_proto ${PY_FILES} ${external_project_dependencies} ${COPY_PADDLE_MASTER})
+    DEPENDS gen_proto_py copy_paddle_pybind framework_py_proto ${PY_FILES} ${external_project_dependencies} ${COPY_PADDLE_MASTER})
 
 add_custom_target(paddle_python ALL DEPENDS
     ${OUTPUT_DIR}/.timestamp)

python/paddle/v2/framework/default_scope_funcs.py

+"""
+Default scope function.
+
+`Paddle` manages Scope as programming language's scope.  It just a 
+thread-local stack of Scope. Top of that stack is current scope, the bottom 
+of that stack is all scopes' parent. 
+
+Invoking `create_var/get_var`  can `create/get` variable in current scope. 
+Invoking `enter_local_scope/leave_local_scope` can create or destroy local 
+scope. 
+
+A `scoped_function` will take a `function` as input. That function will be 
+invoked in a new local scope. 
+"""
+
+import paddle.v2.framework.core
+import threading
+
+__tl_scope__ = threading.local()
+
+__all__ = [
+    'get_cur_scope', 'enter_local_scope', 'leave_local_scope', 'create_var',
+    'get_var', 'scoped_function'
+]
+
+
+def get_cur_scope():
+    """
+    Get current scope.
+    :rtype: paddle.v2.framework.core.Scope
+    """
+    cur_scope_stack = getattr(__tl_scope__, 'cur_scope', None)
+    if cur_scope_stack is None:
+        __tl_scope__.cur_scope = list()
+    if len(__tl_scope__.cur_scope) == 0:
+        __tl_scope__.cur_scope.append(paddle.v2.framework.core.Scope(None))
+    return __tl_scope__.cur_scope[-1]
+
+
+def enter_local_scope():
+    """
+    Enter a new local scope
+    """
+    cur_scope = get_cur_scope()
+    new_scope = paddle.v2.framework.core.Scope(cur_scope)
+    __tl_scope__.cur_scope.append(new_scope)
+
+
+def leave_local_scope():
+    """
+    Leave local scope
+    """
+    __tl_scope__.cur_scope.pop()
+
+
+def create_var(name):
+    """
+    create variable in current scope.
+    """
+    return get_cur_scope().create_var(name)
+
+
+def get_var(name):
+    """
+    get variable in current scope.
+    """
+    return get_cur_scope().get_var(name)
+
+
+def scoped_function(func):
+    """
+    invoke `func` in new scope.
+    
+    :param func: a callable function that will be run in new scope.
+    :type func: callable
+    """
+    enter_local_scope()
+    try:
+        func()
+    except:
+        raise
+    finally:
+        leave_local_scope()

python/paddle/v2/framework/tests/CMakeLists.txt

-add_python_test(test_framework test_protobuf.py)
+add_python_test(test_framework test_protobuf.py test_scope.py
+    test_default_scope_funcs.py)

python/paddle/v2/framework/tests/test_default_scope_funcs.py

+from paddle.v2.framework.default_scope_funcs import *
+import unittest
+
+
+class TestDefaultScopeFuncs(unittest.TestCase):
+    def test_cur_scope(self):
+        self.assertIsNotNone(get_cur_scope())
+
+    def test_none_variable(self):
+        self.assertIsNone(get_var("test"))
+
+    def test_create_var_get_var(self):
+        var_a = create_var("var_a")
+        self.assertIsNotNone(var_a)
+        self.assertIsNotNone(get_cur_scope().get_var('var_a'))
+        enter_local_scope()
+        self.assertIsNotNone(get_cur_scope().get_var('var_a'))
+        leave_local_scope()
+
+    def test_var_get_int(self):
+        def __new_scope__():
+            i = create_var("var_i")
+            self.assertFalse(i.is_int())
+            i.set_int(10)
+            self.assertTrue(i.is_int())
+            self.assertEqual(10, i.get_int())
+
+        for _ in xrange(10):
+            scoped_function(__new_scope__)
+
+
+if __name__ == '__main__':
+    unittest.main()

python/paddle/v2/framework/tests/test_protobuf.py

@@ -24,3 +24,7 @@ class TestFrameworkProto(unittest.TestCase):
         attr.type = attr_type_lib.FLOAT
         op_proto.type = "cos"
         self.assertTrue(op_proto.IsInitialized())
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/v2/framework/tests/test_scope.py

+import paddle.v2.framework.core
+import unittest
+
+
+class TestScope(unittest.TestCase):
+    def test_create_destroy(self):
+        paddle_c = paddle.v2.framework.core
+        scope = paddle_c.Scope(None)
+        self.assertIsNotNone(scope)
+        scope_with_parent = paddle_c.Scope(scope)
+        self.assertIsNotNone(scope_with_parent)
+
+    def test_none_variable(self):
+        paddle_c = paddle.v2.framework.core
+        scope = paddle_c.Scope(None)
+        self.assertIsNone(scope.get_var("test"))
+
+    def test_create_var_get_var(self):
+        paddle_c = paddle.v2.framework.core
+        scope = paddle_c.Scope(None)
+        var_a = scope.create_var("var_a")
+        self.assertIsNotNone(var_a)
+        self.assertIsNotNone(scope.get_var('var_a'))
+        scope2 = paddle_c.Scope(scope)
+        self.assertIsNotNone(scope2.get_var('var_a'))
+
+    def test_var_get_int(self):
+        paddle_c = paddle.v2.framework.core
+        scope = paddle_c.Scope(None)
+        var = scope.create_var("test_int")
+        var.set_int(10)
+        self.assertTrue(var.is_int())
+        self.assertEqual(10, var.get_int())
+
+
+if __name__ == '__main__':
+    unittest.main()

python/paddle/v2/optimizer.py

@@ -66,6 +66,8 @@ class Optimizer(object):
             if use_sparse_remote_updater:
                         gradient_machine.prefetch(in_args)
                         parameter_updater.getParametersRemote()
+
+        :param pserver_spec: pserver location, eg: localhost:3000
         :return: parameter_updater
         """
         if is_local:

python/paddle/v2/trainer.py

@@ -41,6 +41,7 @@ class SGD(object):
     :type parameters: paddle.v2.parameters.Parameters
     :param extra_layers: Some layers in the neural network graph are not
                          in the path of cost layer.
+    :param pserver_spec: pserver location, eg: localhost:3000
     :type extra_layers: paddle.v2.config_base.Layer
     """
 

python/setup.py.in

@@ -29,7 +29,9 @@ setup(name='paddle',
       description='Parallel Distributed Deep Learning',
       install_requires=setup_requires,
       packages=packages,
-      package_data={'paddle.v2.master': ['libpaddle_master.so'], },
+      package_data={'paddle.v2.master': ['libpaddle_master.so'],
+            'paddle.v2.framework': ['core.so']
+      },
       package_dir={
           '': '${CMAKE_CURRENT_SOURCE_DIR}',
           # The paddle.v2.framework.proto will be generated while compiling.