diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 61b989dc698798eca932516e558c63f107ef2754..efb4dcb2dfbc63bb6905961b054cdef860cf4573 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -21,10 +21,10 @@ sha: 28c0ea8a67a3e2dbbf4822ef44e85b63a0080a29 hooks: - id: clang-formater -- repo: https://github.com/dnephin/pre-commit-golang - sha: e4693a4c282b4fc878eda172a929f7a6508e7d16 +- repo: https://github.com/PaddlePaddle/pre-commit-golang + sha: 16398aeccf263adaf53b2495eed0406347d76281 hooks: - id: go-fmt - files: (.*\.go) - - id: go-lint - files: (.*\.go) + types: [go] + - id: gometalinter + types: [go] diff --git a/.travis.yml b/.travis.yml index 2cf7666fb5d0c47034676864a52c3d3dbce19683..376c693602b56fe719decfeb41c217497e143e12 100644 --- a/.travis.yml +++ b/.travis.yml @@ -41,6 +41,8 @@ before_install: - pip install rarfile - curl https://glide.sh/get | bash - eval "$(GIMME_GO_VERSION=1.8.3 gimme)" + - go get -u github.com/alecthomas/gometalinter + - gometalinter --install - | function timeout() { perl -e 'alarm shift; exec @ARGV' "$@"; } script: diff --git a/CMakeLists.txt b/CMakeLists.txt index fb1c85bf742c80308edb009c080cb0da6d409ee0..dcff6b54cafce35846627e78cfcdac65fae7e686 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -137,7 +137,8 @@ if(WITH_GPU) endif(WITH_GPU) if(USE_NNPACK) - list(APPEND EXTERNAL_LIBS ${NNPACK_LIB} ${PTHREADPOOL_LIB} "rt") + include(external/nnpack) + list(APPEND EXTERNAL_LIBS ${NNPACK_LIBS}) endif(USE_NNPACK) add_subdirectory(proto) diff --git a/Dockerfile.android b/Dockerfile.android index fa24f6f06c4e76444c83bcf13fe312afdcb6c348..c0fa58c384f9ebcae60477ffce49ea4ffa929db9 100644 --- a/Dockerfile.android +++ b/Dockerfile.android @@ -14,6 +14,17 @@ RUN apt-get update && \ wget curl tar unzip gcc g++ locales clang-format-3.8 swig cmake && \ apt-get clean -y +# Install Go and glide +RUN wget -O go.tgz https://storage.googleapis.com/golang/go1.8.1.linux-amd64.tar.gz && \ + tar -C /usr/local -xzf go.tgz && \ + mkdir /root/gopath && \ + mkdir /root/gopath/bin && \ + mkdir /root/gopath/src && \ + rm go.tgz +ENV GOROOT=/usr/local/go GOPATH=/root/gopath +# should not be in the same line with GOROOT definition, otherwise docker build could not find GOROOT. +ENV PATH=${PATH}:${GOROOT}/bin:${GOPATH}/bin + # git credential to skip password typing RUN git config --global credential.helper store diff --git a/cmake/cross_compiling/android.cmake b/cmake/cross_compiling/android.cmake index dcfbc5d0129d7763daaf17c33d2b7791e87d3018..5e3e437a8da9624df35a5c754fe77be73f20361d 100644 --- a/cmake/cross_compiling/android.cmake +++ b/cmake/cross_compiling/android.cmake @@ -108,6 +108,7 @@ IF("${CMAKE_VERSION}" VERSION_LESS "3.7.0") ENDIF() IF(ANDROID_ABI STREQUAL "arm64-v8a") SET(ANDROID_TOOLCHAIN_NAME aarch64-linux-android) + SET(CMAKE_SYSTEM_PROCESSOR aarch64) ENDIF() SET(ANDROID_TOOLCHAIN_PREFIX "${ANDROID_TOOLCHAIN_ROOT}/bin/${ANDROID_TOOLCHAIN_NAME}-") ENDIF() @@ -166,7 +167,7 @@ IF("${CMAKE_VERSION}" VERSION_LESS "3.7.0") ENDIF() IF(ANDROID_ABI STREQUAL "arm64-v8a") - LIST(APPEND ANDROID_COMPILER_FLAGS -march=armv8-a) + LIST(APPEND ANDROID_COMPILER_FLAGS -march=armv8-a) ENDIF() STRING(REPLACE ";" " " ANDROID_COMPILER_FLAGS "${ANDROID_COMPILER_FLAGS}") @@ -193,6 +194,10 @@ ELSE() SET(CMAKE_ANDROID_STANDALONE_TOOLCHAIN ${ANDROID_STANDALONE_TOOLCHAIN}) ENDIF() SET(CMAKE_ANDROID_ARCH_ABI ${ANDROID_ABI}) - SET(CMAKE_ANDROID_ARM_MODE ${ANDROID_ARM_MODE}) - SET(CMAKE_ANDROID_ARM_NEON ${ANDROID_ARM_NEON}) + IF(ANDROID_ABI MATCHES "^armeabi(-v7a)?$") + SET(CMAKE_ANDROID_ARM_MODE ${ANDROID_ARM_MODE}) + IF(ANDROID_ABI STREQUAL "armeabi-v7a") + SET(CMAKE_ANDROID_ARM_NEON ${ANDROID_ARM_NEON}) + ENDIF() + ENDIF() ENDIF() diff --git a/paddle/function/nnpack/nnpack.cmake b/cmake/external/nnpack.cmake similarity index 54% rename from paddle/function/nnpack/nnpack.cmake rename to cmake/external/nnpack.cmake index 7182730ae8f133bdc4f73bfc46fa8acbe5f3b603..d42bcb0f329041462bd8b568052fbb8226d18e4e 100644 --- a/paddle/function/nnpack/nnpack.cmake +++ b/cmake/external/nnpack.cmake @@ -7,10 +7,24 @@ set(NNPACK_ROOT $ENV{NNPACK_ROOT} CACHE PATH "Folder contains NNPACK") find_path(NNPACK_INC_DIR nnpack.h PATHS ${NNPACK_ROOT}/include) find_library(NNPACK_LIB NAMES nnpack PATHS ${NNPACK_ROOT}/lib) find_library(PTHREADPOOL_LIB NAMES pthreadpool PATHS ${NNPACK_ROOT}/lib) +find_library(NNPACK_UKERNELS_LIB NAMES nnpack_ukernels PATHS ${NNPACK_ROOT}/lib) +find_library(NNPACK_CPUFEATURES_LIB NAMES cpufeatures PATHS ${NNPACK_ROOT}/lib) if(NNPACK_INC_DIR AND NNPACK_LIB AND PTHREADPOOL_LIB) set(NNPACK_FOUND ON) INCLUDE_DIRECTORIES(${NNPACK_INC_DIR}) + + set(NNPACK_LIBS) + list(APPEND NNPACK_LIBS ${NNPACK_LIB} ${PTHREADPOOL_LIB}) + if (NNPACK_UKERNELS_LIB) + list(APPEND NNPACK_LIBS ${NNPACK_UKERNELS_LIB}) + endif() + if (NNPACK_CPUFEATURES_LIB) + list(APPEND NNPACK_LIBS ${NNPACK_CPUFEATURES_LIB}) + endif() + if(NOT ANDROID) + list(APPEND NNPACK_LIBS "rt") + endif() else() message(FATAL_ERROR "Cannot find NNPACK in (${NNPACK_ROOT})") endif() diff --git a/go/master/c/client.go b/go/master/c/client.go index 31f431197454c2ec6a25624d37b60876d99f0087..2cbe164c7b406b189f44ec850796203f24779205 100644 --- a/go/master/c/client.go +++ b/go/master/c/client.go @@ -23,7 +23,6 @@ import ( log "github.com/sirupsen/logrus" ) -var nullPtr = unsafe.Pointer(uintptr(0)) var mu sync.Mutex var handleMap = make(map[C.paddle_master_client]*master.Client) var curHandle C.paddle_master_client @@ -114,13 +113,13 @@ func paddle_next_record(client C.paddle_master_client, record **C.uchar) C.int { if err != nil { // Error // TODO: return the type of error? - *record = (*C.uchar)(nullPtr) + *record = (*C.uchar)(nil) return -1 } if len(r) == 0 { // Empty record - *record = (*C.uchar)(nullPtr) + *record = (*C.uchar)(nil) return 0 } diff --git a/go/master/client.go b/go/master/client.go index de883bf4b9a3de8d6d6e35e8e808dcf7ba54cb46..90b99470978d21480eb2d8097e7dec217b9524eb 100644 --- a/go/master/client.go +++ b/go/master/client.go @@ -69,7 +69,10 @@ 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.Meta.ID) + err = c.taskFinished(t.Meta.ID) + if err != nil { + log.Errorln(err) + } } } diff --git a/go/master/client_internal_test.go b/go/master/client_internal_test.go index 49263474c8fe2410ffb6db93a9647f5ab066b06b..70dc09bf9461142ff6498355a5858ba9a1320510 100644 --- a/go/master/client_internal_test.go +++ b/go/master/client_internal_test.go @@ -66,11 +66,21 @@ func TestGetFinishTask(t *testing.T) { for i := 0; i < totalTask*chunkPerTask; i++ { w := recordio.NewWriter(f, -1, -1) - w.Write(nil) + _, err = w.Write(nil) + if err != nil { + panic(err) + } + // call Close to force RecordIO writing a chunk. - w.Close() + err = w.Close() + if err != nil { + panic(err) + } + } + err = f.Close() + if err != nil { + panic(err) } - f.Close() // Manually intialize client to avoid calling c.getRecords() c := &Client{} @@ -79,7 +89,11 @@ func TestGetFinishTask(t *testing.T) { ch := make(chan string, 1) ch <- addr go c.monitorMaster(ch) - c.SetDataset([]string{path}) + err = c.SetDataset([]string{path}) + if err != nil { + panic(err) + } + checkOnePass := func(i int) { var tasks []Task for idx := 0; idx < totalTask; idx++ { diff --git a/go/master/client_test.go b/go/master/client_test.go index 6666d3860c412daa8711fbfa2d729a261b3fd887..bc92dc5ac973d62434b71e09705143ac8fbbd2fa 100644 --- a/go/master/client_test.go +++ b/go/master/client_test.go @@ -57,14 +57,30 @@ func TestNextRecord(t *testing.T) { w := recordio.NewWriter(f, -1, -1) for i := 0; i < total; i++ { - w.Write([]byte{byte(i)}) + _, err = w.Write([]byte{byte(i)}) + if err != nil { + panic(err) + } + } + + err = w.Close() + if err != nil { + panic(err) + } + + err = f.Close() + if err != nil { + panic(err) } - w.Close() - f.Close() + curAddr := make(chan string, 1) curAddr <- fmt.Sprintf(":%d", p) c := master.NewClient(curAddr, 10) - c.SetDataset([]string{path}) + err = c.SetDataset([]string{path}) + if err != nil { + panic(err) + } + for pass := 0; pass < 50; pass++ { received := make(map[byte]bool) for i := 0; i < total; i++ { diff --git a/go/master/etcd_client.go b/go/master/etcd_client.go index 04c1394e963d1eb541b80b91407fb55b0d1e1f2a..69dc6a8268748ad9a72eb10fc2789982f565d291 100644 --- a/go/master/etcd_client.go +++ b/go/master/etcd_client.go @@ -30,7 +30,7 @@ type EtcdClient struct { // NewEtcdClient creates a new EtcdClient. func NewEtcdClient(endpoints []string, addr string, lockPath, addrPath, statePath string, ttlSec int) (*EtcdClient, error) { log.Debugf("Connecting to etcd at %v", endpoints) - // TODO(helin): gracefully shutdown etcd store. Becuase etcd + // TODO(helin): gracefully shutdown etcd store. Because etcd // store holds a etcd lock, even though the lock will expire // when the lease timeout, we need to implement graceful // shutdown to release the lock. @@ -60,7 +60,7 @@ func NewEtcdClient(endpoints []string, addr string, lockPath, addrPath, statePat } log.Debugf("Successfully acquired lock at %s.", lockPath) - put := clientv3.OpPut(addrPath, string(addr)) + put := clientv3.OpPut(addrPath, addr) resp, err := cli.Txn(context.Background()).If(lock.IsOwner()).Then(put).Commit() if err != nil { return nil, err diff --git a/go/master/inmem_store.go b/go/master/inmem_store.go index bcd549b20e46381783bad11caa08cb7f4ba40add..57e75dc4e01b4bafa8153bcc7fbc82a9eb2b08f5 100644 --- a/go/master/inmem_store.go +++ b/go/master/inmem_store.go @@ -4,7 +4,7 @@ import "sync" // InMemStore is an in memory implementation of Store interface. // -// It does not tolerate the fault that casues the program to crash. +// It does not tolerate the fault that causes the program to crash. type InMemStore struct { mu sync.Mutex buf []byte diff --git a/go/master/service.go b/go/master/service.go index 9cef2270ce6a51425e40b9281f93f2f9c9981329..262735f421ad7ae04050e9264a177ee4c46e68d0 100644 --- a/go/master/service.go +++ b/go/master/service.go @@ -160,7 +160,7 @@ func (s *Service) recover() (bool, error) { // snapshot *must* be called with s.mu being held. func (s *Service) snapshot() error { - // TOOD(helin): etcd request has a size limit, so the snapshot + // TODO(helin): etcd request has a size limit, so the snapshot // size is limited by the max request size. We should either // divide the snapshot into smaller chunks and save under // different keys, or configure the request size to be big @@ -289,7 +289,6 @@ func (s *Service) processFailedTask(t taskEntry, epoch int) { 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() { diff --git a/go/pserver/client/c/cclient.go b/go/pserver/client/c/cclient.go index 7ddaceb7ed33db32e19a191402100a0c0efa241a..718b4304c80791b4d8a8816f256c8fa93e0b1ead 100644 --- a/go/pserver/client/c/cclient.go +++ b/go/pserver/client/c/cclient.go @@ -34,7 +34,6 @@ import ( log "github.com/sirupsen/logrus" ) -var nullPtr = unsafe.Pointer(uintptr(0)) var mu sync.Mutex var handleMap = make(map[C.paddle_pserver_client]*client.Client) var curHandle C.paddle_pserver_client @@ -63,7 +62,7 @@ func remove(client C.paddle_pserver_client) *client.Client { } func cArrayToSlice(p unsafe.Pointer, len int) []byte { - if p == nullPtr { + if p == nil { return nil } @@ -101,11 +100,11 @@ func paddle_new_pserver_client(addrs *C.char, selected int) C.paddle_pserver_cli } //export paddle_new_etcd_pserver_client -func paddle_new_etcd_pserver_client(etcd_endpoints *C.char, selected int) C.paddle_pserver_client { +func paddle_new_etcd_pserver_client(etcdEndpoints *C.char, selected int) C.paddle_pserver_client { // TODO(Longfei: use etcd lock to decide which trainer to initialize the parameters) - addr := C.GoString(etcd_endpoints) - etcd_client := client.NewEtcd(addr) - c := client.NewClient(etcd_client, etcd_client.Desired(), selector(selected != 0)) + addr := C.GoString(etcdEndpoints) + etcdClient := client.NewEtcd(addr) + c := client.NewClient(etcdClient, etcdClient.Desired(), selector(selected != 0)) return add(c) } @@ -124,20 +123,20 @@ func paddle_begin_init_params(client C.paddle_pserver_client) C.int { } //export paddle_init_param -func paddle_init_param(client C.paddle_pserver_client, param C.paddle_parameter, param_config unsafe.Pointer, config_len C.int) C.int { +func paddle_init_param(client C.paddle_pserver_client, param C.paddle_parameter, paramConfig unsafe.Pointer, configLen C.int) C.int { et := pserver.ElementType(param.element_type) name := C.GoString(param.name) content := cArrayToSlice(unsafe.Pointer(param.content), int(param.content_len)) pc := pserver.ParameterWithConfig{ Param: pserver.Parameter{Name: name, ElementType: et, Content: content}, - Config: cArrayToSlice(param_config, int(config_len)), + Config: cArrayToSlice(paramConfig, int(configLen)), } c := get(client) err := c.InitParam(pc) if err != nil { if err.Error() == pserver.AlreadyInitialized { - log.Warningf("parameter %s already initialized, treat paddle_init_param as sucessful.", name) + log.Warningf("parameter %s already initialized, treat paddle_init_param as successful.", name) return C.PSERVER_OK } log.Errorln(err) @@ -153,7 +152,7 @@ func paddle_finish_init_params(client C.paddle_pserver_client) C.int { err := c.FinishInitParams() if err != nil { if err.Error() == pserver.AlreadyInitialized { - log.Warningln("parameters already initialized, treat paddle_finish_init_params as sucessful.") + log.Warningln("parameters already initialized, treat paddle_finish_init_params as successful.") return C.PSERVER_OK } @@ -223,12 +222,12 @@ func paddle_get_params(client C.paddle_pserver_client, dst **C.paddle_parameter, p := ps[i] param := *(**C.paddle_parameter)(unsafe.Pointer((uintptr(unsafe.Pointer(dst)) + uintptr(i)*unsafe.Sizeof(*dst)))) - if unsafe.Pointer(param) == nullPtr { + if unsafe.Pointer(param) == nil { log.Errorln("must pre-allocate parameter.") return C.PSERVER_ERROR } - if unsafe.Pointer(param.content) != nullPtr { + if unsafe.Pointer(param.content) != nil { if int(param.content_len) != len(p.Content) { log.Errorf("the pre-allocated content len does not match parameter content len. Pre-allocated len: %d, returned len: %d", param.content_len, len(p.Content)) return C.PSERVER_ERROR diff --git a/go/pserver/client/client.go b/go/pserver/client/client.go index aa8bfe30c26fcc0875ad479ecd562700ccefa5a3..b4a45e1c21056550ef9264746bcf58a8abb369a1 100644 --- a/go/pserver/client/client.go +++ b/go/pserver/client/client.go @@ -233,7 +233,7 @@ func (c *Client) Save(path string) error { func strHash(s string) uint32 { h := fnv.New32a() - h.Write([]byte(s)) + _, _ = h.Write([]byte(s)) return h.Sum32() } diff --git a/go/pserver/client/client_test.go b/go/pserver/client/client_test.go index aab91556b4b91fab6de66322987eabe24f1b0f70..5c89882a297323034be2875a6d4cb71d715eb0c2 100644 --- a/go/pserver/client/client_test.go +++ b/go/pserver/client/client_test.go @@ -79,15 +79,33 @@ func initEtcdClient() { log.Errorf("err %v", err) } ctx, cancel := context.WithTimeout(context.Background(), timeout) - client.Delete(ctx, pserver.PsDesired) - client.Delete(ctx, pserver.PsPath) - client.Put(ctx, pserver.PsDesired, strconv.Itoa(numPserver)) + _, err = client.Delete(ctx, pserver.PsDesired) + if err != nil { + panic(err) + } + + _, err = client.Delete(ctx, pserver.PsPath) + if err != nil { + panic(err) + } + + _, err = client.Put(ctx, pserver.PsDesired, strconv.Itoa(numPserver)) + if err != nil { + panic(err) + } + ports := initClient() for i := 0; i < numPserver; i++ { - client.Put(ctx, pserver.PsPath+strconv.Itoa(i), ":"+strconv.Itoa(ports[i])) + _, err = client.Put(ctx, pserver.PsPath+strconv.Itoa(i), ":"+strconv.Itoa(ports[i])) + if err != nil { + panic(err) + } } cancel() - client.Close() + err = client.Close() + if err != nil { + panic(err) + } } type selector bool diff --git a/go/pserver/client/etcd_client.go b/go/pserver/client/etcd_client.go index 8eb2a4f4511fc7139a55a2cd47ad73a82137b260..953065b427ed52d39f1253ea94d485b765ea5dc2 100644 --- a/go/pserver/client/etcd_client.go +++ b/go/pserver/client/etcd_client.go @@ -12,8 +12,7 @@ import ( ) const ( - // DefaultEtcdTimeout is the default etcd timeout - DefaultEtcdTimeout time.Duration = 5 * time.Second + defaultEtcdTimeout time.Duration = 5 * time.Second ) // EtcdClient is used by pserver client that is a part of trainer process. @@ -48,7 +47,7 @@ func (p *EtcdClient) Desired() int { psDesired, err = strconv.Atoi(string(resp.Kvs[0].Value)) if err != nil { - log.Errorf("psDesired %s invalid %v", psDesired, err) + log.Errorf("psDesired %d invalid %v", psDesired, err) time.Sleep(p.timeout) continue } @@ -67,12 +66,12 @@ func (p *EtcdClient) List() []Server { for { for i := 0; i < psDesired; i++ { ctx, cancel := context.WithTimeout(context.Background(), p.timeout) + cancel() psKey := pserver.PsPath + strconv.Itoa(i) log.Debugf("checking %s", psKey) resp, err := p.client.Get(ctx, psKey) - cancel() if err != nil { - log.Infof("Get psKey=%s error, %v", psKey, err) + log.Infof("Get psKey= %s error, %v", psKey, err) time.Sleep(p.timeout) continue } @@ -107,11 +106,11 @@ func NewEtcd(endpoints string) *EtcdClient { for { cli, err = clientv3.New(clientv3.Config{ Endpoints: ep, - DialTimeout: DefaultEtcdTimeout, + DialTimeout: defaultEtcdTimeout, }) if err != nil { log.Errorf("Init etcd connection failed: %v", err) - time.Sleep(DefaultEtcdTimeout) + time.Sleep(defaultEtcdTimeout) continue } break @@ -119,7 +118,7 @@ func NewEtcd(endpoints string) *EtcdClient { log.Infof("Connected to etcd: %s\n", endpoints) client := &EtcdClient{ client: cli, - timeout: DefaultEtcdTimeout, + timeout: defaultEtcdTimeout, endpoints: ep, } return client diff --git a/go/pserver/etcd_client.go b/go/pserver/etcd_client.go index 66af4fa0b483f1caea385df61e54d871072a0375..e70e826975b26db302a6799e9171cff970153aac 100644 --- a/go/pserver/etcd_client.go +++ b/go/pserver/etcd_client.go @@ -177,10 +177,10 @@ func (e *EtcdClient) registerPserverEtcd(ctx context.Context, port int) (int, er break } } - if registered == true { + if registered { return nil } - return errors.New("not registerd, may due to already have enough pservers") + return errors.New("not registered, may due to already have enough pservers") }, concurrency.WithAbortContext(ctx), concurrency.WithIsolation(concurrency.RepeatableReads)) if err != nil { @@ -211,8 +211,5 @@ func (e *EtcdClient) PutKey(key string, value []byte, timeout time.Duration) err ctx, cancel := context.WithTimeout(context.Background(), timeout) _, err := e.etcdClient.Put(ctx, key, string(value)) cancel() - if err != nil { - return err - } - return nil + return err } diff --git a/go/pserver/optimizer.go b/go/pserver/optimizer.go index d6b7fafd59c0453b9f40019166d01ebdc9775117..151a3f80332b0e62767586f9f769c839ba19ce1e 100644 --- a/go/pserver/optimizer.go +++ b/go/pserver/optimizer.go @@ -14,8 +14,6 @@ import ( log "github.com/sirupsen/logrus" ) -var nullPtr = unsafe.Pointer(uintptr(0)) - type optimizer struct { opt *C.struct_paddle_optimizer elementType ElementType @@ -23,7 +21,7 @@ type optimizer struct { } func cArrayToSlice(p unsafe.Pointer, len int) []byte { - if p == nullPtr { + if p == nil { return nil } @@ -92,8 +90,8 @@ func (o *optimizer) UpdateParameter(g Gradient) error { } func (o *optimizer) Cleanup() { - if unsafe.Pointer(o.opt) != nullPtr { + if unsafe.Pointer(o.opt) != nil { C.paddle_release_optimizer(o.opt) - o.opt = (*C.struct_paddle_optimizer)(nullPtr) + o.opt = (*C.struct_paddle_optimizer)(nil) } } diff --git a/go/pserver/service.go b/go/pserver/service.go index fec2ec61dc67756439d9fa478788d1f155876538..c723959d6b87524762e2f874bb5e4d5bd567cd00 100644 --- a/go/pserver/service.go +++ b/go/pserver/service.go @@ -211,7 +211,7 @@ func (s *Service) GetParam(name string, parameter *Parameter) error { // learning optimization methods are stochastic in // nature. This race condition is allowed deliberately // to save the program from making a copy of the - // paramter content. + // parameter content. parameter.Name = name parameter.ElementType = opt.elementType parameter.Content = opt.GetWeights() @@ -219,7 +219,7 @@ func (s *Service) GetParam(name string, parameter *Parameter) error { } // pserver save checkpoint -func (s *Service) doCheckpoint() error { +func (s *Service) doCheckpoint() (err error) { <-s.initialized s.mu.Lock() defer s.mu.Unlock() @@ -237,9 +237,9 @@ func (s *Service) doCheckpoint() error { } var buf bytes.Buffer encoder := gob.NewEncoder(&buf) - err := encoder.Encode(cp) + err = encoder.Encode(cp) if err != nil { - return err + return } cpMeta := checkpointMeta{} @@ -248,10 +248,14 @@ func (s *Service) doCheckpoint() error { h := md5.New() cpMeta.MD5 = hex.EncodeToString(h.Sum(buf.Bytes())) - cpMetajson, _ := json.Marshal(cpMeta) + 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 err + return } if _, err = os.Stat(cpMeta.UUID); os.IsNotExist(err) { log.Info("checkpoint does not exists.") @@ -264,15 +268,32 @@ func (s *Service) doCheckpoint() error { } } f, err := os.Create(cpMeta.UUID) - defer f.Close() if err != nil { - return err + return } + + defer func() { + closeErr := f.Close() + if closeErr != nil { + if err != nil { + log.Errorln(closeErr) + } else { + // Set closeErr as return value. + err = closeErr + } + } + }() + writer := bufio.NewWriter(f) _, err = writer.Write(buf.Bytes()) - writer.Flush() if err != nil { - return err + return } - return nil + + err = writer.Flush() + if err != nil { + return + } + + return } diff --git a/paddle/framework/CMakeLists.txt b/paddle/framework/CMakeLists.txt index 824d34d016da5561f682eb275a73ac72cc7386ce..e7d1c7203aa3422b3f5dab4a83da4e175219ba81 100644 --- a/paddle/framework/CMakeLists.txt +++ b/paddle/framework/CMakeLists.txt @@ -1,19 +1,19 @@ -# ddim lib +cc_library(enforce SRCS enforce.cc DEPS glog) +cc_test(enforce_test SRCS enforce_test.cc DEPS enforce) cc_library(ddim SRCS ddim.cc) cc_test(ddim_test SRCS ddim_test.cc DEPS ddim) nv_test(dim_test SRCS dim_test.cu DEPS ddim) -cc_test(tensor_test SRCS tensor_test.cc DEPS ddim glog gflags) +cc_library(tensor SRCS tensor.cc DEPS ddim place enforce paddle_memory) +cc_test(tensor_test SRCS tensor_test.cc DEPS tensor) cc_test(variable_test SRCS variable_test.cc) cc_test(scope_test SRCS scope_test.cc) -cc_library(enforce SRCS enforce.cc DEPS glog gflags) -cc_test(enforce_test SRCS enforce_test.cc DEPS enforce) proto_library(attr_type SRCS attr_type.proto) 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_library(operator SRCS operator.cc DEPS op_desc device_context enforce) +cc_library(operator SRCS operator.cc DEPS op_desc device_context tensor) 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 enforce) diff --git a/paddle/framework/ddim.cc b/paddle/framework/ddim.cc index 73f5499ad15752237a73ca27e0cd0fe2c5e86b4e..d2ef85afe55e640a17b8c957bac61d175e69ff3f 100644 --- a/paddle/framework/ddim.cc +++ b/paddle/framework/ddim.cc @@ -117,6 +117,8 @@ int DDim::operator[](int idx) const { return boost::apply_visitor(DynamicConstIndexer(idx), var); } +ssize_t DDim::size() const { return arity(*this); } + bool DDim::operator==(DDim d) const { if (var.which() != d.getVar().which()) { return false; @@ -278,5 +280,9 @@ std::ostream& operator<<(std::ostream& os, const DDim& ddim) { return os; } +DDim::DDim(std::initializer_list init_list) { + *this = make_ddim(init_list); +} + } // namespace framework } // namespace paddle diff --git a/paddle/framework/ddim.h b/paddle/framework/ddim.h index a0c2a8a74afdefd4a504ec6fa730238e077efbb5..3976c6c0299c489764c7ccc209bef0a84736be12 100644 --- a/paddle/framework/ddim.h +++ b/paddle/framework/ddim.h @@ -29,6 +29,8 @@ struct DDim { template explicit DDim(const Dim& in) : var(in) {} + /*implicit*/ DDim(std::initializer_list init_list); + template DDim& operator=(const Dim& in) { var = in; @@ -57,6 +59,8 @@ struct DDim { DDim operator+(DDim d) const; DDim operator*(DDim d) const; + + ssize_t size() const; }; /** diff --git a/paddle/framework/ddim_test.cc b/paddle/framework/ddim_test.cc index 6a099f2aeb4aa117bca8695aa326fbd1272a43d6..9d18a2972ce62139430b240b4599854b14290a32 100644 --- a/paddle/framework/ddim_test.cc +++ b/paddle/framework/ddim_test.cc @@ -49,6 +49,7 @@ TEST(DDim, Equality) { // arity of a DDim EXPECT_EQ(paddle::framework::arity(ddim), 3); + EXPECT_EQ(ddim.size(), 3); // product of a DDim EXPECT_EQ(paddle::framework::product(vddim), 45); diff --git a/paddle/framework/op_registry.h b/paddle/framework/op_registry.h index 41bdb65f8e9bbbf63ec6e62e8c2243cc3d6f21de..c41fe10729501698fd07f59456f64ac26df77f08 100644 --- a/paddle/framework/op_registry.h +++ b/paddle/framework/op_registry.h @@ -1,6 +1,7 @@ #pragma once #include +#include #include #include #include @@ -197,6 +198,8 @@ Add a mark to which output is temporary is helpful for future optimization. class OpRegistry { using OpCreator = std::function; + using VarIndexMap = std::unordered_map; + using VarNameList = std::vector; public: template @@ -211,24 +214,64 @@ class OpRegistry { op_proto.IsInitialized(), "Fail to initialize %s's OpProto, because %s is not initialized", op_type, op_proto.InitializationErrorString()); + + VarIndexMaps()[op_type].reset(new VarIndexMap()); + auto& varmap = *VarIndexMaps()[op_type]; + int idx = 0; + for (auto& var : op_proto.inputs()) { + varmap[var.name()] = idx++; + } + idx = 0; + for (auto& var : op_proto.outputs()) { + varmap[var.name()] = idx++; + } + } + + static OperatorPtr CreateOp(const std::string& type, + const VarNameList& inputs, + const VarNameList& outputs, + const AttributeMap& attrs) { + auto op_create_it = creators().find(type); + PADDLE_ENFORCE(op_create_it != creators().end(), + "Operator %s cannot be found", type); + + auto op = op_create_it->second(); + op->type_ = type; + op->inputs_ = inputs; + op->outputs_ = outputs; + op->attrs_ = attrs; + op_checkers().at(type).Check(op->attrs_); + + GenerateTempVariableName(op); + + { + auto var_index_it = VarIndexMaps().find(type); + if (var_index_it != VarIndexMaps().end()) { + op->in_out_idxs_ = var_index_it->second; + } + } + + op->Init(); + return OperatorPtr(op); } static OperatorPtr CreateOp(const OpDesc& op_desc) { - std::string op_type = op_desc.type(); - OperatorPtr op(creators().at(op_type)()); - op->type_ = op_desc.type(); - op->inputs_.reserve((size_t)op_desc.inputs_size()); + std::vector inputs; + 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::back_inserter(inputs)); + + std::vector outputs; + outputs.reserve((size_t)op_desc.outputs_size()); std::copy(op_desc.outputs().begin(), op_desc.outputs().end(), - std::back_inserter(op->outputs_)); + std::back_inserter(outputs)); + + AttributeMap attrs; for (auto& attr : op_desc.attrs()) { - op->attrs_[attr.name()] = AttrTypeHelper::GetAttrValue(attr); + attrs[attr.name()] = AttrTypeHelper::GetAttrValue(attr); } - op_checkers().at(op_type).Check(op->attrs_); - op->Init(); - return op; + + return CreateOp(op_desc.type(), inputs, outputs, attrs); } static std::unordered_map& protos() { @@ -237,6 +280,23 @@ class OpRegistry { }; private: + static std::unordered_map>& + VarIndexMaps() { + static std::unordered_map> maps_; + return maps_; + } + + static void GenerateTempVariableName(OperatorBase* op) { + static std::atomic gUniqId(0UL); + for (auto& outname : op->outputs_) { + if (outname == OperatorBase::TMP_VAR_NAME()) { + outname += op->type_; + outname += "@"; + outname += std::to_string(gUniqId.fetch_add(1)); + } + } + } + static std::unordered_map& creators() { static std::unordered_map creators_; return creators_; @@ -278,7 +338,7 @@ class OpRegisterHelper { /** * Macro to Register OperatorKernel. */ -#define REGISTER_OP_KERNEL(type, DEVICE_TYPE, PlaceType, KernelType) \ +#define REGISTER_OP_KERNEL(type, DEVICE_TYPE, PlaceType, ...) \ STATIC_ASSERT_GLOBAL_NAMESPACE( \ __reg_op_kernel_##type##_##DEVICE_TYPE##__, \ "REGISTER_OP_KERNEL must be in global namespace"); \ @@ -287,17 +347,19 @@ class OpRegisterHelper { ::paddle::framework::OperatorWithKernel::OpKernelKey key; \ key.place_ = PlaceType(); \ ::paddle::framework::OperatorWithKernel::AllOpKernels()[#type][key] \ - .reset(new KernelType()); \ + .reset(new __VA_ARGS__()); \ } \ }; \ static __op_kernel_register__##type##__ __reg_kernel_##type##__; \ int __op_kernel_register_##type##_handle_##DEVICE_TYPE##__() { return 0; } -#define REGISTER_OP_GPU_KERNEL(type, KernelType) \ - REGISTER_OP_KERNEL(type, GPU, ::paddle::platform::GPUPlace, KernelType) +// (type, KernelType) +#define REGISTER_OP_GPU_KERNEL(type, ...) \ + REGISTER_OP_KERNEL(type, GPU, ::paddle::platform::GPUPlace, __VA_ARGS__) -#define REGISTER_OP_CPU_KERNEL(type, KernelType) \ - REGISTER_OP_KERNEL(type, CPU, ::paddle::platform::CPUPlace, KernelType) +// (type, KernelType) +#define REGISTER_OP_CPU_KERNEL(type, ...) \ + REGISTER_OP_KERNEL(type, CPU, ::paddle::platform::CPUPlace, __VA_ARGS__) /** * Macro to mark what Operator and Kernel we will use and tell the compiler to diff --git a/paddle/framework/operator.cc b/paddle/framework/operator.cc index 7756162a872db6de3f932a09e4b7525a2fde70da..36479830535cdd49c93d965e6b68981012097b71 100644 --- a/paddle/framework/operator.cc +++ b/paddle/framework/operator.cc @@ -12,30 +12,76 @@ 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 + #include "paddle/framework/operator.h" namespace paddle { namespace framework { +const std::string& OperatorBase::Input(const std::string& name) const { + auto it = in_out_idxs_->find(name); + PADDLE_ENFORCE(it != in_out_idxs_->end(), "no key [%s] in in_out_idxs_", + name); + + if (attrs_.count("input_format") == 0) { + return inputs_[it->second]; + } else { + const auto& input_format = GetAttr>("input_format"); + int idx = input_format[it->second]; + return inputs_.at(idx); + } +} + +std::vector OperatorBase::Inputs(const std::string& name) const { + auto input_format = GetAttr>("input_format"); + auto offset = in_out_idxs_->at(name); + + return std::vector{ + inputs_.begin() + input_format.at(offset), + inputs_.begin() + input_format.at(offset + 1)}; +} + +const std::string& OperatorBase::Output(const std::string& name) const { + auto it = in_out_idxs_->find(name); + PADDLE_ENFORCE(it != in_out_idxs_->end(), "no key [%s] in in_out_idxs_", + name); + + if (attrs_.count("output_format") == 0) { + return outputs_[it->second]; + } else { + const auto& output_format = GetAttr>("output_format"); + int idx = output_format[it->second]; + return outputs_.at(idx); + } +} + +std::vector OperatorBase::Outputs(const std::string& name) const { + auto output_format = GetAttr>("output_format"); + auto offset = in_out_idxs_->at(name); + + return std::vector{ + outputs_.begin() + output_format.at(offset), + outputs_.begin() + output_format.at(offset + 1)}; +} + std::string OperatorBase::DebugString() const { std::stringstream ss; - ss << "=================\n"; - ss << "type = " << type_ << "\n"; - ss << "inputs = ["; - for (auto& ipt : inputs_) { - ss << ipt << ", "; - } - ss << "]\n"; - ss << "outputs = ["; - for (auto& opt : outputs_) { - ss << opt << ", "; + ss << "Op(" << type_ << "), inputs:("; + for (size_t i = 0; i < inputs_.size(); ++i) { + ss << inputs_[i]; + if (i != inputs_.size() - 1) { + ss << ", "; + } } - ss << "]\n"; - ss << "attr_keys = ["; - for (auto& attr : attrs_) { - ss << attr.first << ", "; + ss << "), outputs:("; + for (size_t i = 0; i < outputs_.size(); ++i) { + ss << outputs_[i]; + if (i != outputs_.size() - 1) { + ss << ", "; + } } - ss << "]\n"; + ss << ")."; return ss.str(); } diff --git a/paddle/framework/operator.h b/paddle/framework/operator.h index b62cac6d277e3b635938a048d9e6ce58d03c327b..4ae31b213fe7845314b23ec42530b37ed0fd8ae1 100644 --- a/paddle/framework/operator.h +++ b/paddle/framework/operator.h @@ -14,18 +14,20 @@ limitations under the License. */ #pragma once -#include -#include -#include -#include -#include -#include -#include #include #include #include #include +#include "paddle/framework/attr_checker.h" +#include "paddle/framework/op_desc.pb.h" +#include "paddle/framework/op_proto.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" + namespace paddle { namespace framework { @@ -39,6 +41,13 @@ using OperatorPtr = std::shared_ptr; */ class OperatorBase { public: + /// If a variable is a empty variable, that name will be used. + static std::string EMPTY_VAR_NAME() { return "@EMPTY@"; } + + /// If a variable is a temporary variable, that name will be set in Python, + /// but it will be convert to a unique name in scope after OpCreator. + static std::string TMP_VAR_NAME() { return "@TEMP@"; } + virtual ~OperatorBase() {} template @@ -62,11 +71,69 @@ class OperatorBase { virtual void Run(const ScopePtr& scope, const platform::DeviceContext& dev_ctx) const = 0; + // Get a input with argument's name described in `op_proto` + const std::string& Input(const std::string& name) const; + // Get a input which has multiple variables. + // TODO add a vector_view to prevent memory copy. + std::vector Inputs(const std::string& name) const; + // Get a output with argument's name described in `op_proto` + const std::string& Output(const std::string& name) const; + // Get an output which has multiple variables. + // TODO add a vector_view to prevent memory copy. + std::vector Outputs(const std::string& name) const; + public: std::string type_; std::vector inputs_; std::vector outputs_; AttributeMap attrs_; + // store the arguments' offset described in op_desc. + std::shared_ptr> in_out_idxs_; +}; + +class KernelContext { + public: + KernelContext(const OperatorBase* op, const std::shared_ptr& 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 Variable* Input(const std::string& name) const { + return scope_->GetVariable(op_.Input(name)); + } + + const Variable* Output(const std::string& name) const { + return scope_->GetVariable(op_.Output(name)); + } + + const std::vector Inputs(const std::string& name) const { + auto names = op_.Inputs(name); + std::vector res; + std::transform( + names.begin(), names.end(), res.begin(), + [this](const std::string& name) { return scope_->GetVariable(name); }); + return res; + } + + const std::vector Outputs(const std::string& name) const { + auto names = op_.Outputs(name); + std::vector res; + std::transform( + names.begin(), names.end(), res.begin(), + [this](const std::string& name) { return scope_->GetVariable(name); }); + return res; + } + + const OperatorBase& op_; + const std::shared_ptr& scope_; + const platform::DeviceContext& device_context_; }; class OpKernel { @@ -77,25 +144,6 @@ class OpKernel { * 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 ScopePtr& 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 ScopePtr& scope_; - const platform::DeviceContext& device_context_; - }; - virtual void Compute(const KernelContext& context) const = 0; virtual ~OpKernel() {} @@ -140,7 +188,7 @@ class OperatorWithKernel : public OperatorBase { void Run(const ScopePtr& 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)); + opKernel->Compute(KernelContext(this, scope, dev_ctx)); } static std::unordered_map& @@ -148,6 +196,7 @@ class OperatorWithKernel : public OperatorBase { static std::unordered_map g_all_op_kernels; return g_all_op_kernels; } + void InferShape(const std::shared_ptr& scope) const final { std::vector ins; VarNamesToTensors(scope, inputs_, &ins); diff --git a/paddle/framework/operator_test.cc b/paddle/framework/operator_test.cc index 19ac4ecafa21d0a6fde57ef5e867670d7823fde0..8e55d0111f39b2f632cf5a49c2ad3f210683652c 100644 --- a/paddle/framework/operator_test.cc +++ b/paddle/framework/operator_test.cc @@ -30,7 +30,6 @@ class OpWithoutKernelTest : public OperatorBase { op_run_num++; ASSERT_EQ((int)inputs_.size(), 1); ASSERT_EQ((int)outputs_.size(), 1); - ASSERT_NEAR(GetAttr("scale"), 3.14, 1e-5); ASSERT_EQ(scope->GetVariable(inputs_[0]), nullptr); ASSERT_EQ(x, 1); ASSERT_NE(scope->GetVariable(outputs_[0]), nullptr); @@ -86,9 +85,11 @@ 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("scale", "scale of cosine op"); + AddInput("x", "input of test op"); + AddOutput("y", "output of test op"); + AddAttr("scale", "scale of cosine op") + .SetDefault(1.0) + .LargerThan(0.0); AddComment("This is test op"); } }; @@ -101,13 +102,68 @@ class OpWithKernelTest : public OperatorWithKernel { const std::vector& outputs) const override {} }; +template class CPUKernelTest : public OpKernel { public: - void Compute(const KernelContext& context) const { + void Compute(const KernelContext& ctx) const { + std::cout << "this is cpu kernel" << std::endl; + std::cout << ctx.op_.DebugString() << std::endl; cpu_kernel_run_num++; - ASSERT_EQ((int)context.op_.inputs_.size(), 1); - ASSERT_EQ((int)context.op_.outputs_.size(), 1); - ASSERT_NEAR(context.op_.GetAttr("scale"), 3.14, 1e-5); + ASSERT_EQ(ctx.op_.Input("x"), "IN1"); + ASSERT_EQ(ctx.op_.Output("y"), "OUT1"); + } +}; + +// multiple inputs test +class OperatorMultiInputsTest : public OperatorBase { + public: + void Init() override { x = 1; } + void InferShape(const std::shared_ptr& scope) const override {} + void Run(const std::shared_ptr& scope, + const platform::DeviceContext& dev_ctx) const override { + ASSERT_EQ(scope->GetVariable(inputs_[0]), nullptr); + ASSERT_EQ(x, 1); + ASSERT_NE(scope->GetVariable(outputs_[0]), nullptr); + ASSERT_EQ(Input("x"), "IN1"); + ASSERT_EQ(Input("y"), "OUT1"); + } + + public: + float x = 0; +}; + +class OpKernelTestMultiInputsProtoAndCheckerMaker + : public OpProtoAndCheckerMaker { + public: + OpKernelTestMultiInputsProtoAndCheckerMaker(OpProto* proto, + OpAttrChecker* op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { + AddInputs("xs", "inputs of test op"); + AddInput("k", "input of test op"); + AddOutputs("ys", "outputs of test op"); + AddAttr("scale", "scale of cosine op") + .SetDefault(1.0) + .LargerThan(0.0); + AddComment("This is test op"); + } +}; + +class CPUKernalMultiInputsTest : public OpKernel { + public: + void Compute(const KernelContext& ctx) const { + auto xs = ctx.op_.Inputs("xs"); + ASSERT_EQ(xs.size(), 3UL); + ASSERT_EQ(xs[0], "x0"); + ASSERT_EQ(xs[1], "x1"); + ASSERT_EQ(xs[2], "x2"); + + auto k = ctx.op_.Input("k"); + ASSERT_EQ(k, "k0"); + + auto ys = ctx.op_.Outputs("ys"); + ASSERT_EQ(ys.size(), 2UL); + ASSERT_EQ(ys[0], "y0"); + ASSERT_EQ(ys[1], "y1"); } }; @@ -116,8 +172,10 @@ class CPUKernelTest : public OpKernel { REGISTER_OP(op_with_kernel, paddle::framework::OpWithKernelTest, paddle::framework::OpKernelTestProtoAndCheckerMaker); -REGISTER_OP_CPU_KERNEL(op_with_kernel, paddle::framework::CPUKernelTest); +REGISTER_OP_CPU_KERNEL(op_with_kernel, + paddle::framework::CPUKernelTest); +// test with single input TEST(OpKernel, all) { paddle::framework::OpDesc op_desc; op_desc.set_type("op_with_kernel"); @@ -137,3 +195,47 @@ TEST(OpKernel, all) { op->Run(scope, cpu_device_context); ASSERT_EQ(paddle::framework::cpu_kernel_run_num, 1); } + +REGISTER_OP(op_multi_inputs_with_kernel, paddle::framework::OpWithKernelTest, + paddle::framework::OpKernelTestMultiInputsProtoAndCheckerMaker); +REGISTER_OP_CPU_KERNEL(op_multi_inputs_with_kernel, + paddle::framework::CPUKernalMultiInputsTest); + +// test with multi inputs +TEST(OpKernel, multi_inputs) { + using namespace paddle::framework; + + OpDesc op_desc; + op_desc.set_type("op_multi_inputs_with_kernel"); + *op_desc.mutable_inputs()->Add() = "x0"; + *op_desc.mutable_inputs()->Add() = "x1"; + *op_desc.mutable_inputs()->Add() = "x2"; + *op_desc.mutable_inputs()->Add() = "k0"; + *op_desc.mutable_outputs()->Add() = "y0"; + *op_desc.mutable_outputs()->Add() = "y1"; + auto attr = op_desc.mutable_attrs()->Add(); + attr->set_name("scale"); + attr->set_type(paddle::framework::AttrType::FLOAT); + attr->set_f(3.14); + + auto attr0 = op_desc.mutable_attrs()->Add(); + attr0->set_name("input_format"); + attr0->set_type(paddle::framework::AttrType::INTS); + auto input_format = attr0->mutable_ints(); + input_format->Add(0); // x0 + input_format->Add(3); // k + input_format->Add(4); // end + + auto attr1 = op_desc.mutable_attrs()->Add(); + attr1->set_name("output_format"); + attr1->set_type(paddle::framework::AttrType::INTS); + auto output_format = attr1->mutable_ints(); + output_format->Add(0); // y0 + output_format->Add(2); // y1 + + paddle::platform::CPUDeviceContext cpu_device_context; + auto scope = std::make_shared(); + + OperatorPtr op(paddle::framework::OpRegistry::CreateOp(op_desc)); + op->Run(scope, cpu_device_context); +} diff --git a/paddle/framework/tensor.cc b/paddle/framework/tensor.cc new file mode 100644 index 0000000000000000000000000000000000000000..964f15ab66bca7da75824e192e61600c29e572c0 --- /dev/null +++ b/paddle/framework/tensor.cc @@ -0,0 +1,19 @@ +/* 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 + +namespace paddle { +namespace framework {} +} // namespace paddle diff --git a/paddle/framework/tensor.h b/paddle/framework/tensor.h index 62e0710a8244ce80e35d2cf9a922c4fd9f1a1b69..3dcd8d08970e16539cadeef23ef07f153483937d 100644 --- a/paddle/framework/tensor.h +++ b/paddle/framework/tensor.h @@ -17,19 +17,24 @@ limitations under the License. */ #include #include #include +#include #include "paddle/framework/ddim.h" #include "paddle/framework/enforce.h" #include "paddle/memory/memory.h" #include "paddle/platform/place.h" namespace paddle { +namespace pybind { +namespace details { // forward declare +template +struct CastToPyBufferImpl; +} // namespace details +} // namespace pybind namespace framework { class Tensor { public: - Tensor() : numel_(0), offset_(0) {} - - Tensor& operator=(const Tensor& src) = delete; + Tensor() : offset_(0) {} template const T* data() const { @@ -39,21 +44,33 @@ class Tensor { } template - T* mutable_data(DDim dims, paddle::platform::Place place) { + T* mutable_data(DDim dims, platform::Place place) { set_dims(dims); return mutable_data(place); } template - T* mutable_data(paddle::platform::Place place) { - PADDLE_ENFORCE(numel_ > 0, - "Tensor::numel_ must be larger than zero to call " + T* mutable_data(platform::Place place) { + PADDLE_ENFORCE(product(dims_) > 0, + "Tensor's numel must be larger than zero to call " "Tensor::mutable_data. Call Tensor::set_dim first."); if (holder_ == nullptr || !(holder_->place() == place) /* some versions of boost::variant don't have operator!= */ - || holder_->size() < numel_ * sizeof(T) + offset_) { - holder_.reset(new PlaceholderImpl(place, numel_ * sizeof(T))); + || holder_->size() < product(dims_) * sizeof(T) + offset_) { + if (platform::is_cpu_place(place)) { + holder_.reset(new PlaceholderImpl( + boost::get(place), product(dims_) * sizeof(T))); + } else if (platform::is_gpu_place(place)) { +#ifdef __CUDACC__ + holder_.reset(new PlaceholderImpl( + boost::get(place), product(dims_) * sizeof(T))); +#else + PADDLE_ENFORCE(true, "'GPUPlace' is not supported in CPU only device."); +#endif + } else { + PADDLE_ENFORCE(true, "Unknown 'place'."); + } offset_ = 0; } return reinterpret_cast(reinterpret_cast(holder_->ptr()) + @@ -69,12 +86,12 @@ class Tensor { } template - void CopyFrom(const Tensor& src, paddle::platform::Place dst_place) { + void CopyFrom(const Tensor& src, platform::Place dst_place) { PADDLE_ENFORCE(platform::is_cpu_place(src.holder_->place()) && platform::is_cpu_place(dst_place), "Tensor::CopyFrom only support CPU now."); src.CheckDims(); - size_t size = src.numel_ * sizeof(T); + size_t size = product(src.dims_) * sizeof(T); set_dims(src.dims()); const void* src_ptr = static_cast(src.data()); void* dst_ptr = static_cast(mutable_data(dst_place)); @@ -108,7 +125,6 @@ class Tensor { return; } dims_ = dims; - numel_ = product(dims_); } DDim dims() const { return dims_; } @@ -119,53 +135,55 @@ class Tensor { struct Placeholder { virtual ~Placeholder() {} virtual void* ptr() const = 0; - virtual paddle::platform::Place place() const = 0; + virtual platform::Place place() const = 0; virtual size_t size() const = 0; + virtual std::type_index type() const = 0; }; - template + template struct PlaceholderImpl : public Placeholder { private: + template class Deleter { public: - Deleter(platform::Place place) : place_(place) {} - void operator()(T* ptr) { - paddle::memory::Free(place_, static_cast(ptr)); - } + Deleter(PType place) : place_(place) {} + void operator()(T* ptr) { memory::Free(place_, static_cast(ptr)); } private: - paddle::platform::Place place_; + PType place_; }; public: - PlaceholderImpl(paddle::platform::Place place, size_t size) - : ptr_(static_cast(paddle::memory::Alloc(place, size)), - Deleter(place)), + PlaceholderImpl(PlaceType place, size_t size) + : ptr_(static_cast(memory::Alloc(place, size)), + Deleter(place)), place_(place), size_(size) {} virtual void* ptr() const { return static_cast(ptr_.get()); } virtual size_t size() const { return size_; } virtual paddle::platform::Place place() const { return place_; } + virtual std::type_index type() const { return std::type_index(typeid(T)); } - std::unique_ptr ptr_; - paddle::platform::Place place_; // record the place of ptr_. - size_t size_; // size of the memory block. + std::unique_ptr> ptr_; + platform::Place place_; // record the place of ptr_. + size_t size_; // size of the memory block. }; template inline void CheckDims() const { PADDLE_ENFORCE(holder_ != nullptr, "Tenosr holds no memory. Call Tensor::mutable_data first."); - PADDLE_ENFORCE(holder_->size() >= numel_ * sizeof(T) + offset_, + PADDLE_ENFORCE(holder_->size() >= product(dims_) * sizeof(T) + offset_, "Tensor's dims_ is out of bound. Call Tensor::mutable_data " "first to re-allocate memory."); } std::shared_ptr holder_; // holds the memory block if allocated. DDim dims_; - size_t numel_; // cache of `product(dims_)` size_t offset_; // marks the begin of tensor data area. + template + friend struct paddle::pybind::details::CastToPyBufferImpl; }; } // namespace framework diff --git a/paddle/framework/tensor_test.cc b/paddle/framework/tensor_test.cc index 255f69372f4f06609471b9ff7a9b9ce790fcddf0..84c6f0cf6558819440458688ca52b06c1cf11dd0 100644 --- a/paddle/framework/tensor_test.cc +++ b/paddle/framework/tensor_test.cc @@ -47,7 +47,7 @@ TEST(Tensor, DataAssert) { /* 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; @@ -72,7 +72,7 @@ TEST(Tensor, MutableData) { p2 = src_tensor.mutable_data(make_ddim({2, 2}), CPUPlace()); EXPECT_EQ(p1, p2); } - +#ifdef __CUDACC__ { Tensor src_tensor; float* p1 = nullptr; @@ -94,6 +94,7 @@ TEST(Tensor, MutableData) { p2 = src_tensor.mutable_data(make_ddim({2, 2}), GPUPlace()); EXPECT_EQ(p1, p2); } +#endif } TEST(Tensor, ShareDataFrom) { @@ -108,9 +109,11 @@ TEST(Tensor, ShareDataFrom) { dst_tensor.ShareDataFrom(src_tensor); } catch (EnforceNotMet err) { caught = true; - std::string msg = "Tenosr holds no memory. 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]); + std::string msg = + "Tenosr holds no memory. 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]); } } ASSERT_TRUE(caught); @@ -120,6 +123,7 @@ first."; const char* what = err.what(); for (size_t i = 0; i < msg.length(); ASSERT_EQ(src_tensor.data(), dst_tensor.data()); } +#ifdef __CUDACC__ { Tensor src_tensor; Tensor dst_tensor; @@ -127,6 +131,7 @@ first."; const char* what = err.what(); for (size_t i = 0; i < msg.length(); dst_tensor.ShareDataFrom(src_tensor); ASSERT_EQ(src_tensor.data(), dst_tensor.data()); } +#endif } TEST(Tensor, Slice) { @@ -155,6 +160,7 @@ TEST(Tensor, Slice) { EXPECT_EQ(src_data_address + 3 * 4 * 1 * sizeof(int), slice_data_address); } +#ifdef __CUDACC__ { Tensor src_tensor; src_tensor.mutable_data(make_ddim({6, 9}), GPUPlace()); @@ -176,6 +182,7 @@ TEST(Tensor, Slice) { EXPECT_EQ(slice_data_address, slice_mutable_data_address); EXPECT_EQ(src_data_address + 9 * 2 * sizeof(double), slice_data_address); } +#endif } TEST(Tensor, CopyFrom) { @@ -203,4 +210,3 @@ TEST(Tensor, CopyFrom) { EXPECT_EQ(dst_ptr[i], slice_ptr[i]); } } -*/ \ No newline at end of file diff --git a/paddle/function/CMakeLists.txt b/paddle/function/CMakeLists.txt index 1518a8a654cfb54376a49760dc5873733c916937..a5b14c0c71c18da1bb0b506c663f8680b1c3830a 100644 --- a/paddle/function/CMakeLists.txt +++ b/paddle/function/CMakeLists.txt @@ -11,7 +11,6 @@ if(WITH_GPU) endif() if(USE_NNPACK) - include(nnpack/nnpack.cmake) list(APPEND cpp_files nnpack/NNPACKConvOp.cpp) if(WITH_TESTING) add_unittest(NNPACKConvOpTest nnpack/NNPACKConvOpTest.cpp) diff --git a/paddle/function/nnpack/NNPACKConvOp.cpp b/paddle/function/nnpack/NNPACKConvOp.cpp index e8080c3d714b324f072a380f738b9764477dfe04..f0ec77a5d00333993427fb8d0bc938c884e50c95 100644 --- a/paddle/function/nnpack/NNPACKConvOp.cpp +++ b/paddle/function/nnpack/NNPACKConvOp.cpp @@ -16,7 +16,7 @@ limitations under the License. */ #include "paddle/function/ConvOp.h" DEFINE_bool(nnpack_allocate_outside, - false, + true, "Allocate and free workspace memory outside the NNPACK interface."); DEFINE_int32(nnpack_num_threads, 0, @@ -58,18 +58,10 @@ public: workspaceBuffer_ = nullptr; workspaceSize_ = 0; - threadpool_ = nullptr; - if (FLAGS_nnpack_num_threads) { - threadpool_ = pthreadpool_create(FLAGS_nnpack_num_threads); - VLOG(3) << "Number of threads " - << pthreadpool_get_threads_count(threadpool_); - } + create_nnpack_threadpool(); } ~NNPACKConvFunction() { - if (threadpool_) { - pthreadpool_destroy(threadpool_); - } if (workspaceBuffer_) { free(workspaceBuffer_); } @@ -225,14 +217,25 @@ public: } } + static void create_nnpack_threadpool() { + if (FLAGS_nnpack_num_threads && threadpool_ == nullptr) { + threadpool_ = pthreadpool_create(FLAGS_nnpack_num_threads); + VLOG(3) << "Number of threads " + << pthreadpool_get_threads_count(threadpool_); + } + } + private: nnp_convolution_algorithm algorithm_; nnp_convolution_transform_strategy transform_strategy_; void* workspaceBuffer_; size_t workspaceSize_; - pthreadpool_t threadpool_; + static pthreadpool_t threadpool_; }; +template +pthreadpool_t NNPACKConvFunction::threadpool_ = nullptr; + REGISTER_TYPED_FUNC(NNPACKConv, CPU, NNPACKConvFunction); } // namespace paddle diff --git a/paddle/operators/CMakeLists.txt b/paddle/operators/CMakeLists.txt index 40bb326512c118178184120d4bc26dc127689ff3..f47c3a42083f289d6c99fe6df62e3478e0363e31 100644 --- a/paddle/operators/CMakeLists.txt +++ b/paddle/operators/CMakeLists.txt @@ -1,6 +1,49 @@ -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() +function(op_library TARGET) + # op_library is a function to create op library. The interface is same as + # cc_library. But it handle split GPU/CPU code and link some common library + # for ops. + set(cc_srcs) + set(cu_srcs) + set(op_common_deps operator op_registry) + set(options "") + set(oneValueArgs "") + set(multiValueArgs SRCS DEPS) + cmake_parse_arguments(op_library "${options}" "${oneValueArgs}" + "${multiValueArgs}" ${ARGN}) + + foreach(src ${op_library_SRCS}) + if (${src} MATCHES ".*\\.cu$") + list(APPEND cu_srcs ${src}) + elseif(${src} MATCHES ".*\\.cc$") + list(APPEND cc_srcs ${src}) + else() + message(FATAL_ERROR "${TARGET} Source file ${src} should only be .cc or .cu") + endif() + endforeach() + + list(LENGTH cc_srcs cc_srcs_len) + if (${cc_srcs_len} EQUAL 0) + message(FATAL_ERROR "The op library ${TARGET} should contains at least one .cc file") + endif() + + list(LENGTH cu_srcs cu_srcs_len) + if (${cu_srcs_len} EQUAL 0) + message(WARNING "The op library ${TARGET} not support GPU!") + endif() + + if (WITH_GPU) + nv_library(${TARGET} SRCS ${cc_srcs} ${cu_srcs} DEPS ${op_library_DEPS} + ${op_common_deps}) + else() + cc_library(${TARGET} SRCS ${cc_srcs} DEPS ${op_library_DEPS} + ${op_common_deps}) + endif() +endfunction() + +op_library(add_op SRCS add_op.cc add_op.cu) cc_test(add_op_test SRCS add_op_test.cc DEPS add_op) + +op_library(mul_op SRCS mul_op.cc mul_op.cu) +op_library(rowwise_add_op SRCS rowwise_add_op.cu rowwise_add_op.cc) +op_library(sigmoid_op SRCS sigmoid_op.cu sigmoid_op.cc) +op_library(softmax_op SRCS softmax_op.cc softmax_op.cu) diff --git a/paddle/operators/add_op.cc b/paddle/operators/add_op.cc index 522b23cbc49f025a1ff674ce157358899d690e6d..355c92a50481fb00e81da94381fa1944f1825ed7 100644 --- a/paddle/operators/add_op.cc +++ b/paddle/operators/add_op.cc @@ -31,8 +31,7 @@ protected: "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()) + outputs[0]->set_dims(inputs[0]->dims()); } }; diff --git a/paddle/operators/add_op.h b/paddle/operators/add_op.h index 17d459dbc86af73fa86934a5ccce9da509c59c6b..000564f66dff2b20d17cee10e44aaca114c2c908 100644 --- a/paddle/operators/add_op.h +++ b/paddle/operators/add_op.h @@ -8,10 +8,10 @@ namespace operators { template class AddKernel : public framework::OpKernel { public: - void Compute(const KernelContext &context) const override { + void Compute(const framework::KernelContext &context) const override { LOG(INFO) << "Add kernel in " << typeid(Place).name(); } }; -} // namespace op +} // namespace operators } // namespace paddle diff --git a/paddle/operators/mul_op.cc b/paddle/operators/mul_op.cc new file mode 100644 index 0000000000000000000000000000000000000000..713b2a5dc83d8dd5a3d944101591d75cb19fe04f --- /dev/null +++ b/paddle/operators/mul_op.cc @@ -0,0 +1,60 @@ +/* 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 +#include +#include + +namespace paddle { +namespace operators { + +class MulOp : public framework::OperatorWithKernel { +protected: + void InferShape( + const std::vector &inputs, + const std::vector &outputs) const override { + PADDLE_ENFORCE(inputs.size() == 2, "The mul op must take two inputs"); + auto dim0 = inputs[0]->dims(); + auto dim1 = inputs[1]->dims(); + PADDLE_ENFORCE(dim0.size() == 2 && dim1.size() == 2, + "The input of mul op must be matrix"); + PADDLE_ENFORCE( + dim0[1] == dim1[0], + "First matrix's width must be equal with second matrix's height."); + PADDLE_ENFORCE(outputs.size() == 1, "The mul op must take one output"); + outputs[0]->set_dims({dim0[0], dim1[1]}); + } +}; + +class MulOpMaker : public framework::OpProtoAndCheckerMaker { +public: + MulOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker) + : framework::OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("X", "The first input of mul op"); + AddInput("Y", "The second input of mul op"); + AddOutput("Out", "The output of mul op"); + AddComment(R"DOC( +Two Element Mul Operator. + +The equation is: Out = X * Y +)DOC"); + } +}; + +} // namespace operators +} // namespace paddle + +REGISTER_OP(mul, paddle::operators::MulOp, paddle::operators::MulOpMaker); +REGISTER_OP_CPU_KERNEL( + mul, paddle::operators::MulKernel); diff --git a/paddle/operators/mul_op.cu b/paddle/operators/mul_op.cu new file mode 100644 index 0000000000000000000000000000000000000000..201723df247993c5cc1650edbe4f74441e3217d4 --- /dev/null +++ b/paddle/operators/mul_op.cu @@ -0,0 +1,20 @@ +/* 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 +#include + +REGISTER_OP_GPU_KERNEL(mul, + paddle::operators::MulKernel); \ No newline at end of file diff --git a/paddle/operators/mul_op.h b/paddle/operators/mul_op.h new file mode 100644 index 0000000000000000000000000000000000000000..ce8a0169e0cbaafb7e90d2227c9597fff463883d --- /dev/null +++ b/paddle/operators/mul_op.h @@ -0,0 +1,31 @@ +/* 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 +#include + +namespace paddle { +namespace operators { + +template +class MulKernel : public framework::OpKernel { +public: + void Compute(const framework::KernelContext &context) const override { + LOG(INFO) << "Mul kernel in " << typeid(Place).name(); + } +}; +} // namespace operators +} // namespace paddle diff --git a/paddle/operators/rowwise_add_op.cc b/paddle/operators/rowwise_add_op.cc new file mode 100644 index 0000000000000000000000000000000000000000..414bafd0468033813d50d4d6723e68ee9347eaac --- /dev/null +++ b/paddle/operators/rowwise_add_op.cc @@ -0,0 +1,61 @@ +/* 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 +#include +namespace paddle { +namespace operators { + +class RowWiseAddOp : public framework::OperatorWithKernel { +protected: + void InferShape( + const std::vector &inputs, + const std::vector &outputs) const override { + PADDLE_ENFORCE(inputs.size() == 2UL, "Two inputs is needed by rowwise add"); + auto dim0 = inputs[0]->dims(); + auto dim1 = inputs[1]->dims(); + + PADDLE_ENFORCE(dim0.size() == 2, "Input 0 must be matrix"); + PADDLE_ENFORCE(dim1.size() == 1, "The second input must be vector"); + PADDLE_ENFORCE(dim0[1] == dim1[0], "The width of two input must be same"); + PADDLE_ENFORCE(outputs.size() == 1, "The output size must be 1"); + outputs[0]->set_dims(inputs[0]->dims()); + } +}; + +class RowWiseAddOpMaker : public framework::OpProtoAndCheckerMaker { +public: + RowWiseAddOpMaker(framework::OpProto *proto, + framework::OpAttrChecker *op_checker) + : framework::OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("X", "The left input of row-wise add op, must be matrix"); + AddInput("b", "The right input of row-wise add op, must be vector"); + AddOutput("Out", "The output of row-wise add op"); + AddComment(R"DOC(Row-wise Add operator + +for i in xrange(X.shape[0]): + Out = X[i] + b +)DOC"); + } +}; + +} // namespace operators +} // namespace paddle + +REGISTER_OP(rowwise_add, + paddle::operators::RowWiseAddOp, + paddle::operators::RowWiseAddOpMaker); +REGISTER_OP_CPU_KERNEL( + rowwise_add, + paddle::operators::RowWiseAddKernel); diff --git a/paddle/operators/rowwise_add_op.cu b/paddle/operators/rowwise_add_op.cu new file mode 100644 index 0000000000000000000000000000000000000000..2c4bfbf93a1064a47a19c991fa6655b5d67e83cb --- /dev/null +++ b/paddle/operators/rowwise_add_op.cu @@ -0,0 +1,6 @@ +#include +#include + +REGISTER_OP_GPU_KERNEL( + rowwise_add, + paddle::operators::RowWiseAddKernel); diff --git a/paddle/operators/rowwise_add_op.h b/paddle/operators/rowwise_add_op.h new file mode 100644 index 0000000000000000000000000000000000000000..35f43e6376be6239021e7a9bacb849b93d5226b5 --- /dev/null +++ b/paddle/operators/rowwise_add_op.h @@ -0,0 +1,31 @@ +/* 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 +#include + +namespace paddle { +namespace operators { + +template +class RowWiseAddKernel : public framework::OpKernel { +public: + void Compute(const framework::KernelContext &context) const override { + LOG(INFO) << "RowWiseAdd kernel in " << typeid(Place).name(); + } +}; + +} // namespace operators +} // namespace paddle diff --git a/paddle/operators/sigmoid_op.cc b/paddle/operators/sigmoid_op.cc new file mode 100644 index 0000000000000000000000000000000000000000..45ae277c538ca90716febaf2f3d92b560149d147 --- /dev/null +++ b/paddle/operators/sigmoid_op.cc @@ -0,0 +1,49 @@ +/* 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 +#include +namespace paddle { +namespace operators { + +class SigmoidOp : public framework::OperatorWithKernel { +protected: + void InferShape( + const std::vector &inputs, + const std::vector &outputs) const override { + PADDLE_ENFORCE(inputs.size() == 1, "Sigmoid Op only have one input"); + PADDLE_ENFORCE(outputs.size() == 1, "Sigmoid Op only have one output"); + outputs[0]->set_dims(inputs[0]->dims()); + } +}; + +class SigmoidOpMaker : public framework::OpProtoAndCheckerMaker { +public: + SigmoidOpMaker(framework::OpProto *proto, + framework::OpAttrChecker *op_checker) + : framework::OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("X", "sigmoid input"); + AddInput("Y", "sigmoid output"); + AddComment("Sigmoid function"); + } +}; + +} // namespace operators +} // namespace paddle + +REGISTER_OP(sigmoid, + paddle::operators::SigmoidOp, + paddle::operators::SigmoidOpMaker); +REGISTER_OP_CPU_KERNEL( + sigmoid, paddle::operators::SigmoidKernel); diff --git a/paddle/operators/sigmoid_op.cu b/paddle/operators/sigmoid_op.cu new file mode 100644 index 0000000000000000000000000000000000000000..79d5222348f610b1b016a2df06e8b1e0a4fac66c --- /dev/null +++ b/paddle/operators/sigmoid_op.cu @@ -0,0 +1,5 @@ +#include +#include + +REGISTER_OP_GPU_KERNEL( + sigmoid, paddle::operators::SigmoidKernel); diff --git a/paddle/operators/sigmoid_op.h b/paddle/operators/sigmoid_op.h new file mode 100644 index 0000000000000000000000000000000000000000..42173343f3e364729ecd190fc554b8c45ecfca8d --- /dev/null +++ b/paddle/operators/sigmoid_op.h @@ -0,0 +1,31 @@ +/* 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 +#include + +namespace paddle { +namespace operators { + +template +class SigmoidKernel : public framework::OpKernel { +public: + void Compute(const framework::KernelContext &context) const override { + LOG(INFO) << "Sigmoid kernel in " << typeid(Place).name(); + } +}; +} // namespace operators +} // namespace paddle diff --git a/paddle/operators/softmax_op.cc b/paddle/operators/softmax_op.cc new file mode 100644 index 0000000000000000000000000000000000000000..4ca7be359e210d7a31aef94e498f37a1ad4879a2 --- /dev/null +++ b/paddle/operators/softmax_op.cc @@ -0,0 +1,49 @@ +/* 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 +#include + +namespace paddle { +namespace operators { + +class SoftmaxOp : public framework::OperatorWithKernel { +protected: + void InferShape( + const std::vector &inputs, + const std::vector &outputs) const override { + PADDLE_ENFORCE(inputs.size() == 1, "Only one input is need for softmax"); + PADDLE_ENFORCE(outputs.size() == 1, "Only one output is need for softmax"); + + outputs[0]->set_dims(inputs[0]->dims()); + } +}; + +class SoftmaxOpMaker : public framework::OpProtoAndCheckerMaker { +public: + SoftmaxOpMaker(framework::OpProto *proto, + framework::OpAttrChecker *op_checker) + : OpProtoAndCheckerMaker(proto, op_checker) { + AddInput("X", "input of softmax"); + AddOutput("Y", "output of softmax"); + AddComment("Softmax Op"); + } +}; + +} // namespace operators +} // namespace paddle + +namespace ops = paddle::operators; + +REGISTER_OP(softmax, ops::SoftmaxOp, ops::SoftmaxOpMaker); +REGISTER_OP_CPU_KERNEL(softmax, ops::SoftmaxKernel); diff --git a/paddle/operators/softmax_op.cu b/paddle/operators/softmax_op.cu new file mode 100644 index 0000000000000000000000000000000000000000..903eef1b62231d65e2f9ec7a1f57fca0f4c4605c --- /dev/null +++ b/paddle/operators/softmax_op.cu @@ -0,0 +1,5 @@ +#include +#include + +REGISTER_OP_GPU_KERNEL( + softmax, paddle::operators::SoftmaxKernel); diff --git a/paddle/operators/softmax_op.h b/paddle/operators/softmax_op.h new file mode 100644 index 0000000000000000000000000000000000000000..74e9e2786b11b9a87cd9700d8458d4e611a8d4bb --- /dev/null +++ b/paddle/operators/softmax_op.h @@ -0,0 +1,31 @@ +/* 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 +#include + +namespace paddle { +namespace operators { + +template +class SoftmaxKernel : public framework::OpKernel { +public: + void Compute(const framework::KernelContext &context) const override { + LOG(INFO) << "Softmax kernel in " << typeid(Place).name(); + } +}; +} // namespace operators +} // namespace paddle diff --git a/paddle/pybind/CMakeLists.txt b/paddle/pybind/CMakeLists.txt index 8564a5f5fe474dbd55ab3e413f9c2cf93f88e38e..00b14a94321990baef6de35df547eed04b3da04f 100644 --- a/paddle/pybind/CMakeLists.txt +++ b/paddle/pybind/CMakeLists.txt @@ -1 +1,2 @@ -cc_library(paddle_pybind SHARED SRCS pybind.cc DEPS pybind python add_op) +cc_library(paddle_pybind SHARED SRCS pybind.cc DEPS pybind python + add_op mul_op rowwise_add_op sigmoid_op softmax_op) diff --git a/paddle/pybind/pybind.cc b/paddle/pybind/pybind.cc index c1a025ed0492f10237ee552a9b854f1937aa465c..fc9c6544c3cbf5a804b2d052f738bd483d6bf41b 100644 --- a/paddle/pybind/pybind.cc +++ b/paddle/pybind/pybind.cc @@ -15,6 +15,8 @@ limitations under the License. */ #include #include #include +#include +#include #include #include #include @@ -24,10 +26,35 @@ namespace py = pybind11; namespace pd = paddle::framework; USE_OP(add_two); +USE_OP(softmax); +USE_OP(mul); +USE_OP(rowwise_add); +USE_OP(sigmoid); PYBIND11_PLUGIN(core) { py::module m("core", "C++ core of Paddle Paddle"); + py::class_(m, "Tensor", py::buffer_protocol()) + .def_buffer([](pd::Tensor& self) -> py::buffer_info { + return paddle::pybind::CastToPyBuffer(self); + }) + .def("get_dims", + [](const pd::Tensor& self) { return pd::vectorize(self.dims()); }) + .def("set_dims", + [](pd::Tensor& self, const std::vector& dim) { + self.set_dims(pd::make_ddim(dim)); + }) + .def("alloc_float", + [](pd::Tensor& self) { + self.mutable_data(paddle::platform::CPUPlace()); + }) + .def("alloc_int", + [](pd::Tensor& self) { + self.mutable_data(paddle::platform::CPUPlace()); + }) + .def("set", paddle::pybind::PyTensorSetFromArray) + .def("set", paddle::pybind::PyTensorSetFromArray); + py::class_(m, "Variable", R"DOC(Variable Class. All parameter, weight, gradient are variables in Paddle. @@ -38,7 +65,12 @@ All parameter, weight, gradient are variables in Paddle. *var.GetMutable() = val; }) .def("get_int", - [](const pd::Variable& var) -> int { return var.Get(); }); + [](const pd::Variable& var) -> int { return var.Get(); }) + .def("get_tensor", + [](pd::Variable& self) -> pd::Tensor* { + return self.GetMutable(); + }, + py::return_value_policy::reference); py::class_>(m, "Scope") .def(py::init&>()) @@ -63,6 +95,23 @@ All parameter, weight, gradient are variables in Paddle. } return ret_values; }); + m.def_submodule( + "var_names", + "The module will return special predefined variable name in Paddle") + .def("empty", pd::OperatorBase::EMPTY_VAR_NAME) + .def("temp", pd::OperatorBase::TMP_VAR_NAME); + + py::class_(m, "Operator") + .def("__str__", &pd::OperatorBase::DebugString) + .def_static("create", [](const std::string& protobin) { + pd::OpDesc desc; + PADDLE_ENFORCE(desc.ParsePartialFromString(protobin), + "Cannot parse user input to OpDesc"); + PADDLE_ENFORCE(desc.IsInitialized(), + "User OpDesc is not initialized, reason %s", + desc.InitializationErrorString()); + return pd::OpRegistry::CreateOp(desc); + }); return m.ptr(); } diff --git a/paddle/pybind/tensor_bind.h b/paddle/pybind/tensor_bind.h new file mode 100644 index 0000000000000000000000000000000000000000..b96516643ab55b9615ccafdc41d3290590987d95 --- /dev/null +++ b/paddle/pybind/tensor_bind.h @@ -0,0 +1,95 @@ +/* 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 +#include +#include + +namespace py = pybind11; + +namespace paddle { + +namespace pybind { + +namespace details { + +template +struct CastToPyBufferImpl; + +template +struct CastToPyBufferImpl { + py::buffer_info operator()(framework::Tensor &tensor) { + PADDLE_THROW("This type of tensor cannot be expose to Python"); + return py::buffer_info(); + } +}; + +template +struct CastToPyBufferImpl { + using CUR_TYPE = typename std::tuple_element>::type; + py::buffer_info operator()(framework::Tensor &tensor) { + PADDLE_ENFORCE(paddle::platform::is_cpu_place(tensor.holder_->place()), + "Only CPU tensor can cast to numpy array"); + + if (std::type_index(typeid(CUR_TYPE)) == tensor.holder_->type()) { + auto dim_vec = framework::vectorize(tensor.dims()); + std::vector dims_outside; + std::vector strides; + dims_outside.resize(dim_vec.size()); + strides.resize(dim_vec.size()); + + size_t prod = 1; + for (size_t i = dim_vec.size(); i != 0; --i) { + dims_outside[i - 1] = (size_t)dim_vec[i - 1]; + strides[i - 1] = sizeof(CUR_TYPE) * prod; + prod *= dims_outside[i - 1]; + } + + return py::buffer_info( + tensor.mutable_data(tensor.holder_->place()), + sizeof(CUR_TYPE), + py::format_descriptor::format(), + (size_t)framework::arity(tensor.dims()), + dims_outside, + strides); + } else { + constexpr bool less = I + 1 < std::tuple_size>::value; + return CastToPyBufferImpl()(tensor); + } + } +}; +} // namespace details +inline py::buffer_info CastToPyBuffer(framework::Tensor &tensor) { + auto buffer_info = details::CastToPyBufferImpl()(tensor); + return buffer_info; +} + +template +void PyTensorSetFromArray( + framework::Tensor &self, + py::array_t array) { + std::vector dims; + dims.reserve(array.ndim()); + for (size_t i = 0; i < array.ndim(); ++i) { + dims.push_back((int)array.shape()[i]); + } + + self.set_dims(framework::make_ddim(dims)); + auto *dst = self.mutable_data(paddle::platform::CPUPlace()); + std::memcpy(dst, array.data(), sizeof(T) * array.size()); +} + +} // namespace pybind +} // namespace paddle diff --git a/paddle/scripts/docker/build_android.sh b/paddle/scripts/docker/build_android.sh index bfa10c91553563bddac8c1b41bf21490fb89d3cf..56d290be4ab04a9f6974023159aa8571d27f8dd5 100644 --- a/paddle/scripts/docker/build_android.sh +++ b/paddle/scripts/docker/build_android.sh @@ -2,9 +2,9 @@ set -xe -mkdir -p /paddle/build -cd /paddle/build -rm -f /paddle/install 2>/dev/null || true +mkdir -p /paddle/build_android +cd /paddle/build_android +rm -rf /paddle/install 2>/dev/null || true cmake -DCMAKE_SYSTEM_NAME=Android \ -DANDROID_STANDALONE_TOOLCHAIN=$ANDROID_STANDALONE_TOOLCHAIN \ -DANDROID_ABI=armeabi-v7a \ @@ -21,6 +21,3 @@ cmake -DCMAKE_SYSTEM_NAME=Android \ .. make -j `nproc` make install - -export PATH=/paddle/install/bin:/paddle/install/opt/paddle/bin:$PATH -paddle version diff --git a/paddle/scripts/travis/check_style.sh b/paddle/scripts/travis/check_style.sh index 4754bdd4c80de9700d92b0e33ecfdfc582f42813..8049aeb7b00870220e59c981addf6d70a66877c7 100755 --- a/paddle/scripts/travis/check_style.sh +++ b/paddle/scripts/travis/check_style.sh @@ -13,6 +13,11 @@ export PATH=/usr/bin:$PATH pre-commit install clang-format --version +# set up go environment for running gometalinter +mkdir -p $GOPATH/src/github.com/PaddlePaddle/ +ln -sf $TRAVIS_BUILD_DIR $GOPATH/src/github.com/PaddlePaddle/Paddle +cd $GOPATH/src/github.com/PaddlePaddle/Paddle/go; glide install; cd - + if ! pre-commit run -a ; then git diff --exit-code fi diff --git a/python/paddle/v2/framework/create_op_creation_methods.py b/python/paddle/v2/framework/create_op_creation_methods.py index 2fcdfead25414ccf44e9bfa964c83b98c852f6be..c2a7ae7692b08762ffbc91726be7bfa90e8ddedb 100644 --- a/python/paddle/v2/framework/create_op_creation_methods.py +++ b/python/paddle/v2/framework/create_op_creation_methods.py @@ -1,11 +1,246 @@ import paddle.v2.framework.core as core import paddle.v2.framework.proto.op_proto_pb2 as op_proto_pb2 +import paddle.v2.framework.proto.op_desc_pb2 as op_desc_pb2 +import paddle.v2.framework.proto.attr_type_pb2 as attr_type_pb2 +import cStringIO def get_all_op_protos(): + """ + Get all registered op proto from Paddle C++ + :return: list of OpProto + """ protostrs = core.get_all_op_protos() ret_values = [] for pbstr in protostrs: op_proto = op_proto_pb2.OpProto.FromString(str(pbstr)) ret_values.append(op_proto) return ret_values + + +class OpDescCreationMethod(object): + """ + A Functor object to convert user input(use key word args) to OpDesc based on + OpProto. + + :param op_proto: The OpProto object. + :type op_proto: op_proto_pb2.OpProto + """ + + def __init__(self, op_proto): + if not isinstance(op_proto, op_proto_pb2.OpProto): + raise TypeError("Argument should be OpProto") + self.__op_proto__ = op_proto + + def __call__(self, *args, **kwargs): + """ + Convert user input to OpDesc. Only key-word args are supported. + :return: OpDesc based on user input + :rtype: op_desc_pb2.OpDesc + """ + if len(args) != 0: + raise ValueError("Only keyword arguments is supported by Paddle") + op_desc = op_desc_pb2.OpDesc() + + # Inputs + ipts, ipt_format, _ = OpDescCreationMethod.extract_input_or_output( + "input", kwargs, self.__op_proto__.inputs) + op_desc.inputs.extend(ipts) + if ipt_format is not None: + op_desc.attrs.extend([ipt_format]) + + # Outputs + outs, out_format, tmp_index = OpDescCreationMethod.extract_input_or_output( + "output", kwargs, self.__op_proto__.outputs) + op_desc.outputs.extend(outs) + if out_format is not None: + op_desc.attrs.extend([out_format]) + if len(tmp_index) != 0: + tmp_index_attr = op_desc.attrs.add() + tmp_index_attr.type = attr_type_pb2.INTS + tmp_index_attr.name = "temporary_index" + tmp_index_attr.ints.extend(tmp_index) + + # Types + op_desc.type = self.__op_proto__.type + + # Attrs + for attr in self.__op_proto__.attrs: + if attr.generated: + continue + user_defined_attr = kwargs.get(attr.name, None) + if user_defined_attr is not None: + new_attr = op_desc.attrs.add() + new_attr.name = attr.name + new_attr.type = attr.type + if attr.type == attr_type_pb2.INT: + new_attr.i = user_defined_attr + elif attr.type == attr_type_pb2.FLOAT: + new_attr.f = user_defined_attr + elif attr.type == attr_type_pb2.STRING: + new_attr.s = user_defined_attr + elif attr.type == attr_type_pb2.INTS: + new_attr.ints.extend(user_defined_attr) + elif attr.type == attr_type_pb2.FLOATS: + new_attr.floats.extend(user_defined_attr) + elif attr.type == attr_type_pb2.STRINGS: + new_attr.strings.extend(user_defined_attr) + else: + raise NotImplementedError("Not support attribute type " + + attr.type) + + return op_desc + + @staticmethod + def extract_input_or_output(in_out, kwargs, meta): + """ + Extract input variable names or output variable names from key-word + arguments, which base on VarProtos. + + :param in_out: "input" or "output" + :param kwargs: key-word arguments that user inputted. + :param meta: a list of VarProto + :return: The three object will be return. The variable names. The + input_format or output_format attribute(None if the input or output is + not multiple). The temporary variable index list. + """ + multiple = OpDescCreationMethod.any_is_true((m.multiple for m in meta)) + tmp_index = [] + retv = [] + if multiple: + var_format = op_desc_pb2.AttrDesc() + var_format.type = attr_type_pb2.INTS + var_format.name = "%s_format" % in_out + var_format.ints.append(0) + + for var in meta: + var_name = var.name + + if var.temporary: + var_name = [core.var_names.temp()] + tmp_index.append(len(retv)) + else: + var_name = kwargs.get(var_name, []) + if not isinstance(var_name, list): + var_name = [var_name] + retv.extend(var_name) + var_format.ints.append(len(var_name) + var_format.ints[-1]) + return retv, var_format, tmp_index + else: + for var in meta: + if var.temporary: + retv.append(kwargs.get(var.name, core.var_names.temp())) + tmp_index.append(len(retv)) + else: + retv.append(kwargs.get(var.name, core.var_names.empty())) + return retv, None, tmp_index + + @staticmethod + def any_is_true(generator): + """ + Reduce a bool array to one. If any of them is True, then return True. + """ + for flag in generator: + if flag: + return True + return False + + +def get_docstring_from_op_proto(op_proto): + """ + Generate docstring from a OpProto + :param op_proto: a OpProto instance. + :type op_proto: op_proto_pb2.OpProto + :return: docstring + """ + if not isinstance(op_proto, op_proto_pb2.OpProto): + raise TypeError("Input must be OpProto") + f = cStringIO.StringIO() + f.write(op_proto.comment) + f.write("\n") + + def __append_param__(name, comment, type): + # Maybe replace the following line with template engine is better. + f.write(":param ") + f.write(name) + f.write(": ") + f.write(comment) + f.write("\n") + f.write(":type ") + f.write(name) + f.write(": ") + f.write(type) + f.write("\n") + + for ipt in op_proto.inputs: + __append_param__(ipt.name, ipt.comment, "list | basestr" + if ipt.multiple else "basestr") + + temp_var_prefix = \ + "This is a temporary variable. It does not have to set by user. " + for opt in op_proto.outputs: + __append_param__(opt.name, opt.comment if not opt.temporary else + temp_var_prefix + opt.comment, "list | basestr" + if opt.multiple else "basestr") + + for attr in op_proto.attrs: + attr_type = None + if attr.type == attr_type_pb2.INT: + attr_type = "int" + elif attr.type == attr_type_pb2.FLOAT: + attr_type = "float" + elif attr.type == attr_type_pb2.STRING: + attr_type = "basestr" + elif attr.type == attr_type_pb2.INTS: + attr_type = "list of int" + elif attr.type == attr_type_pb2.FLOATS: + attr_type = "list of float" + elif attr.type == attr_type_pb2.STRINGS: + attr_type = "list of basestr" + + if attr_type is None: + raise RuntimeError("Not supported attribute type " + attr.type) + + __append_param__(attr.name, attr.comment, attr_type) + + return f.getvalue() + + +def create_op_creation_method(op_proto): + """ + Generate op creation method for an OpProto + """ + method = OpDescCreationMethod(op_proto) + + def __impl__(*args, **kwargs): + opdesc = method(*args, **kwargs) + return core.Operator.create(opdesc.SerializeToString()) + + __impl__.__doc__ = get_docstring_from_op_proto(op_proto) + return __impl__ + + +class OpCreationsHolder(object): + """ + A object will holds all op creation methods. + + Use `op_creations.xxx_op` to access them. + """ + pass + + +op_creations = OpCreationsHolder() + + +def __bootstrap__(): + """ + Bootstrap function for this module. It will dynamic create all op creation + methods in runtime. + """ + for op_proto in get_all_op_protos(): + func = create_op_creation_method(op_proto) + func.__name__ = str(op_proto.type) + setattr(op_creations, func.__name__, func) + + +__bootstrap__() diff --git a/python/paddle/v2/framework/tests/CMakeLists.txt b/python/paddle/v2/framework/tests/CMakeLists.txt index 86fc60f26aee0fbdcf4ac4938d20d26d35df57f6..4ce2bef6fcc4b8ddf5a6de3809a1891bce590aab 100644 --- a/python/paddle/v2/framework/tests/CMakeLists.txt +++ b/python/paddle/v2/framework/tests/CMakeLists.txt @@ -1,2 +1,3 @@ add_python_test(test_framework test_protobuf.py test_scope.py - test_default_scope_funcs.py test_op_creation_methods.py) + test_default_scope_funcs.py test_op_creation_methods.py + test_tensor.py) diff --git a/python/paddle/v2/framework/tests/test_op_creation_methods.py b/python/paddle/v2/framework/tests/test_op_creation_methods.py index b205e2cabb99ab08604ab3c3ce073bcb95ec4bb3..41db7c0d535aa920b34d6cc346090a8c15bfb110 100644 --- a/python/paddle/v2/framework/tests/test_op_creation_methods.py +++ b/python/paddle/v2/framework/tests/test_op_creation_methods.py @@ -1,9 +1,13 @@ import unittest import paddle.v2.framework.create_op_creation_methods as creation +import paddle.v2.framework.core as core +import paddle.v2.framework.proto.op_proto_pb2 as op_proto_pb2 +import paddle.v2.framework.proto.op_desc_pb2 as op_desc_pb2 +import paddle.v2.framework.proto.attr_type_pb2 as attr_type_pb2 -class TestOpCreationsMethods(unittest.TestCase): - def test_all_protos(self): +class TestGetAllProtos(unittest.TestCase): + def test_all(self): all_protos = creation.get_all_op_protos() self.assertNotEqual(0, len(all_protos)) @@ -11,5 +15,240 @@ class TestOpCreationsMethods(unittest.TestCase): self.assertTrue(each.IsInitialized()) +class TestOpDescCreationMethod(unittest.TestCase): + def test_plain_input_output(self): + op = op_proto_pb2.OpProto() + op.type = "test" + ipt = op.inputs.add() + ipt.name = "X" + ipt.comment = "not matter" + + ipt = op.inputs.add() + ipt.name = "Y" + ipt.comment = "not matter" + + opt = op.outputs.add() + opt.name = "Z" + opt.comment = "not matter" + + op.comment = "not matter" + + self.assertTrue(op.IsInitialized()) + + method = creation.OpDescCreationMethod(op) + output = method(X="a", Y="b", Z="c") + + expected = op_desc_pb2.OpDesc() + expected.type = "test" + expected.inputs.extend(["a", "b"]) + expected.outputs.append("c") + self.assertEqual(expected, output) + + def test_multiple_input_plain_output(self): + op = op_proto_pb2.OpProto() + op.type = "fc" + ipt = op.inputs.add() + ipt.name = "X" + ipt.comment = "" + ipt.multiple = True + + ipt = op.inputs.add() + ipt.name = "W" + ipt.comment = "" + ipt.multiple = True + + ipt = op.inputs.add() + ipt.name = "b" + ipt.comment = "" + + out = op.outputs.add() + out.name = "Y" + out.comment = "" + + op.comment = "" + self.assertTrue(op.IsInitialized()) + method = creation.OpDescCreationMethod(op) + + generated1 = method(X="x", W="w", b="b", Y="y") + expected1 = op_desc_pb2.OpDesc() + expected1.inputs.extend(['x', 'w', 'b']) + expected1.outputs.extend(['y']) + expected1.type = 'fc' + attr = expected1.attrs.add() + attr.name = 'input_format' + attr.type = attr_type_pb2.INTS + attr.ints.extend([0, 1, 2, 3]) + self.assertEqual(expected1, generated1) + + generated2 = method( + X=['x1', 'x2', 'x3'], b='b', W=['w1', 'w2', 'w3'], Y='y') + expected2 = op_desc_pb2.OpDesc() + expected2.inputs.extend(['x1', 'x2', 'x3', 'w1', 'w2', 'w3', 'b']) + expected2.outputs.extend(['y']) + expected2.type = 'fc' + attr = expected2.attrs.add() + attr.name = 'input_format' + attr.type = attr_type_pb2.INTS + attr.ints.extend([0, 3, 6, 7]) + self.assertEqual(expected2, generated2) + + def test_attrs(self): + op = op_proto_pb2.OpProto() + op.type = "test" + ipt = op.inputs.add() + ipt.name = 'X' + ipt.comment = "" + + def __add_attr__(name, type): + attr = op.attrs.add() + attr.name = name + attr.comment = "" + attr.type = type + + __add_attr__("int_attr", attr_type_pb2.INT) + __add_attr__("float_attr", attr_type_pb2.FLOAT) + __add_attr__("string_attr", attr_type_pb2.STRING) + __add_attr__("ints_attr", attr_type_pb2.INTS) + __add_attr__("floats_attr", attr_type_pb2.FLOATS) + __add_attr__("strings_attr", attr_type_pb2.STRINGS) + + op.comment = "" + self.assertTrue(op.IsInitialized()) + + method = creation.OpDescCreationMethod(op) + + generated = method( + X="a", + int_attr=10, + float_attr=3.2, + string_attr="test_str", + ints_attr=[0, 1, 2, 3, 4], + floats_attr=[0.2, 3.2, 4.5], + strings_attr=["a", "b", "c"]) + + expected = op_desc_pb2.OpDesc() + expected.type = "test" + expected.inputs.extend(['a']) + attr = expected.attrs.add() + attr.name = "int_attr" + attr.type = attr_type_pb2.INT + attr.i = 10 + + attr = expected.attrs.add() + attr.name = "float_attr" + attr.type = attr_type_pb2.FLOAT + attr.f = 3.2 + + attr = expected.attrs.add() + attr.name = "string_attr" + attr.type = attr_type_pb2.STRING + attr.s = "test_str" + + attr = expected.attrs.add() + attr.name = "ints_attr" + attr.type = attr_type_pb2.INTS + attr.ints.extend([0, 1, 2, 3, 4]) + + attr = expected.attrs.add() + attr.name = 'floats_attr' + attr.type = attr_type_pb2.FLOATS + attr.floats.extend([0.2, 3.2, 4.5]) + + attr = expected.attrs.add() + attr.name = 'strings_attr' + attr.type = attr_type_pb2.STRINGS + attr.strings.extend(['a', 'b', 'c']) + + self.assertEqual(expected, generated) + + def test_input_temporary_output(self): + op = op_proto_pb2.OpProto() + op.type = "test" + out = op.outputs.add() + out.name = "OUT" + out.comment = "" + + out = op.outputs.add() + out.name = "TMP" + out.comment = "" + out.temporary = True + + out = op.outputs.add() + out.name = "OUT2" + out.comment = "" + op.comment = "" + + method = creation.OpDescCreationMethod(op) + generated = method(OUT="a", OUT2="b") + desc = op_desc_pb2.OpDesc() + desc.outputs.extend(["a", core.var_names.temp(), "b"]) + desc.type = "test" + attr = desc.attrs.add() + attr.name = "temporary_index" + attr.type = attr_type_pb2.INTS + attr.ints.append(2) + self.assertEqual(generated, desc) + + +class TestOpCreationDocStr(unittest.TestCase): + def test_all(self): + op = op_proto_pb2.OpProto() + op.type = "test" + op.comment = """Test Op. + +This op is used for unit test, not a real op. +""" + a = op.inputs.add() + a.name = "a" + a.comment = "Input a for test op" + a.multiple = True + + b = op.inputs.add() + b.name = "b" + b.comment = "Input b for test op" + self.assertTrue(op.IsInitialized()) + + o1 = op.outputs.add() + o1.name = "output" + o1.comment = "The output of test op" + + o2 = op.outputs.add() + o2.name = "temp output" + o2.comment = "The temporary output of test op" + o2.temporary = True + + test_str = op.attrs.add() + test_str.name = "str_attr" + test_str.type = attr_type_pb2.STRING + test_str.comment = "A string attribute for test op" + + actual = creation.get_docstring_from_op_proto(op) + expected_docstring = '''Test Op. + +This op is used for unit test, not a real op. + +:param a: Input a for test op +:type a: list | basestr +:param b: Input b for test op +:type b: basestr +:param output: The output of test op +:type output: basestr +:param temp output: This is a temporary variable. It does not have to set by user. The temporary output of test op +:type temp output: basestr +:param str_attr: A string attribute for test op +:type str_attr: basestr +''' + self.assertEqual(expected_docstring, actual) + + +class TestOpCreations(unittest.TestCase): + def test_all(self): + add_op = creation.op_creations.add_two(X="a", Y="b", Out="z") + self.assertIsNotNone(add_op) + # Invoke C++ DebugString() + self.assertEqual('Op(add_two), inputs:(a, b), outputs:(z).', + str(add_op)) + + if __name__ == "__main__": unittest.main() diff --git a/python/paddle/v2/framework/tests/test_tensor.py b/python/paddle/v2/framework/tests/test_tensor.py new file mode 100644 index 0000000000000000000000000000000000000000..b72aff3b9cd16595c7e81856642196b2bb61a790 --- /dev/null +++ b/python/paddle/v2/framework/tests/test_tensor.py @@ -0,0 +1,45 @@ +import paddle.v2.framework.core as core +import unittest +import numpy + + +class TestScope(unittest.TestCase): + def test_int_tensor(self): + scope = core.Scope(None) + var = scope.create_var("test_tensor") + tensor = var.get_tensor() + + tensor.set_dims([1000, 784]) + tensor.alloc_int() + + tensor_array = numpy.array(tensor) + self.assertEqual((1000, 784), tensor_array.shape) + tensor_array[3, 9] = 1 + tensor_array[19, 11] = 2 + tensor.set(tensor_array) + + tensor_array_2 = numpy.array(tensor) + self.assertEqual(1.0, tensor_array_2[3, 9]) + self.assertEqual(2.0, tensor_array_2[19, 11]) + + def test_float_tensor(self): + scope = core.Scope(None) + var = scope.create_var("test_tensor") + tensor = var.get_tensor() + + tensor.set_dims([1000, 784]) + tensor.alloc_float() + + tensor_array = numpy.array(tensor) + self.assertEqual((1000, 784), tensor_array.shape) + tensor_array[3, 9] = 1.0 + tensor_array[19, 11] = 2.0 + tensor.set(tensor_array) + + tensor_array_2 = numpy.array(tensor) + self.assertAlmostEqual(1.0, tensor_array_2[3, 9]) + self.assertAlmostEqual(2.0, tensor_array_2[19, 11]) + + +if __name__ == '__main__': + unittest.main() diff --git a/python/paddle/v2/optimizer.py b/python/paddle/v2/optimizer.py index 7e8a3bece9acb93ffba634e7b3656f2b580a48f2..ba581980334fec6226a537af2cf53b3465d32c1e 100644 --- a/python/paddle/v2/optimizer.py +++ b/python/paddle/v2/optimizer.py @@ -1,4 +1,3 @@ -import py_paddle.swig_paddle as swig_api import paddle.trainer_config_helpers.config_parser_utils as config_parser_utils import paddle.trainer_config_helpers.optimizers as v1_optimizers """ @@ -17,6 +16,7 @@ __all__ = [ class Optimizer(object): def __init__(self, **kwargs): + import py_paddle.swig_paddle as swig_api if 'batch_size' in kwargs: del kwargs['batch_size'] # not important for python library. @@ -35,18 +35,22 @@ class Optimizer(object): For each optimizer(SGD, Adam), GradientMachine should enable different buffers. """ + import py_paddle.swig_paddle as swig_api tmp = swig_api.ParameterOptimizer.create(self.__opt_conf__) assert isinstance(tmp, swig_api.ParameterOptimizer) return tmp.getParameterTypes() def __create_local_updater__(self): + import py_paddle.swig_paddle as swig_api return swig_api.ParameterUpdater.createLocalUpdater(self.__opt_conf__) def __create_remote_updater__(self, pass_num, use_sparse_updater): + import py_paddle.swig_paddle as swig_api return swig_api.ParameterUpdater.createRemoteUpdater( self.__opt_conf__, pass_num, use_sparse_updater) def __create_new_remote_updater__(self, pserver_spec, use_etcd): + import py_paddle.swig_paddle as swig_api return swig_api.ParameterUpdater.createNewRemoteUpdater( self.__opt_conf__, pserver_spec, use_etcd)