diff --git a/Dockerfile b/Dockerfile index 156ad3552b2c4ff90b405c35c66d44117c2624a4..0f0d14503c31afbbfcd568a7785a13e849aec408 100644 --- a/Dockerfile +++ b/Dockerfile @@ -38,12 +38,11 @@ RUN apt-get update && \ RUN pip --no-cache-dir install 'numpy>=1.12.0' # Install Go and glide -RUN wget -O go.tgz https://storage.googleapis.com/golang/go1.8.1.linux-amd64.tar.gz && \ - tar -C /usr/local -xzf go.tgz && \ +RUN wget -qO- https://storage.googleapis.com/golang/go1.8.1.linux-amd64.tar.gz | \ + tar -xz -C /usr/local && \ mkdir /root/gopath && \ mkdir /root/gopath/bin && \ - mkdir /root/gopath/src && \ - rm go.tgz + mkdir /root/gopath/src ENV GOROOT=/usr/local/go GOPATH=/root/gopath # should not be in the same line with GOROOT definition, otherwise docker build could not find GOROOT. ENV PATH=${PATH}:${GOROOT}/bin:${GOPATH}/bin diff --git a/cmake/external/any.cmake b/cmake/external/any.cmake index 5d2f7219b2007493916a39e839d647a9d0046c9f..85cce80b70a1fcf57015ac7a264e4950616b2717 100644 --- a/cmake/external/any.cmake +++ b/cmake/external/any.cmake @@ -8,7 +8,7 @@ ExternalProject_Add( extern_lib_any ${EXTERNAL_PROJECT_LOG_ARGS} GIT_REPOSITORY "https://github.com/PaddlePaddle/any.git" - GIT_TAG "8fef1e93710a0edf8d7658999e284a1142c4c020" + GIT_TAG "15595d8324be9e8a9a80d9ae442fdd12bd66df5d" PREFIX ${ANY_SOURCE_DIR} UPDATE_COMMAND "" CONFIGURE_COMMAND "" diff --git a/cmake/external/mklml.cmake b/cmake/external/mklml.cmake index 17a1ca4ed04dce85ae3c7fdd5f22d6eeed03db59..e9fd3d4bedc983ae7c544cf289dc841cf22f9de4 100644 --- a/cmake/external/mklml.cmake +++ b/cmake/external/mklml.cmake @@ -17,7 +17,7 @@ IF(NOT ${WITH_MKLML}) ENDIF(NOT ${WITH_MKLML}) IF(WIN32 OR APPLE) - MESSAGE(WARNING + MESSAGE(WARNING "Windows or Mac is not supported with MKLML in Paddle yet." "Force WITH_MKLML=OFF") SET(WITH_MKLML OFF CACHE STRING "Disable MKLML package in Windows and MacOS" FORCE) @@ -43,22 +43,21 @@ SET(CMAKE_INSTALL_RPATH "${CMAKE_INSTALL_RPATH}" "${MKLML_ROOT}/lib") INCLUDE_DIRECTORIES(${MKLML_INC_DIR}) -SET(mklml_cmakefile ${MKLML_DOWNLOAD_DIR}/CMakeLists.txt) -FILE(WRITE ${mklml_cmakefile} "PROJECT(MKLML)\n" - "cmake_minimum_required(VERSION 3.0)\n" - "install(DIRECTORY ${MKLML_VER}\n" - " DESTINATION ${MKLML_DST_DIR})\n") +FILE(WRITE ${MKLML_DOWNLOAD_DIR}/CMakeLists.txt + "PROJECT(MKLML)\n" + "cmake_minimum_required(VERSION 3.0)\n" + "install(DIRECTORY ${MKLML_VER}\n" + " DESTINATION ${MKLML_DST_DIR})\n") ExternalProject_Add( ${MKLML_PROJECT} ${EXTERNAL_PROJECT_LOG_ARGS} PREFIX ${MKLML_SOURCE_DIR} DOWNLOAD_DIR ${MKLML_DOWNLOAD_DIR} - DOWNLOAD_COMMAND wget --no-check-certificate -O ${MKLML_DOWNLOAD_DIR}/${MKLML_VER}.tgz ${MKLML_URL} - && tar -xzf ${MKLML_DOWNLOAD_DIR}/${MKLML_VER}.tgz + DOWNLOAD_COMMAND wget --no-check-certificate -qO- ${MKLML_URL} | tar xz -C ${MKLML_DOWNLOAD_DIR} DOWNLOAD_NO_PROGRESS 1 UPDATE_COMMAND "" - CMAKE_ARGS -DCMAKE_INSTALL_PREFIX=${MKLML_INSTALL_ROOT} + CMAKE_ARGS -DCMAKE_INSTALL_PREFIX=${MKLML_INSTALL_ROOT} CMAKE_CACHE_ARGS -DCMAKE_INSTALL_PREFIX:PATH=${MKLML_INSTALL_ROOT} ) diff --git a/doc/getstarted/build_and_install/docker_install_cn.rst b/doc/getstarted/build_and_install/docker_install_cn.rst index 87c286a1af75e08313813f1373ea03b85d4af523..02b96bb413156786db6dc77696c5640b97c10aa4 100644 --- a/doc/getstarted/build_and_install/docker_install_cn.rst +++ b/doc/getstarted/build_and_install/docker_install_cn.rst @@ -3,6 +3,43 @@ PaddlePaddle的Docker容器使用方式 PaddlePaddle目前唯一官方支持的运行的方式是Docker容器。因为Docker能在所有主要操作系统（包括Linux，Mac OS X和Windows）上运行。 请注意，您需要更改 `Dockers设置 `_ 才能充分利用Mac OS X和Windows上的硬件资源。 +Docker使用入门 +------------------------------ + +几个基础的概念帮助理解和使用Docker： + +- *镜像*：一个Docker镜像是一个打包好的软件。它包含了这个软件本身和它所依赖的运行环境。PaddlePaddle的Docker镜像就包含了PaddlePaddle的Python库以及其依赖的多个Python库。这样我们可以直接在Docker中运行需要的程序而不需要安装后在执行。可以执行： + + .. code-block:: bash + + docker images + + 来列出当前系统中的所有镜像，同样可以执行： + + .. code-block:: bash + + docker pull paddlepaddle/paddle:0.10.0 + + 来下载Docker镜像，paddlepaddle/paddle是从官方镜像源Dockerhub.com下载的，推荐国内用户使用ocker.paddlepaddle.org/paddle下载。 + +- *容器*： 如果说一个Docker镜像就是一个程序，那容器就是这个程序运行时产生的“进程”。 + 实际上，一个容器就是一个操作系统的进程，但是是运行在独立的进程空间，文件系统以及网络之上。 + 可以执行： + + .. code-block:: bash + + docker run paddlepaddle/paddle:0.10.0 + + 来使用一个镜像启动一个容器。 + +- 默认情况下，Docker容器会运行在独立的文件系统空间之上，我们无法在Docker容器中 + 访问到主机上的文件。可以通过*挂载Volume*的方式，将主机上的文件或目录挂载到 + Docker容器中。下面的命令把当前目录挂载到了容器中的 /data 目录下，容器使用 + debian镜像，并且启动后执行 :code:`ls /data`。 + + .. code-block:: bash + + docker run --rm -v $(pwd):/data debian ls /data PaddlePaddle发布的Docker镜像使用说明 ------------------------------ @@ -12,11 +49,11 @@ PaddlePaddle需要的所有编译工具。把编译出来的PaddlePaddle也打 像，称为生产镜像，里面涵盖了PaddlePaddle运行所需的所有环境。每次 PaddlePaddle发布新版本的时候都会发布对应版本的生产镜像以及开发镜像。运 行镜像包括纯CPU版本和GPU版本以及其对应的非AVX版本。我们会在 -`dockerhub.com `_ 提供最新 -的Docker镜像，可以在"tags"标签下找到最新的Paddle镜像版本。为了方便在国 -内的开发者下载Docker镜像，我们提供了国内的镜像服务器供大家使用。如果您 -在国内，请把文档里命令中的paddlepaddle/paddle替换成 -docker.paddlepaddle.org/paddle。 +`dockerhub.com `_ +和国内镜像`docker.paddlepaddle.org` 提供最新 +的Docker镜像，可以在"tags"标签下找到最新的Paddle镜像版本。 + +**注意：为了方便在国内的开发者下载Docker镜像，我们提供了国内的镜像服务器供大家使用。如果您在国内，请把文档里命令中的paddlepaddle/paddle替换成docker.paddlepaddle.org/paddle。** 1. 开发镜像：:code:`paddlepaddle/paddle:0.10.0-dev` @@ -68,6 +105,8 @@ docker.paddlepaddle.org/paddle。 如果输出是No，就需要选择使用no-AVX的镜像 + **注：在0.10.0之后的版本，PaddlePaddle都可以自动判断硬件是否支持AVX，所以无需判断AVX即可使用** + 以上方法在GPU镜像里也能用，只是请不要忘记提前在物理机上安装GPU最新驱动。 为了保证GPU驱动能够在镜像里面正常运行，我们推荐使用[nvidia-docker](https://github.com/NVIDIA/nvidia-docker)来运行镜像。 diff --git a/doc/getstarted/build_and_install/docker_install_en.rst b/doc/getstarted/build_and_install/docker_install_en.rst index b6fd3329b273aabe80edd5f1ff064a311648b3c2..94860240f6a4a9bed8a865684a8a79960489280e 100644 --- a/doc/getstarted/build_and_install/docker_install_en.rst +++ b/doc/getstarted/build_and_install/docker_install_en.rst @@ -63,12 +63,35 @@ CPU-only version and a CUDA GPU version and their no-AVX versions. We put the docker images on `dockerhub.com `_. You can find the -latest versions under "tags" tab at dockerhub.com. If you are in -China, you can use our Docker image registry mirror to speed up the -download process. To use it, please replace all paddlepaddle/paddle in -the commands to docker.paddlepaddle.org/paddle. +latest versions under "tags" tab at dockerhub.com. -1. Production images, this image might have multiple variants: +** NOTE: If you are in China, you can use our Docker image registry mirror to speed up the download process. To use it, please replace all paddlepaddle/paddle in the commands to docker.paddlepaddle.org/paddle.** + + +1. development image :code:`paddlepaddle/paddle:-dev` + + This image has packed related develop tools and runtime + environment. Users and developers can use this image instead of + their own local computer to accomplish development, build, + releasing, document writing etc. While different version of paddle + may depends on different version of libraries and tools, if you + want to setup a local environment, you must pay attention to the + versions. The development image contains: + + - gcc/clang + - nvcc + - Python + - sphinx + - woboq + - sshd + + Many developers use servers with GPUs, they can use ssh to login to + the server and run :code:`docker exec` to enter the docker + container and start their work. Also they can start a development + docker image with SSHD service, so they can login to the container + and start work. + +2. Production images, this image might have multiple variants: - GPU/AVX：:code:`paddlepaddle/paddle:-gpu` - GPU/no-AVX：:code:`paddlepaddle/paddle:-gpu-noavx` @@ -84,7 +107,7 @@ the commands to docker.paddlepaddle.org/paddle. if cat /proc/cpuinfo | grep -i avx; then echo Yes; else echo No; fi - + **NOTE：versions after 0.10.0 will automatically detect system AVX support, so manual detect is not needed in this case.** To run the CPU-only image as an interactive container: .. code-block:: bash @@ -103,29 +126,6 @@ the commands to docker.paddlepaddle.org/paddle. nvidia-docker run -it --rm paddlepaddle/paddle:0.10.0-gpu /bin/bash -2. development image :code:`paddlepaddle/paddle:-dev` - - This image has packed related develop tools and runtime - environment. Users and developers can use this image instead of - their own local computer to accomplish development, build, - releasing, document writing etc. While different version of paddle - may depends on different version of libraries and tools, if you - want to setup a local environment, you must pay attention to the - versions. The development image contains: - - - gcc/clang - - nvcc - - Python - - sphinx - - woboq - - sshd - - Many developers use servers with GPUs, they can use ssh to login to - the server and run :code:`docker exec` to enter the docker - container and start their work. Also they can start a development - docker image with SSHD service, so they can login to the container - and start work. - Train Model Using Python API ---------------------------- diff --git a/go/cmd/pserver/pserver.go b/go/cmd/pserver/pserver.go index f9cd8f87e8f2e715c87834ee08482be0f511f681..bec5775d540729000ab2dd3002600f0a92619d70 100644 --- a/go/cmd/pserver/pserver.go +++ b/go/cmd/pserver/pserver.go @@ -32,7 +32,7 @@ import ( func main() { port := flag.Int("port", 0, "port of the pserver") - index := flag.Int("index", -1, "index of this pserver, should be larger or equal than 0") + index := flag.Int("index", -1, "index of the pserver, set to -1 if use etcd for auto pserver index registry") etcdEndpoint := flag.String("etcd-endpoint", "http://127.0.0.1:2379", "comma separated endpoint string for pserver to connect to etcd") dialTimeout := flag.Duration("dial-timeout", 5*time.Second, "dial timeout") @@ -60,12 +60,12 @@ func main() { idx, err = e.Register(*port) candy.Must(err) - cp, err = pserver.NewCheckpointFromFile(*checkpointPath, idx, e) + cp, err = pserver.LoadCheckpoint(e, idx) if err != nil { if err == pserver.ErrCheckpointNotFound { log.Infof("Could not find the pserver checkpoint.") } else { - log.Errorf("Fetch checkpoint failed, %s", err) + panic(err) } } } diff --git a/go/glide.lock b/go/glide.lock index 1f16abdf66422abcd0ab7987cab3499d02cf1b9c..be1fb24d772a6524cb798c6169c23ff03e9fed7b 100644 --- a/go/glide.lock +++ b/go/glide.lock @@ -1,5 +1,5 @@ -hash: 2a1c0eca5c07a130e3d224f9821f96cfa37a39bf6bce141c855bbc57ef569f1c -updated: 2017-07-29T07:34:48.722757905+08:00 +hash: 1b9b07408ca7fac27a374dc2ccd2433e4bff090484008a037df967284949a582 +updated: 2017-08-03T21:46:51.744995189Z imports: - name: github.com/beorn7/perks version: 4c0e84591b9aa9e6dcfdf3e020114cd81f89d5f9 @@ -145,6 +145,8 @@ imports: version: a1dba9ce8baed984a2495b658c82687f8157b98f subpackages: - xfs +- name: github.com/satori/go.uuid + version: 879c5887cd475cd7864858769793b2ceb0d44feb - name: github.com/sirupsen/logrus version: a3f95b5c423586578a4e099b11a46c2479628cac - name: github.com/topicai/candy diff --git a/go/glide.yaml b/go/glide.yaml index bc23fa6ebf2c3db61e2d63e5f7e7ddcb595dfed0..a90e71b615de92d64c79823e2a04c46001963932 100644 --- a/go/glide.yaml +++ b/go/glide.yaml @@ -14,11 +14,13 @@ import: version: ^1.0.0 - package: github.com/topicai/candy - package: golang.org/x/crypto - vcs: git repo: https://github.com/golang/crypto.git -- package: golang.org/x/sys vcs: git +- package: golang.org/x/sys repo: https://github.com/golang/sys.git -- package: golang.org/x/text vcs: git +- package: golang.org/x/text repo: https://github.com/golang/text.git + vcs: git +- package: github.com/satori/go.uuid + version: v1.1.0 diff --git a/go/master/service.go b/go/master/service.go index d30e9a33229c0aff354417771b5bf2ae6a781715..df7c6860e6ae13a5be7d0425273812208685ee9d 100644 --- a/go/master/service.go +++ b/go/master/service.go @@ -77,11 +77,12 @@ type taskEntry struct { NumFailure int } -type taskQueues struct { +type masterState struct { Todo []taskEntry Pending map[int]taskEntry // map from task ID to task entry Done []taskEntry Failed []taskEntry + CurPass int } // Service is the master server service. @@ -94,11 +95,11 @@ type Service struct { ready chan struct{} initDone bool - mu sync.Mutex - taskQueues taskQueues - currPass int - jobTasks []taskEntry - + mu sync.Mutex + // State to be persisted to snapshot. + state masterState + // The trainer that is currently saving model. This state is + // transient, does not need to be persisted to snapshot. savingTrainer string } @@ -141,8 +142,8 @@ func NewService(store Store, chunksPerTask int, timeoutDur time.Duration, failur s.chunksPerTask = chunksPerTask s.timeoutDur = timeoutDur s.failureMax = failureMax - s.taskQueues = taskQueues{} - s.taskQueues.Pending = make(map[int]taskEntry) + s.state = masterState{} + s.state.Pending = make(map[int]taskEntry) s.ready = make(chan struct{}) s.store = store recovered, err := s.recover() @@ -180,7 +181,7 @@ func (s *Service) recover() (bool, error) { } dec := gob.NewDecoder(gr) - var tqs taskQueues + var tqs masterState err = dec.Decode(&tqs) if err != nil { return false, err @@ -193,7 +194,12 @@ func (s *Service) recover() (bool, error) { log.Errorln(err) } - s.taskQueues = tqs + s.state = tqs + log.WithFields(s.logFields()).Infof("Master recovered from snapshot, scheduling pending task timeout check.") + for _, t := range s.state.Pending { + time.AfterFunc(s.timeoutDur, s.checkTimeoutFunc(t.Task.Meta.ID, t.Task.Meta.Epoch)) + } + return true, nil } @@ -208,7 +214,7 @@ func (s *Service) snapshot() error { var buf bytes.Buffer gw := gzip.NewWriter(&buf) enc := gob.NewEncoder(gw) - err := enc.Encode(s.taskQueues) + err := enc.Encode(s.state) if err != nil { return err } @@ -290,8 +296,7 @@ func (s *Service) SetDataset(globPaths []string, _ *int) error { return err } - s.jobTasks = partition(chunks, s.chunksPerTask) - s.taskQueues.Todo = s.jobTasks + s.state.Todo = partition(chunks, s.chunksPerTask) err = s.snapshot() if err != nil { @@ -319,17 +324,17 @@ func (s *Service) processFailedTask(t taskEntry, epoch int) { } }() - delete(s.taskQueues.Pending, t.Task.Meta.ID) + delete(s.state.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) + s.state.Failed = append(s.state.Failed, t) return } log.Warningf("Task %v failed %d times, re-dispatch.", t.Task, t.NumFailure) - s.taskQueues.Todo = append(s.taskQueues.Todo, t) + s.state.Todo = append(s.state.Todo, t) return } @@ -338,7 +343,7 @@ func (s *Service) checkTimeoutFunc(taskID int, epoch int) func() { s.mu.Lock() defer s.mu.Unlock() - t, ok := s.taskQueues.Pending[taskID] + t, ok := s.state.Pending[taskID] if !ok { return } @@ -350,10 +355,11 @@ func (s *Service) checkTimeoutFunc(taskID int, epoch int) func() { // must be called with lock held. func (s *Service) logFields() log.Fields { return log.Fields{ - "todoLen": len(s.taskQueues.Todo), - "pendingLen": len(s.taskQueues.Pending), - "doneLen": len(s.taskQueues.Done), - "failedLen": len(s.taskQueues.Failed), + "todoLen": len(s.state.Todo), + "pendingLen": len(s.state.Pending), + "doneLen": len(s.state.Done), + "failedLen": len(s.state.Failed), + "curPass": s.state.CurPass, } } @@ -366,17 +372,17 @@ func (s *Service) GetTask(passID int, task *Task) error { s.mu.Lock() defer s.mu.Unlock() - if passID < s.currPass { + if passID < s.state.CurPass { return ErrPassBefore } - if passID > s.currPass { + if passID > s.state.CurPass { // Client may get run to pass after master when one client faster than the // other return ErrPassAfter } - if len(s.taskQueues.Todo) == 0 { - if len(s.taskQueues.Done) == 0 && len(s.taskQueues.Pending) == 0 { + if len(s.state.Todo) == 0 { + if len(s.state.Done) == 0 && len(s.state.Pending) == 0 { log.WithFields(s.logFields()).Warningln("All tasks failed, may start next pass") return ErrAllTaskFailed } @@ -384,10 +390,10 @@ func (s *Service) GetTask(passID int, task *Task) error { return ErrNoMoreAvailable } - t := s.taskQueues.Todo[0] + t := s.state.Todo[0] t.Task.Meta.Epoch++ - s.taskQueues.Todo = s.taskQueues.Todo[1:] - s.taskQueues.Pending[t.Task.Meta.ID] = t + s.state.Todo = s.state.Todo[1:] + s.state.Pending[t.Task.Meta.ID] = t err := s.snapshot() if err != nil { return err @@ -409,7 +415,7 @@ func (s *Service) TaskFinished(taskID int, dummy *int) error { s.mu.Lock() defer s.mu.Unlock() - t, ok := s.taskQueues.Pending[taskID] + t, ok := s.state.Pending[taskID] if !ok { log.WithFields(s.logFields()).Warningln("Pending task #%d not found.", taskID) return nil @@ -417,18 +423,18 @@ func (s *Service) TaskFinished(taskID int, dummy *int) error { // task finished, reset timeout t.NumFailure = 0 - s.taskQueues.Done = append(s.taskQueues.Done, t) - delete(s.taskQueues.Pending, taskID) + s.state.Done = append(s.state.Done, t) + delete(s.state.Pending, taskID) log.WithFields(s.logFields()).Infof("Task #%d finished.", taskID) - if len(s.taskQueues.Todo) == 0 && len(s.taskQueues.Pending) == 0 { + if len(s.state.Todo) == 0 && len(s.state.Pending) == 0 { // increase master side pass count if all tasks finished - s.currPass++ - s.taskQueues.Todo = s.jobTasks - s.taskQueues.Done = []taskEntry{} + s.state.CurPass++ + s.state.Todo = append(s.state.Done, s.state.Failed...) + s.state.Done = []taskEntry{} // TODO(typhoonzero): deal with failed tasks - s.taskQueues.Failed = []taskEntry{} - log.WithFields(s.logFields()).Warningf("all task finished, add new pass data, newpass: %d.", s.currPass) + s.state.Failed = []taskEntry{} + log.WithFields(s.logFields()).Warningf("all task finished, add new pass data, newpass: %d.", s.state.CurPass) } err := s.snapshot() @@ -447,7 +453,7 @@ func (s *Service) TaskFailed(meta TaskMeta, dummy *int) error { s.mu.Lock() defer s.mu.Unlock() - t, ok := s.taskQueues.Pending[meta.ID] + t, ok := s.state.Pending[meta.ID] if !ok { log.WithFields(s.logFields()).Warningln("TaskFailed:Pending task #%v not found.", t.Task.Meta) return nil diff --git a/go/pserver/client/client_test.go b/go/pserver/client/client_test.go index b630d434dca283df67f5b850b35057870fe27529..1243ebd6836550d58144b5033e2755ae8594e948 100644 --- a/go/pserver/client/client_test.go +++ b/go/pserver/client/client_test.go @@ -59,7 +59,7 @@ func initClient() [numPserver]int { go func(l net.Listener) { var cp pserver.Checkpoint - s, err := pserver.NewService(0, 1, "", nil, cp) + s, err := pserver.NewService(0, time.Hour, "", nil, cp) if err != nil { panic(err) } diff --git a/go/pserver/client/etcd_client.go b/go/pserver/client/etcd_client.go index b6ff1fec8a6f37f61f38cb5d004b1d2c886473ed..977ae5af37e2b7d647ae16af9c4403f916b0216d 100644 --- a/go/pserver/client/etcd_client.go +++ b/go/pserver/client/etcd_client.go @@ -103,7 +103,7 @@ func (p *EtcdClient) List() []Server { time.Sleep(p.timeout) continue } - log.Infof("got value (%s) for key: %s", psAddr, psKey) + log.Debugf("got value (%s) for key: %s", psAddr, psKey) servers[i].Index = i servers[i].Addr = psAddr } diff --git a/go/pserver/etcd_client.go b/go/pserver/etcd_client.go index 4fb26307667295ab825d07be6c3d1d4b33f6eb8b..41f0640fc09a3265c0e11c06255c7ee834983203 100644 --- a/go/pserver/etcd_client.go +++ b/go/pserver/etcd_client.go @@ -206,6 +206,7 @@ func (e *EtcdClient) GetKey(key string, timeout time.Duration) ([]byte, error) { if err != nil { return []byte{}, err } + kvs := resp.Kvs if len(kvs) == 0 { return []byte{}, nil @@ -215,9 +216,14 @@ func (e *EtcdClient) GetKey(key string, timeout time.Duration) ([]byte, error) { } // PutKey put into etcd with value by key specified -func (e *EtcdClient) PutKey(key string, value []byte, timeout time.Duration) error { +func (e *EtcdClient) PutKey(key string, value []byte, timeout time.Duration, withLease bool) error { ctx, cancel := context.WithTimeout(context.Background(), timeout) - _, err := e.client.Put(ctx, key, string(value), clientv3.WithLease(e.sess.Lease())) + var err error + if withLease { + _, err = e.client.Put(ctx, key, string(value), clientv3.WithLease(e.sess.Lease())) + } else { + _, err = e.client.Put(ctx, key, string(value)) + } cancel() return err } diff --git a/go/pserver/optimizer.go b/go/pserver/optimizer.go index 709160d45d98b6cf6d60f52ceb3fb33e0a0bd17d..ae7359073494bd9cb6b70b12af4daca064179556 100644 --- a/go/pserver/optimizer.go +++ b/go/pserver/optimizer.go @@ -32,6 +32,7 @@ type optimizer struct { opt *C.struct_paddle_optimizer elementType ElementType contentLen int + config []byte } func cArrayToSlice(p unsafe.Pointer, len int) []byte { @@ -70,6 +71,7 @@ func newOptimizer(paramWithConfigs ParameterWithConfig, State []byte) *optimizer cstate = unsafe.Pointer(&s[0]) } + o.config = c o.opt = C.paddle_create_optimizer((*C.uchar)(&c[0]), C.int(len(c)), C.paddle_element_type(p.ElementType), cbuffer, C.int(paramBufferSize), (*C.char)(cstate), C.int(len(s))) return o diff --git a/go/pserver/service.go b/go/pserver/service.go index 7d297c46d03bf78d18ca9830a318968397119d3e..25751540a9a2dff043c14e0912bfab1aaa938ab4 100644 --- a/go/pserver/service.go +++ b/go/pserver/service.go @@ -25,11 +25,13 @@ import ( "fmt" "io/ioutil" "os" - "path/filepath" + "path" "strconv" "sync" "time" + uuid "github.com/satori/go.uuid" + log "github.com/sirupsen/logrus" ) @@ -42,9 +44,9 @@ var ErrCheckpointNotFound = errors.New("checkpoint not found") // RPC error message. const ( - AlreadyInitialized = "pserver already initialized" - Uninitialized = "pserver not fully initialized" - CheckpointMD5Failed = "checkpoint file MD5 validation failed" + AlreadyInitialized = "pserver already initialized" + Uninitialized = "pserver not fully initialized" + WrongChecksum = "checkpoint file checksum validation failed" ) // Supported element types. @@ -73,11 +75,12 @@ type ParameterWithConfig struct { // checkpointMeta saves checkpoint metadata type checkpointMeta struct { UUID string `json:"uuid"` + Path string `json:"path"` MD5 string `json:"md5"` Timestamp int64 `json:"timestamp"` } -// Checkpoint is the pserver shard persist in file +// Checkpoint is the pserver shard persist in file. type Checkpoint []parameterCheckpoint // Gradient is the gradient of the parameter. @@ -90,50 +93,58 @@ type Service struct { checkpointInterval time.Duration checkpointPath string client *EtcdClient - mu sync.Mutex - optMap map[string]*optimizer + + mu sync.Mutex + optMap map[string]*optimizer } -// parameterCheckpoint saves parameter checkpoint +// 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) +func loadMeta(e *EtcdClient, idx int) (meta checkpointMeta, err error) { + v, err := e.GetKey(PsCheckpoint+strconv.Itoa(idx), 3*time.Second) if err != nil { - return nil, err + return } if len(v) == 0 { - return nil, ErrCheckpointNotFound + err = ErrCheckpointNotFound + return } - var cpMeta checkpointMeta - if err = json.Unmarshal(v, &cpMeta); err != nil { - return nil, err + if err = json.Unmarshal(v, &meta); err != nil { + return } - fn := filepath.Join(cpPath, cpMeta.UUID) - if _, err = os.Stat(fn); os.IsNotExist(err) { + return +} + +// LoadCheckpoint loads checkpoint from file. +func LoadCheckpoint(e *EtcdClient, idx int) (Checkpoint, error) { + cpMeta, err := loadMeta(e, idx) + if err != nil { return nil, err } - content, err := ioutil.ReadFile(fn) + + content, err := ioutil.ReadFile(cpMeta.Path) if err != nil { return nil, err } + // TODO(helin): change MD5 to CRC since CRC is better for file + // checksum in our use case (emphasize speed over security). h := md5.New() md5 := hex.EncodeToString(h.Sum(content)) if md5 != cpMeta.MD5 { - return nil, errors.New(CheckpointMD5Failed) + return nil, errors.New(WrongChecksum) } dec := gob.NewDecoder(bytes.NewReader(content)) - cp := Checkpoint{} - if err = dec.Decode(cp); err != nil { + var cp Checkpoint + if err = dec.Decode(&cp); err != nil { return nil, err } return cp, nil @@ -193,6 +204,15 @@ func (s *Service) FinishInitParams(_ int, _ *int) error { } close(s.initialized) + go func() { + t := time.Tick(s.checkpointInterval) + for range t { + err := s.checkpoint() + if err != nil { + log.Errorln(err) + } + } + }() return nil } @@ -240,23 +260,36 @@ func (s *Service) GetParam(name string, parameter *Parameter) error { return nil } -// pserver save checkpoint -func (s *Service) doCheckpoint() (err error) { - <-s.initialized - s.mu.Lock() - defer s.mu.Unlock() +func traceTime(start time.Time, name string) { + elapsed := time.Since(start) + log.Infof("%s took %v", name, elapsed) +} + +// checkpoint saves checkpoint to disk. +// +// checkpoint should be only called after the parameters are +// initialized. +func (s *Service) checkpoint() (err error) { + log.Infoln("Begin save checkpoint.") + defer traceTime(time.Now(), "save checkpoint") + s.mu.Lock() cp := make([]parameterCheckpoint, len(s.optMap)) index := 0 + // TODO(helin): write checkpoint incrementally to reduce memory + // footprint during checkpoint. for name, opt := range s.optMap { var pc parameterCheckpoint pc.Param.Name = name pc.Param.ElementType = opt.elementType pc.Param.Content = opt.GetWeights() + pc.Config = opt.config pc.State = opt.GetStates() cp[index] = pc index++ } + s.mu.Unlock() + var buf bytes.Buffer encoder := gob.NewEncoder(&buf) err = encoder.Encode(cp) @@ -264,32 +297,9 @@ func (s *Service) doCheckpoint() (err error) { return } - cpMeta := checkpointMeta{} - cpMeta.UUID = s.checkpointPath + strconv.Itoa(s.idx) - cpMeta.Timestamp = time.Now().UnixNano() - h := md5.New() - cpMeta.MD5 = hex.EncodeToString(h.Sum(buf.Bytes())) - - cpMetajson, err := json.Marshal(cpMeta) - if err != nil { - return - } - - err = s.client.PutKey(filepath.Join(PsCheckpoint, strconv.Itoa(s.idx)), cpMetajson, 3*time.Second) - if err != nil { - return - } - if _, err = os.Stat(cpMeta.UUID); os.IsNotExist(err) { - log.Info("checkpoint does not exists.") - } else { - err = os.Remove(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) + id := uuid.NewV4().String() + p := path.Join(s.checkpointPath, id) + f, err := os.Create(p) if err != nil { return } @@ -317,5 +327,43 @@ func (s *Service) doCheckpoint() (err error) { return } + oldMeta, err := loadMeta(s.client, s.idx) + if err == ErrCheckpointNotFound { + log.Infoln("Do not have existing checkpoint.") + err = nil + } + + if err != nil { + return + } + + h := md5.New() + md5 := hex.EncodeToString(h.Sum(buf.Bytes())) + cpMeta := checkpointMeta{ + UUID: id, + Timestamp: time.Now().UnixNano(), + MD5: md5, + Path: p, + } + + json, err := json.Marshal(cpMeta) + if err != nil { + return + } + + err = s.client.PutKey(PsCheckpoint+strconv.Itoa(s.idx), json, 3*time.Second, false) + if err != nil { + return + } + + if oldMeta.Path != "" { + rmErr := os.Remove(oldMeta.Path) + if rmErr != nil { + // log error, but still treat checkpoint as + // successful. + log.Errorln(rmErr) + } + } + return } diff --git a/go/pserver/service_test.go b/go/pserver/service_test.go index 988f3b5acb82a95aeb54af2b8b0e4d39a458291a..be648cd1e83e4f7790edac5842db432fb4870072 100644 --- a/go/pserver/service_test.go +++ b/go/pserver/service_test.go @@ -30,7 +30,7 @@ const ( func TestServiceFull(t *testing.T) { var cp pserver.Checkpoint - s, err := pserver.NewService(0, 1, "", nil, cp) + s, err := pserver.NewService(0, time.Hour, "", nil, cp) if err != nil { t.Error(err) } @@ -102,7 +102,7 @@ func TestServiceFull(t *testing.T) { func TestMultipleInit(t *testing.T) { var cp pserver.Checkpoint - s, err := pserver.NewService(0, 1, "", nil, cp) + s, err := pserver.NewService(0, time.Hour, "", nil, cp) if err != nil { t.Fatal(err) } @@ -119,7 +119,7 @@ func TestMultipleInit(t *testing.T) { func TestUninitialized(t *testing.T) { var cp pserver.Checkpoint - s, err := pserver.NewService(0, 1, "", nil, cp) + s, err := pserver.NewService(0, time.Hour, "", nil, cp) err = s.SendGrad(pserver.Gradient{}, nil) if err.Error() != pserver.Uninitialized { t.Fatal(err) @@ -128,7 +128,7 @@ func TestUninitialized(t *testing.T) { func TestBlockUntilInitialized(t *testing.T) { var cp pserver.Checkpoint - s, err := pserver.NewService(0, 1, "", nil, cp) + s, err := pserver.NewService(0, time.Hour, "", nil, cp) if err != nil { t.Error(err) } diff --git a/paddle/cuda/CMakeLists.txt b/paddle/cuda/CMakeLists.txt index 73ffa690d9d91b673079fc0ecf91f17cbabfdb1e..0865b02c4f275f3d5069109917b05dff1393fc1e 100755 --- a/paddle/cuda/CMakeLists.txt +++ b/paddle/cuda/CMakeLists.txt @@ -39,6 +39,7 @@ set(CUDA_CU_SOURCES src/hl_cuda_lstm.cu src/hl_top_k.cu src/hl_batch_transpose.cu + src/hl_batch_norm.cu src/hl_cuda_sequence.cu src/hl_table_apply.cu) diff --git a/paddle/cuda/include/hl_batch_norm.h b/paddle/cuda/include/hl_batch_norm.h new file mode 100644 index 0000000000000000000000000000000000000000..afc5e0b2deacc4aadf98b3f7ce115e534bbc5124 --- /dev/null +++ b/paddle/cuda/include/hl_batch_norm.h @@ -0,0 +1,48 @@ +/* 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. */ + +#ifndef HL_BATCH_NORM_H_ +#define HL_BATCH_NORM_H_ + +#include "hl_base.h" + +/** + * @brief batch norm inferece. + * + * @param[in] input input data. + * @param[out] output output data. + * @param[in] scale batch normalization scale parameter (in original + * paper scale is referred to as gamma). + * @param[in] bias batch normalization bias parameter (in original + * paper scale is referred to as beta). + * @param[in] estimatedMean + * @param[in] estimatedVar The moving mean and variance + * accumulated during the training phase are passed + * as inputs here. + * @param[in] epsilon Epsilon value used in the batch + * normalization formula. + */ +extern void hl_batch_norm_cuda_inference(const real* input, + real* output, + const real* scale, + const real* bias, + const real* estimatedMean, + const real* estimatedVar, + const double epsilon, + size_t batchSize, + size_t channel, + size_t height, + size_t width); + +#endif // HL_BATCH_NORM_H_ diff --git a/paddle/cuda/src/hl_batch_norm.cu b/paddle/cuda/src/hl_batch_norm.cu new file mode 100644 index 0000000000000000000000000000000000000000..5828ecb8e049c2f0573ab8547164794bef6db1ca --- /dev/null +++ b/paddle/cuda/src/hl_batch_norm.cu @@ -0,0 +1,66 @@ +/* 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 "hl_batch_norm.h" + +__global__ void batchNormInference(real* output, + const real* input, + const real* scale, + const real* bias, + const real* estimatedMean, + const real* estimatedVar, + const double epsilon, + size_t batchSize, + size_t channel, + size_t height, + size_t width) { + const int tid = threadIdx.x; + const int num = channel * height * width; + const int batch = blockIdx.x; + for (int i = tid; i < num; i += blockDim.x) { + const int c = i / (height * width); + const int id = batch * num + i; + real val = input[id] - estimatedMean[c]; + val /= sqrt(estimatedVar[c] + epsilon); + val *= scale[c]; + val += bias[c]; + output[id] = val; + } +} + +void hl_batch_norm_cuda_inference(const real* input, + real* output, + const real* scale, + const real* bias, + const real* estimatedMean, + const real* estimatedVar, + const double epsilon, + size_t batchSize, + size_t channel, + size_t height, + size_t width) { + batchNormInference<<>>(output, + input, + scale, + bias, + estimatedMean, + estimatedVar, + epsilon, + batchSize, + channel, + height, + width); + + CHECK_SYNC("hl_batch_norm_cuda_inference failed!"); +} diff --git a/paddle/cuda/src/hl_cuda_cudnn.cc b/paddle/cuda/src/hl_cuda_cudnn.cc index 7ad8a39768a064140a08c912a5a467bc24a12adf..78642a17443b0b4d81defaa46579332ef20c71a1 100644 --- a/paddle/cuda/src/hl_cuda_cudnn.cc +++ b/paddle/cuda/src/hl_cuda_cudnn.cc @@ -1023,14 +1023,6 @@ void hl_batch_norm_forward_inference(hl_tensor_descriptor inputDesc, real beta = 1.0f; cudnnBatchNormMode_t mode = CUDNN_BATCHNORM_SPATIAL; - int batch_size = ((cudnn_tensor_descriptor)inputDesc)->batch_size; - if (batch_size > 1024 && g_cudnn_lib_version < 6000) { - LOG(INFO) << " To process current batch data with size " << batch_size - << " (>1024), cudnnBatchNorm requires cuDNN version >= 6000." - << " If there is an error complaining CUDNN_STATUS_NOT_SUPPORTED," - << " just recompile PaddlePaddle with cuDNN >= 6000, replacing" - << " current version " << g_cudnn_lib_version; - } CHECK_CUDNN( dynload::cudnnBatchNormalizationForwardInference(t_resource.cudnn_handle, mode, diff --git a/paddle/framework/CMakeLists.txt b/paddle/framework/CMakeLists.txt index 05436e7f88ca8c807d07ed4933439dbbea0e9fa8..833ae46c5f29431121cb04f2a24900d7e59fedf4 100644 --- a/paddle/framework/CMakeLists.txt +++ b/paddle/framework/CMakeLists.txt @@ -44,4 +44,5 @@ cc_library(paddle_pybind SHARED mean_op cross_entropy_op recurrent_op - uniform_random_op) + uniform_random_op + fill_zeros_like_op) diff --git a/paddle/framework/pybind.cc b/paddle/framework/pybind.cc index cefdd88e8984733b3a5ea551de2052270a7281c2..011391bc2df4206dde15030cd78d6ea329530de4 100644 --- a/paddle/framework/pybind.cc +++ b/paddle/framework/pybind.cc @@ -40,6 +40,7 @@ USE_OP(mean); USE_OP(sigmoid); USE_OP(softmax); USE_OP(rowwise_add); +USE_OP(fill_zeros_like); USE_OP_WITHOUT_KERNEL(recurrent_op); USE_OP(uniform_random); namespace paddle { diff --git a/paddle/gserver/layers/CudnnBatchNormLayer.cpp b/paddle/gserver/layers/CudnnBatchNormLayer.cpp index 09dac05a7ad7a80bd6b9e12e8f7f060310d516c8..44ba2c4b7d1562d2ce839b5f4b4de1af35e6925f 100644 --- a/paddle/gserver/layers/CudnnBatchNormLayer.cpp +++ b/paddle/gserver/layers/CudnnBatchNormLayer.cpp @@ -14,6 +14,7 @@ limitations under the License. */ #include "CudnnBatchNormLayer.h" #include "Layer.h" +#include "paddle/cuda/include/hl_batch_norm.h" #include "paddle/utils/Stat.h" namespace paddle { @@ -79,16 +80,33 @@ void CudnnBatchNormLayer::forward(PassType passType) { savedInvVar); } else { // used movingMean and movingVar in testing - hl_batch_norm_forward_inference(ioDesc_, - input, - ioDesc_, - output, - bnParamDesc_, - gamma, - beta, - movingMean, - movingVar, - EPS); + if (batchSize <= 1024) { + hl_batch_norm_forward_inference(ioDesc_, + input, + ioDesc_, + output, + bnParamDesc_, + gamma, + beta, + movingMean, + movingVar, + EPS); + } else { + // There is a limitation in cudnn library. + // When the batch size is larger than 1024 in cuDNN v5.1, + // the cudnnBatchNormalizationForwardInference will fail. + hl_batch_norm_cuda_inference(input, + output, + gamma, + beta, + movingMean, + movingVar, + EPS, + batchSize, + channels_, + imageH_, + imageW_); + } } /* activation */ { diff --git a/paddle/gserver/tests/test_BatchNorm.cpp b/paddle/gserver/tests/test_BatchNorm.cpp index 83fcfed46cd568d22237eeef9c0215e4e3ad2666..659eefa31bdb1f2433d03a59d5bf4782c71bdecf 100644 --- a/paddle/gserver/tests/test_BatchNorm.cpp +++ b/paddle/gserver/tests/test_BatchNorm.cpp @@ -21,6 +21,8 @@ limitations under the License. */ #include "paddle/utils/GlobalConstants.h" #include "LayerGradUtil.h" +#include "paddle/cuda/include/hl_batch_norm.h" +#include "paddle/math/tests/TensorCheck.h" #include "paddle/testing/TestUtil.h" using namespace paddle; // NOLINT @@ -117,6 +119,74 @@ TEST(Layer, batchNorm) { CHECK_EQ(static_cast(convLayer->getOutputValue()->getWidth()), 576); } +#ifndef PADDLE_ONLY_CPU +void batchNormInference(int n, int c, int h, int w) { + MatrixPtr input = std::make_shared(n, c * h * w); + MatrixPtr cudnnOut = std::make_shared(n, c * h * w); + MatrixPtr cudaOut = std::make_shared(n, c * h * w); + MatrixPtr cudnnCheck = std::make_shared(n, c * h * w); + MatrixPtr cudaCheck = std::make_shared(n, c * h * w); + input->randomizeUniform(); + cudnnOut->zeroMem(); + cudaOut->zeroMem(); + + MatrixPtr scale = std::make_shared(1, c); + scale->randomizeUniform(); + MatrixPtr bias = std::make_shared(1, c); + bias->randomizeUniform(); + + MatrixPtr movingMean = std::make_shared(1, c); + movingMean->randomizeUniform(); + + MatrixPtr movingVar = std::make_shared(1, c); + movingVar->randomizeUniform(); + movingVar->clip(0.01, 50); + + hl_tensor_descriptor ioDesc; + hl_tensor_descriptor bnDesc; + hl_create_tensor_descriptor(&ioDesc); + hl_create_tensor_descriptor(&bnDesc); + hl_tensor_reshape(ioDesc, n, c, h, w); + hl_tensor_reshape(bnDesc, 1, c, 1, 1); + + double EPS = 1E-5; + hl_batch_norm_forward_inference(ioDesc, + input->getData(), + ioDesc, + cudnnOut->getData(), + bnDesc, + scale->getData(), + bias->getData(), + movingMean->getData(), + movingVar->getData(), + EPS); + + hl_batch_norm_cuda_inference(input->getData(), + cudaOut->getData(), + scale->getData(), + bias->getData(), + movingMean->getData(), + movingVar->getData(), + EPS, + n, + c, + h, + w); + + cudnnCheck->copyFrom(*cudnnOut); + cudaCheck->copyFrom(*cudaOut); + autotest::TensorCheckErr(*cudnnCheck, *cudaCheck); + + hl_destroy_tensor_descriptor(ioDesc); + hl_destroy_tensor_descriptor(bnDesc); +} + +TEST(BatchNorm, Inference) { + batchNormInference(33, 267, 1, 1); + batchNormInference(19, 105, 4, 4); +} +#endif + int main(int argc, char** argv) { testing::InitGoogleTest(&argc, argv); initMain(argc, argv); diff --git a/paddle/operators/fill_zeros_like_op.cc b/paddle/operators/fill_zeros_like_op.cc index 3d37d64c5a8c288684122f3e686262399d32ed7b..198b4576c887122fdac1a3fbff5a248a3d9fa0a3 100644 --- a/paddle/operators/fill_zeros_like_op.cc +++ b/paddle/operators/fill_zeros_like_op.cc @@ -13,8 +13,6 @@ See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/operators/fill_zeros_like_op.h" -#include "paddle/framework/op_registry.h" -#include "paddle/framework/tensor.h" namespace paddle { namespace operators { diff --git a/paddle/operators/fill_zeros_like_op.cu b/paddle/operators/fill_zeros_like_op.cu index ed1068219c8fee8c6e8809f450a9d38c8226f317..4f1054cf47e35572dbbc51ca742994065a027919 100644 --- a/paddle/operators/fill_zeros_like_op.cu +++ b/paddle/operators/fill_zeros_like_op.cu @@ -12,6 +12,7 @@ See the License for the specific language governing permissions and limitations under the License. */ +#define EIGEN_USE_GPU #include "paddle/framework/op_registry.h" #include "paddle/operators/fill_zeros_like_op.h" diff --git a/paddle/operators/fill_zeros_like_op.h b/paddle/operators/fill_zeros_like_op.h index 4bff1fbfc15af1f4d1ce9c99fe48b0b0f11b5b3f..dfaed2c9aaf2bf5c1a9b803fc9c8b9ea0e5c5d4e 100644 --- a/paddle/operators/fill_zeros_like_op.h +++ b/paddle/operators/fill_zeros_like_op.h @@ -13,9 +13,7 @@ See the License for the specific language governing permissions and limitations under the License. */ #pragma once -#include "glog/logging.h" -#include "paddle/framework/eigen.h" -#include "paddle/framework/operator.h" +#include "paddle/operators/type_alias.h" namespace paddle { namespace operators { @@ -26,7 +24,8 @@ class FillZerosLikeKernel : public framework::OpKernel { void Compute(const framework::ExecutionContext& context) const override { auto* output = context.Output(0); output->mutable_data(context.GetPlace()); - framework::EigenVector::Flatten(*output).setZero(); + auto t = framework::EigenVector::Flatten(*output); + t.device(context.GetEigenDevice()) = t.constant(T(0)); } }; diff --git a/paddle/pybind/CMakeLists.txt b/paddle/pybind/CMakeLists.txt index 29dd0ded0ac75893da7e244d92725cd5e285efce..8e6b258e00c0012876cda8ffc5b340322d51e894 100644 --- a/paddle/pybind/CMakeLists.txt +++ b/paddle/pybind/CMakeLists.txt @@ -6,4 +6,5 @@ cc_library(paddle_pybind SHARED add_op mean_op cross_entropy_op - recurrent_op) + recurrent_op + fill_zeros_like_op) diff --git a/python/paddle/v2/framework/tests/CMakeLists.txt b/python/paddle/v2/framework/tests/CMakeLists.txt index f1457515daa66d0bec05627cc9d6aa837849a0db..0328bea7f7f18562fcb6b5a19cd2a2c70f10a532 100644 --- a/python/paddle/v2/framework/tests/CMakeLists.txt +++ b/python/paddle/v2/framework/tests/CMakeLists.txt @@ -13,6 +13,7 @@ py_test(test_protobuf SRCS test_protobuf.py) py_test(test_add_two_op SRCS test_add_two_op.py) py_test(test_sigmoid_op SRCS test_sigmoid_op.py) py_test(test_softmax_op SRCS test_softmax_op.py) +py_test(test_fill_zeros_like_op SRCS test_fill_zeros_like_op.py) py_test(gradient_checker SRCS gradient_checker.py) diff --git a/python/paddle/v2/framework/tests/test_fill_zeros_like_op.py b/python/paddle/v2/framework/tests/test_fill_zeros_like_op.py new file mode 100644 index 0000000000000000000000000000000000000000..e5c862605fb11a5ea1426cf8f9054589dc377ff1 --- /dev/null +++ b/python/paddle/v2/framework/tests/test_fill_zeros_like_op.py @@ -0,0 +1,16 @@ +import unittest +from op_test_util import OpTestMeta +import numpy + + +class TestFillZerosLikeOp(unittest.TestCase): + __metaclass__ = OpTestMeta + + def setUp(self): + self.type = "fill_zeros_like" + self.inputs = {'Src': numpy.random.random((219, 232)).astype("float32")} + self.outputs = {'Dst': numpy.zeros_like(self.inputs['Src'])} + + +if __name__ == '__main__': + unittest.main()