Merge remote-tracking branch 'origin/develop' into random_op

doc/design/cluster_train/save_model.md

@@ -75,10 +75,11 @@ snapshot to a model will be a TODO for future.
 ### Trainer Election
 
 One trainer will be elected as the one to save the model. When using
-etcd, trainer ID is a randomly generated UUID, we will utilize etcd to
-elect one trainer. When not using etcd, unique trainer IDs will be
-given by the administrator, the trainer whose ID is "0" is elected to
-save the model.
+etcd, trainer ID is a randomly generated UUID, the trainer will
+contact the master server requesting to save the model, and find out
+if itself is elected. When the master server is not used, unique
+trainer IDs will be given by the administrator, the trainer whose ID
+is "0" is elected to save the model.
 
 ### Model Save Path
 

doc/design/simple_op_design.md

@@ -49,6 +49,7 @@ message AttrProto {
 message VarProto {
 	required string name = 1;
 	required string comment = 2;
+	required bool is_tensor = 3;
 };
 
 message OpProto {

doc/faq/index_cn.rst

@@ -311,3 +311,13 @@ Paddle二进制在运行时捕获了浮点数异常，只要出现浮点数异
 * 训练数据有问题，导致参数收敛到了一些奇异的情况。或者输入数据尺度过大，有些特征的取值达到数百万，这时进行矩阵乘法运算就可能导致浮点数溢出。
 
 主要的解决办法是减小学习律或者对数据进行归一化处理。
+
+15. 编译安装后执行 import paddle.v2 as paddle 报ImportError: No module named v2
+------------------------------------------------------------------------
+先查看一下是否曾经安装过paddle v1版本，有的话需要先卸载：
+
+pip uninstall py_paddle paddle
+
+然后安装paddle的python环境, 在build目录下执行
+
+pip install python/dist/paddle*.whl && pip install ../paddle/dist/py_paddle*.whl

go/cmd/pserver/pserver.go

@@ -59,9 +59,13 @@ func main() {
 
 		cp, err = pserver.NewCheckpointFromFile(*checkpointPath, idx, e)
 		if err != nil {
+			if err == pserver.ErrCheckpointNotFound {
+				log.Infof("Could not find the pserver checkpoint.")
+			} else {
 				log.Errorf("Fetch checkpoint failed, %s", err)
 			}
 		}
+	}
 
 	s, err := pserver.NewService(idx, *checkpointInterval, *checkpointPath, e, cp)
 	candy.Must(err)

go/master/c/client.go

@@ -22,6 +22,9 @@ package main
 #define PADDLE_MASTER_OK    0
 #define PADDLE_MASTER_ERROR -1
 
+#define PADDLE_SAVE_MODEL_OK   1
+#define PADDLE_SAVE_MODEL_SKIP 0
+
 typedef int paddle_master_client;
 */
 import "C"
@@ -33,7 +36,6 @@ import (
 	"unsafe"
 
 	"github.com/PaddlePaddle/Paddle/go/master"
-	"github.com/coreos/etcd/clientv3"
 	log "github.com/sirupsen/logrus"
 )
 
@@ -65,32 +67,32 @@ func remove(client C.paddle_master_client) *master.Client {
 }
 
 //export paddle_new_etcd_master_client
+//
+// bufSize is the record buffer size.
 func paddle_new_etcd_master_client(etcdEndpoints *C.char, timeout int, bufSize int) C.paddle_master_client {
 	p := C.GoString(etcdEndpoints)
-	cli, err := clientv3.New(clientv3.Config{
-		Endpoints:   strings.Split(p, ","),
-		DialTimeout: time.Second * time.Duration(timeout),
-	})
+	endpoints := strings.Split(p, ",")
+	c, err := master.NewClient(
+		master.WithEtcd(endpoints, time.Duration(timeout)*time.Second),
+		master.WithBuffer(bufSize),
+	)
 	if err != nil {
 		panic(err)
 	}
-	ch := make(chan string, 1)
-	a, err := master.GetKey(cli, master.DefaultAddrPath, timeout)
-	if err != nil {
-		panic(err)
-	}
-	ch <- a
-	go master.WatchKey(cli, master.DefaultAddrPath, ch)
-	c := master.NewClient(ch, bufSize)
+
 	return add(c)
 }
 
 //export paddle_new_master_client
+//
+// bufSize is the record buffer size.
 func paddle_new_master_client(addr *C.char, bufSize int) C.paddle_master_client {
 	a := C.GoString(addr)
-	ch := make(chan string, 1)
-	ch <- a
-	c := master.NewClient(ch, bufSize)
+	c, err := master.NewClient(master.WithAddr(a), master.WithBuffer(bufSize))
+	if err != nil {
+		panic(err)
+	}
+
 	return add(c)
 }
 
@@ -117,9 +119,10 @@ func paddle_set_dataset(client C.paddle_master_client, path **C.char, size C.int
 	return C.PADDLE_MASTER_OK
 }
 
-// return value:
-//     0:ok
-//    -1:error
+// paddle_next_record gets the nexts training record.
+//
+// returns number of bytes of the records if success, -1 if failed.
+//
 //export paddle_next_record
 func paddle_next_record(client C.paddle_master_client, record **C.uchar) C.int {
 	c := get(client)
@@ -143,6 +146,29 @@ func paddle_next_record(client C.paddle_master_client, record **C.uchar) C.int {
 	return C.int(size)
 }
 
+// paddle_request_save_model requests the master server to approve the
+// caller to save the model.
+//
+// returns 1 if the save the model request is approved, 0 if the
+// request is rejected because other trainer is saving the model, -1
+// if error happened.
+//
+//export paddle_request_save_model
+func paddle_request_save_model(client C.paddle_master_client, trainerID string, blockMS int) C.int {
+	c := get(client)
+	need, err := c.RequestSaveModel(trainerID, time.Duration(blockMS)*time.Millisecond)
+	if err != nil {
+		log.Errorln(err)
+		return C.PADDLE_MASTER_ERROR
+	}
+
+	if need {
+		return C.PADDLE_SAVE_MODEL_OK
+	}
+
+	return C.PADDLE_SAVE_MODEL_SKIP
+}
+
 //export mem_free
 func mem_free(p unsafe.Pointer) {
 	// "free" may be a better name for this function, but doing so

go/master/client.go

@@ -16,10 +16,12 @@ package master
 
 import (
 	"os"
+	"sync"
 	"time"
 
 	"github.com/PaddlePaddle/Paddle/go/connection"
 	"github.com/PaddlePaddle/recordio"
+	"github.com/coreos/etcd/clientv3"
 	log "github.com/sirupsen/logrus"
 )
 
@@ -27,6 +29,7 @@ import (
 type Client struct {
 	conn       *connection.Conn
 	ch         chan record
+	initChOnce sync.Once
 }
 
 type record struct {
@@ -34,24 +37,83 @@ type record struct {
 	err error
 }
 
-// NewClient creates a new Client.
+// WithBuffer sets the client to buffer the training record.
 //
 // bufSize is the record buffer size. NextRecord will read from this
 // buffer.
-func NewClient(addrCh <-chan string, bufSize int) *Client {
-	c := &Client{}
-	c.conn = connection.New()
+func WithBuffer(bufSize int) func(*Client) error {
+	return func(c *Client) error {
+		if bufSize <= 0 {
+			return nil
+		}
+
+		c.initChOnce.Do(func() {
 			c.ch = make(chan record, bufSize)
-	go c.monitorMaster(addrCh)
 			go c.getRecords()
-	return c
+		})
+		return nil
+	}
+}
+
+// WithAddr sets the client to use fixed master address.
+func WithAddr(addr string) func(c *Client) error {
+	return func(c *Client) error {
+		ch := make(chan string, 1)
+		ch <- addr
+		go c.monitorMaster(ch)
+		return nil
+	}
+}
+
+// WithEtcd sets the client to use etcd for master discovery.
+func WithEtcd(endpoints []string, timeout time.Duration) func(*Client) error {
+	return func(c *Client) error {
+		cli, err := clientv3.New(clientv3.Config{
+			Endpoints:   endpoints,
+			DialTimeout: timeout,
+		})
+		if err != nil {
+			return err
+		}
+
+		ch := make(chan string, 1)
+		a, err := GetKey(cli, DefaultAddrPath, timeout)
+		if err != nil {
+			return err
+		}
+
+		if a != "" {
+			// Master is registered, send to the master address
+			// channel.
+			ch <- a
+		}
+
+		go watchKey(cli, DefaultAddrPath, ch)
+		go c.monitorMaster(ch)
+		return nil
+	}
+}
+
+// NewClient creates a new Client.
+func NewClient(opts ...func(*Client) error) (*Client, error) {
+	c := &Client{}
+	c.conn = connection.New()
+
+	for _, opt := range opts {
+		err := opt(c)
+		if err != nil {
+			return nil, err
+		}
+
+	}
+
+	return c, nil
 }
 
 func (c *Client) getRecords() {
 	for {
 		t, err := c.getTask()
 		if err != nil {
-			// getTask call.
 			log.Errorf("Get task failed, sleep 3 seconds and continue, %s", err)
 			time.Sleep(3 * time.Second)
 			continue
@@ -146,6 +208,20 @@ func (c *Client) taskFailed(meta TaskMeta) error {
 // NextRecord will block until the next record is available. It is
 // thread-safe.
 func (c *Client) NextRecord() ([]byte, error) {
+	c.initChOnce.Do(func() {
+		// initialize with in case WithBuffer is not used.
+		c.ch = make(chan record, 0)
+		go c.getRecords()
+	})
+
 	r := <-c.ch
 	return r.r, r.err
 }
+
+// RequestSaveModel requests the master server to approve the caller
+// to save the model.
+func (c *Client) RequestSaveModel(trainerID string, blockDur time.Duration) (bool, error) {
+	var need bool
+	err := c.conn.Call("Service.RequestSaveModel", SaveModelRequest{TrainerID: trainerID, BlockDur: blockDur}, &need)
+	return need, err
+}

go/master/client_test.go

@@ -87,9 +87,11 @@ func TestNextRecord(t *testing.T) {
 		panic(err)
 	}
 
-	curAddr := make(chan string, 1)
-	curAddr <- fmt.Sprintf(":%d", p)
-	c := master.NewClient(curAddr, 10)
+	c, err := master.NewClient(master.WithAddr(fmt.Sprintf(":%d", p)), master.WithBuffer(10))
+	if err != nil {
+		panic(err)
+	}
+
 	err = c.SetDataset([]string{path})
 	if err != nil {
 		panic(err)

go/master/etcd_client.go

@@ -158,8 +158,8 @@ func (e *EtcdClient) Load() ([]byte, error) {
 }
 
 // GetKey gets the value by the specify key.
-func GetKey(c *clientv3.Client, key string, timeout int) (string, error) {
-	ctx, cancel := context.WithTimeout(context.Background(), time.Second*time.Duration(timeout))
+func GetKey(c *clientv3.Client, key string, timeout time.Duration) (string, error) {
+	ctx, cancel := context.WithTimeout(context.Background(), timeout)
 	resp, err := c.Get(ctx, key)
 	cancel()
 	if err != nil {
@@ -173,8 +173,8 @@ func GetKey(c *clientv3.Client, key string, timeout int) (string, error) {
 	return string(v), nil
 }
 
-// WatchKey watches the specify key and send to valChan if there is some event.
-func WatchKey(c *clientv3.Client, key string, valChan chan<- string) {
+// watchKey watches the specify key and send to valChan if there is some event.
+func watchKey(c *clientv3.Client, key string, valChan chan<- string) {
 	rch := c.Watch(context.Background(), key)
 	for wresp := range rch {
 		for _, ev := range wresp.Events {

go/master/service.go

@@ -81,6 +81,7 @@ type Service struct {
 	mu            sync.Mutex
 	initDone      bool
 	taskQueues    taskQueues
+	savingTrainer string
 }
 
 func partition(chunks []Chunk, chunksPerTask int) []taskEntry {
@@ -246,7 +247,7 @@ func readChunks(globPaths []string) ([]Chunk, error) {
 //
 // SetDataset can be call multiple times. But only the first call will
 // be honored.
-func (s *Service) SetDataset(globPaths []string, dummy *int) error {
+func (s *Service) SetDataset(globPaths []string, _ *int) error {
 	if len(globPaths) == 0 {
 		return errors.New("no dataset specified")
 	}
@@ -330,7 +331,7 @@ func (s *Service) logFields() log.Fields {
 }
 
 // GetTask gets a new task from the service.
-func (s *Service) GetTask(dummy int, task *Task) error {
+func (s *Service) GetTask(_ int, task *Task) error {
 	select {
 	case <-s.ready:
 	}
@@ -380,7 +381,7 @@ func (s *Service) GetTask(dummy int, task *Task) error {
 }
 
 // TaskFinished tell the service that a task is finished.
-func (s *Service) TaskFinished(taskID int, dummy *int) error {
+func (s *Service) TaskFinished(taskID int, _ *int) error {
 	select {
 	case <-s.ready:
 	}
@@ -415,7 +416,7 @@ func (s *Service) TaskFinished(taskID int, dummy *int) error {
 }
 
 // TaskFailed tells the service that a task is failed.
-func (s *Service) TaskFailed(meta TaskMeta, dummy *int) error {
+func (s *Service) TaskFailed(meta TaskMeta, _ *int) error {
 	select {
 	case <-s.ready:
 	}
@@ -432,3 +433,42 @@ func (s *Service) TaskFailed(meta TaskMeta, dummy *int) error {
 	s.processFailedTask(t, meta.Epoch)
 	return nil
 }
+
+// SaveModelRequest is the request for saving model
+type SaveModelRequest struct {
+	TrainerID string
+	BlockDur  time.Duration
+}
+
+// RequestSaveModel requests the master server to approve the caller
+// to save the model.
+func (s *Service) RequestSaveModel(req SaveModelRequest, need *bool) error {
+	s.mu.Lock()
+	defer s.mu.Unlock()
+
+	if req.TrainerID == "" {
+		return errors.New("trainer id is empty")
+	}
+
+	if s.savingTrainer == "" {
+		*need = true
+	} else {
+		if req.TrainerID == s.savingTrainer {
+			// save trainer asked to save model again
+			*need = true
+		} else {
+			*need = false
+		}
+	}
+
+	if *need {
+		s.savingTrainer = req.TrainerID
+		time.AfterFunc(req.BlockDur, func() {
+			s.mu.Lock()
+			s.savingTrainer = ""
+			s.mu.Unlock()
+		})
+	}
+
+	return nil
+}

go/pserver/client/c/cclient.go

@@ -127,13 +127,19 @@ func paddle_pserver_client_release(client C.paddle_pserver_client) {
 	remove(client)
 }
 
+// paddle_begin_init_params tells trainer if it needs to init the
+// parameters.
+//
+// returns 1 if the trainer needs to init the parameters. 0 if the
+// trainer does not need to init the parameters.
+//
 //export paddle_begin_init_params
 func paddle_begin_init_params(client C.paddle_pserver_client) C.int {
 	c := get(client)
 	if selected := c.BeginInitParams(); selected {
 		return 1
 	}
-	return C.PSERVER_OK
+	return 0
 }
 
 //export paddle_init_param
@@ -256,17 +262,4 @@ func paddle_get_params(client C.paddle_pserver_client, dst **C.paddle_parameter,
 	return C.PSERVER_OK
 }
 
-//export paddle_save_model
-func paddle_save_model(client C.paddle_pserver_client, path *C.char) C.int {
-	p := C.GoString(path)
-	c := get(client)
-	err := c.Save(p)
-	if err != nil {
-		log.Errorln(err)
-		return C.PSERVER_ERROR
-	}
-
-	return C.PSERVER_OK
-}
-
 func main() {} // Required but ignored

go/pserver/client/c/test/test_cclient.c

@@ -111,9 +111,5 @@ retry:
     getParams(c);
   }
 
-  if (paddle_save_model(c, "/tmp/")) {
-    fail();
-  }
-
   return 0;
 }

go/pserver/client/client.go

@@ -219,32 +219,6 @@ func (c *Client) GetParams(names []string) ([]pserver.Parameter, error) {
 	return ps, nil
 }
 
-// Save indicates parameters to save the parameter to the given path.
-func (c *Client) Save(path string) error {
-	errCh := make(chan error, len(c.pservers))
-
-	for _, p := range c.pservers {
-		err := p.Call("Service.Save", path, nil)
-		errCh <- err
-	}
-
-	recv := 0
-	for err := range errCh {
-		if err != nil {
-			return err
-		}
-
-		recv++
-		if recv == len(c.pservers) {
-			break
-		}
-	}
-
-	// TODO(helin): there will be many files under path, need to
-	// merge them into a single file.
-	return nil
-}
-
 func strHash(s string) uint32 {
 	h := fnv.New32a()
 	_, _ = h.Write([]byte(s))

go/pserver/service.go

@@ -36,6 +36,10 @@ import (
 // ElementType is the type of elements of a Parameter.
 type ElementType int
 
+// ErrCheckpointNotFound indicates that the pserver checkpoint could
+// not be found.
+var ErrCheckpointNotFound = errors.New("checkpoint not found")
+
 // RPC error message.
 const (
 	AlreadyInitialized  = "pserver already initialized"
@@ -103,6 +107,10 @@ func NewCheckpointFromFile(cpPath string, idx int, e *EtcdClient) (Checkpoint, e
 		return nil, err
 	}
 
+	if len(v) == 0 {
+		return nil, ErrCheckpointNotFound
+	}
+
 	var cpMeta checkpointMeta
 	if err = json.Unmarshal(v, &cpMeta); err != nil {
 		return nil, err
@@ -156,7 +164,7 @@ func NewService(idx int, interval time.Duration, path string, client *EtcdClient
 }
 
 // InitParam initializes a parameter.
-func (s *Service) InitParam(paramWithConfigs ParameterWithConfig, dummy *int) error {
+func (s *Service) InitParam(paramWithConfigs ParameterWithConfig, _ *int) error {
 	select {
 	case <-s.initialized:
 		return errors.New(AlreadyInitialized)
@@ -177,7 +185,7 @@ func (s *Service) InitParam(paramWithConfigs ParameterWithConfig, dummy *int) er
 
 // FinishInitParams tells the parameter server that the parameter
 // initialization has finished.
-func (s *Service) FinishInitParams(dummy0 int, dummy1 *int) error {
+func (s *Service) FinishInitParams(_ int, _ *int) error {
 	select {
 	case <-s.initialized:
 		return errors.New(AlreadyInitialized)
@@ -190,7 +198,7 @@ func (s *Service) FinishInitParams(dummy0 int, dummy1 *int) error {
 
 // SendGrad sends gradient to parameter servers for parameter
 // optimization.
-func (s *Service) SendGrad(g Gradient, dummy *int) error {
+func (s *Service) SendGrad(g Gradient, _ *int) error {
 	select {
 	case <-s.initialized:
 	default:

paddle/framework/CMakeLists.txt

@@ -19,8 +19,10 @@ 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 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)
-cc_test(op_registry_test SRCS op_registry_test.cc DEPS op_registry operator)
+cc_library(grad_op_builder SRCS grad_op_builder.cc DEPS op_proto operator)
+cc_library(op_registry SRCS op_registry.cc DEPS op_desc grad_op_builder)
+cc_test(op_registry_test SRCS op_registry_test.cc DEPS op_registry)
+cc_test(grad_op_builder_test SRCS grad_op_builder_test.cc DEPS grad_op_builder op_registry add_op)
 
 py_proto_compile(framework_py_proto SRCS attr_type.proto op_proto.proto op_desc.proto)
 # Generate an empty __init__.py to make framework_py_proto as a valid python module.
@@ -28,5 +30,6 @@ add_custom_target(framework_py_proto_init ALL COMMAND ${CMAKE_COMMAND} -E touch
 add_dependencies(framework_py_proto framework_py_proto_init)
 
 proto_library(net_proto SRCS net_proto.proto DEPS op_proto)
+# cc_library(net SRCS net.cc DEPS operator net_proto op_registry fc_op)
 cc_library(net SRCS net.cc DEPS operator net_proto op_registry)
-cc_test(net_op_test SRCS net_op_test.cc DEPS net)
+cc_test(net_op_test SRCS net_op_test.cc DEPS net add_op mul_op sigmoid_op softmax_op fc_op)

paddle/framework/grad_op_builder.cc

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/framework/grad_op_builder.h"
+#include "paddle/framework/op_registry.h"
+
+namespace paddle {
+namespace framework {
+
+OperatorBase* GradOpBuilder::Build() {
+  BuildOpInOutArgList();
+  std::string grad_op_type = OpRegistry::grad_ops().at(op_->type_);
+  OperatorBase* grad_op = OpRegistry::op_creators().at(grad_op_type)();
+  grad_op->type_ = grad_op_type;
+  CompleteGradOp(grad_op);
+  return grad_op;
+}
+
+OpInOutArg* GradOpBuilder::BuildArg(const VarProto& var,
+                                    const VarIndexMap& var_map,
+                                    const std::vector<int>& format,
+                                    InOutType type) {
+  int idx = var_map.at(var.name());
+  int begin_idx = format.empty() ? idx : format.at(idx);
+  int end_idx = format.empty() ? idx + 1 : format.at(idx + 1);
+  return new OpInOutArg(var.name(), type, !var.ignore_gradient(), begin_idx,
+                        end_idx);
+}
+
+void GradOpBuilder::BuildOpInOutArgList() {
+  const OpProto& op_proto = OpRegistry::protos().at(op_->type_);
+  const auto& var_map = *(OpRegistry::VarIndexMaps().at(op_->type_));
+  const std::vector<int>& in_format =
+      op_->attrs_.count("input_format")
+          ? op_->GetAttr<std::vector<int>>("input_format")
+          : std::vector<int>();
+  const std::vector<int>& out_format =
+      op_->attrs_.count("output_format")
+          ? op_->GetAttr<std::vector<int>>("output_format")
+          : std::vector<int>();
+  for (const auto& var : op_proto.inputs()) {
+    arg_list_.emplace_back(
+        std::shared_ptr<OpInOutArg>(BuildArg(var, var_map, in_format, IN)));
+  }
+  for (const auto& var : op_proto.outputs()) {
+    arg_list_.emplace_back(
+        std::shared_ptr<OpInOutArg>(BuildArg(var, var_map, out_format, OUT)));
+  }
+}
+
+void GradOpBuilder::AddArgIntoGradOp(const OpInOutArg* arg,
+                                     std::vector<std::string>& in_out,
+                                     std::vector<int>& format,
+                                     VarIndexMap* varmap, int& idx,
+                                     bool is_grad) const {
+  std::string var_name = arg->proto_name_;
+  if (is_grad) {
+    var_name += OperatorBase::GRAD_VAR_SUFFIX();
+  }
+  (*varmap)[var_name] = idx++;
+  size_t pre_sz = in_out.size();
+  auto base_it =
+      arg->type_ == IN ? op_->inputs_.begin() : op_->outputs_.begin();
+  std::copy(base_it + arg->begin_idx_, base_it + arg->end_idx_,
+            std::back_inserter(in_out));
+  if (is_grad) {
+    for (size_t i = pre_sz; i < in_out.size(); ++i) {
+      in_out[i] += OperatorBase::GRAD_VAR_SUFFIX();
+    }
+  }
+  format.push_back(in_out.size());
+}
+
+void GradOpBuilder::CompleteGradOp(OperatorBase* grad_op) const {
+  grad_op->attrs_ = op_->attrs_;
+  grad_op->attrs_.erase("input_format");
+  grad_op->attrs_.erase("output_format");
+  VarIndexMap* grad_varmap = new VarIndexMap();
+  int in_idx = 0;
+  int out_idx = 0;
+  std::vector<int> in_format({0});
+  std::vector<int> out_format({0});
+  for (const auto& arg : arg_list_) {
+    // op_'s inputs_ and outputs_
+    if (arg->needed_in_grad_) {
+      AddArgIntoGradOp(arg.get(), grad_op->inputs_, in_format, grad_varmap,
+                       in_idx, false);
+    }
+    if (arg->type_ == IN) {
+      // gradients of op_'s inputs_
+      AddArgIntoGradOp(arg.get(), grad_op->outputs_, out_format, grad_varmap,
+                       out_idx, true);
+    } else {
+      // gradients of op_'s outputs_
+      AddArgIntoGradOp(arg.get(), grad_op->inputs_, in_format, grad_varmap,
+                       in_idx, true);
+    }
+  }
+  grad_op->attrs_["input_format"] = in_format;
+  grad_op->attrs_["output_format"] = out_format;
+  grad_op->in_out_idxs_.reset(grad_varmap);
+}
+
+}  // namespace framework
+}  // namespace paddle

paddle/framework/grad_op_builder.h

+#pragma once
+
+#include "paddle/framework/op_proto.pb.h"
+#include "paddle/framework/operator.h"
+
+namespace paddle {
+namespace framework {
+class OpRegistry;
+
+enum InOutType { IN, OUT };
+
+struct OpInOutArg {
+  OpInOutArg(const std::string& proto_name, const InOutType& type,
+             bool needed_in_grad, size_t begin_idx, size_t end_idx)
+      : proto_name_(proto_name),
+        type_(type),
+        needed_in_grad_(needed_in_grad),
+        begin_idx_(begin_idx),
+        end_idx_(end_idx) {}
+
+  std::string proto_name_;
+  InOutType type_;
+  bool needed_in_grad_;
+  size_t begin_idx_;
+  size_t end_idx_;
+};
+
+class GradOpBuilder {
+  using VarIndexMap = std::unordered_map<std::string, int>;
+
+ public:
+  GradOpBuilder(const OperatorBase* op) : op_(op) {}
+  OperatorBase* Build();
+
+ private:
+  OpInOutArg* BuildArg(const VarProto& var, const VarIndexMap& var_map,
+                       const std::vector<int>& format, InOutType type);
+  void BuildOpInOutArgList();
+  void AddArgIntoGradOp(const OpInOutArg* arg, std::vector<std::string>& in_out,
+                        std::vector<int>& format, VarIndexMap* varmap, int& idx,
+                        bool is_grad) const;
+  void CompleteGradOp(OperatorBase* grad_op) const;
+  const OperatorBase* op_;
+  std::vector<std::shared_ptr<OpInOutArg>> arg_list_;
+};
+
+}  // namespace framework
+}  // namespace paddle

paddle/framework/grad_op_builder_test.cc

+#include "paddle/framework/grad_op_builder.h"
+#include <gtest/gtest.h>
+#include "paddle/framework/op_registry.h"
+#include "paddle/framework/operator.h"
+
+USE_OP(add_two);
+
+namespace paddle {
+namespace framework {
+
+TEST(GradOpBuilder, AddTwo) {
+  std::shared_ptr<OperatorBase> add_op(
+      OpRegistry::CreateOp("add_two", {"x", "y"}, {"out"}, {}));
+  std::shared_ptr<OperatorBase> grad_add_op = OpRegistry::CreateGradOp(add_op);
+  EXPECT_EQ(static_cast<int>(grad_add_op->inputs_.size()), 4);
+  EXPECT_EQ(static_cast<int>(grad_add_op->outputs_.size()), 2);
+  EXPECT_EQ(grad_add_op->Input("X"), "x");
+  EXPECT_EQ(grad_add_op->Input("Y"), "y");
+  EXPECT_EQ(grad_add_op->Input("Out"), "out");
+  EXPECT_EQ(grad_add_op->Input("Out@GRAD"), "out@GRAD");
+  EXPECT_EQ(grad_add_op->Output("X@GRAD"), "x@GRAD");
+  EXPECT_EQ(grad_add_op->Output("Y@GRAD"), "y@GRAD");
+}
+
+}  // namespace framework
+}  // namespace paddle
\ No newline at end of file

paddle/framework/net.cc

@@ -15,14 +15,24 @@
 */
 
 #include "paddle/framework/net.h"
+#include "paddle/framework/op_registry.h"
 
 namespace paddle {
 namespace framework {
 
+std::shared_ptr<PlainNet> AddBackwardOp(std::shared_ptr<PlainNet> ForwardOps) {
+  auto grad_ops = std::make_shared<PlainNet>();
+  for (auto& op : ForwardOps->ops_) {
+    auto op_grad = OpRegistry::CreateGradOp(op);
+    grad_ops->AddOp(op_grad);
+  }
+  grad_ops->CompleteAddOp();
+  return grad_ops;
+}
+
 void PlainNet::CompleteAddOp(bool calc) {
   add_op_done_ = true;
   if (!calc) return;
-
   std::unordered_set<std::string> input_set;
   std::unordered_set<std::string> output_set;
   std::unordered_set<std::string> temp_output;

paddle/framework/net.h

@@ -39,7 +39,7 @@ namespace framework {
  */
 class Net : public OperatorBase {
  public:
-  virtual void AddOp(const OperatorPtr& op) = 0;
+  virtual void AddOp(const std::shared_ptr<OperatorBase>& op) = 0;
   virtual void CompleteAddOp(bool calc) = 0;
 };
 
@@ -57,7 +57,7 @@ class PlainNet : public Net {
    * Infer all the operators' input and output variables' shapes, will be called
    * before every mini-batch
    */
-  void InferShape(const ScopePtr& scope) const override {
+  void InferShape(const std::shared_ptr<Scope>& scope) const override {
     for (auto& op : ops_) {
       op->InferShape(scope);
     }
@@ -70,7 +70,7 @@ class PlainNet : public Net {
    * scope will be used instead. If no OpContext is provicded, default context
    * will be used.
    */
-  void Run(const ScopePtr& scope,
+  void Run(const std::shared_ptr<Scope>& scope,
            const platform::DeviceContext& dev_ctx) const override {
     for (auto& op : ops_) {
       op->Run(scope, dev_ctx);
@@ -80,7 +80,7 @@ class PlainNet : public Net {
   /**
    * @brief Add an operator by ptr
    */
-  void AddOp(const OperatorPtr& op) override {
+  void AddOp(const std::shared_ptr<OperatorBase>& op) override {
     PADDLE_ENFORCE(!add_op_done_, "Cannot AddOp when this network is sealed");
     ops_.push_back(op);
   }
@@ -89,7 +89,7 @@ class PlainNet : public Net {
 
   std::string DebugString() const override;
 
-  std::vector<OperatorPtr> ops_;
+  std::vector<std::shared_ptr<OperatorBase>> ops_;
 
  private:
   bool add_op_done_{false};
@@ -100,5 +100,7 @@ class PlainNet : public Net {
   }
 };
 
+std::shared_ptr<PlainNet> AddBackwardOp(std::shared_ptr<PlainNet> ForwardOps);
+
 }  // namespace framework
 }  // namespace paddle

paddle/framework/net_op_test.cc

@@ -3,17 +3,24 @@
 #include <paddle/framework/op_registry.h>
 #include <paddle/framework/operator.h>
 
-namespace pd = paddle::framework;
+USE_OP(add_two);
+USE_OP(mul);
+USE_OP(sigmoid);
+USE_OP(softmax);
+
+namespace paddle {
+namespace framework {
 
 static int infer_shape_cnt = 0;
 static int run_cnt = 0;
 
-class TestOp : public pd::OperatorBase {
+class TestOp : public OperatorBase {
  public:
-  void InferShape(const paddle::framework::ScopePtr& scope) const override {
+  void InferShape(
+      const std::shared_ptr<framework::Scope>& scope) const override {
     ++infer_shape_cnt;
   }
-  void Run(const paddle::framework::ScopePtr& scope,
+  void Run(const std::shared_ptr<framework::Scope>& scope,
            const paddle::platform::DeviceContext& dev_ctx) const override {
     ++run_cnt;
   }
@@ -33,7 +40,7 @@ void AssertSameVectorWithoutOrder(const std::vector<T>& expected,
 }
 
 TEST(OpKernel, all) {
-  auto net = std::make_shared<paddle::framework::PlainNet>();
+  auto net = std::make_shared<PlainNet>();
   ASSERT_NE(net, nullptr);
 
   auto op1 = std::make_shared<TestOp>();
@@ -55,13 +62,37 @@ TEST(OpKernel, all) {
   ASSERT_EQ(1UL, tmp_idx.size());
   ASSERT_EQ("y", net->outputs_[tmp_idx[0]]);
 
-  auto scope = std::make_shared<pd::Scope>();
-  paddle::platform::CPUDeviceContext dev_ctx;
+  auto scope = std::make_shared<Scope>();
+  platform::CPUDeviceContext dev_ctx;
 
   net->InferShape(scope);
   net->Run(scope, dev_ctx);
   ASSERT_EQ(2, infer_shape_cnt);
   ASSERT_EQ(2, run_cnt);
-
   ASSERT_THROW(net->AddOp(op2), std::runtime_error);
 }
+TEST(AddBackwardOp, TestGradOp) {
+  auto net = std::make_shared<PlainNet>();
+  ASSERT_NE(net, nullptr);
+  net->AddOp(framework::OpRegistry::CreateOp("mul", {"X", "Y"}, {"Out"}, {}));
+  net->AddOp(
+      framework::OpRegistry::CreateOp("add_two", {"X", "Y"}, {"Out"}, {}));
+  net->AddOp(framework::OpRegistry::CreateOp("add_two", {"X", "Y"}, {""}, {}));
+  auto grad_ops = AddBackwardOp(net);
+  for (auto& op : grad_ops->ops_) {
+    op->DebugString();
+  }
+}
+
+// TODO(zhihong): add fc grad without registering.
+// TEST(AddBackwardOp, TestNoGradOp) {
+//   auto net = std::make_shared<PlainNet>();
+//   ASSERT_NE(net, nullptr);
+//   net->AddOp(framework::OpRegistry::CreateOp("fc", {"X", "W", "b"}, {"Y"},
+//   {})); auto grad_ops = AddBackwardOp(net); for (auto& op : grad_ops->ops_) {
+//     op->DebugString();
+//   }
+// }
+
+}  // namespace framework
+}  // namespace paddle

paddle/framework/net_test.cc

-/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
-
-   Licensed under the Apache License, Version 2.0 (the "License");
-   you may not use this file except in compliance with the License.
-   You may obtain a copy of the License at
-
-   http://www.apache.org/licenses/LICENSE-2.0
-
-   Unless required by applicable law or agreed to in writing, software
-   distributed under the License is distributed on an "AS IS" BASIS,
-   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-   See the License for the specific language governing permissions and
-   limitations under the License. */
-
-#include "paddle/framework/net.h"
-#include "paddle/framework/op_registry.h"
-
-#include <gtest/gtest.h>
-
-namespace paddle {
-namespace framework {
-class FakeFC : public Operator {}
-}  // namespace framework
-}  // namespace paddle

paddle/framework/op_proto.proto

@@ -84,6 +84,11 @@ message VarProto {
     //   "temporary_index": [1]
     // }
     optional bool temporary = 4 [default=false];
+
+    // The gradient of operator can be ignored immediately
+    // e.g. operator AddOp, y = x1 + x2, the gradient of dy/dx1, dy/dx2
+    // can be ignored for the future optimized on graph.
+    optional bool ignore_gradient = 6;
 }
 
 // Op protocol message for 3rd-party language binding.
@@ -105,4 +110,5 @@ message OpProto {
 
     // The type of that Op.
     required string type = 5;
+
 }

paddle/framework/op_registry.h

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
 #pragma once
 
 #include <algorithm>
@@ -6,9 +20,9 @@
 #include <unordered_map>
 #include <unordered_set>
 #include "paddle/framework/attr_checker.h"
+#include "paddle/framework/grad_op_builder.h"
 #include "paddle/framework/op_desc.pb.h"
-#include "paddle/framework/op_proto.pb.h"
-#include "paddle/framework/operator.h"
+#include "paddle/framework/scope.h"
 
 namespace paddle {
 namespace framework {
@@ -73,25 +87,29 @@ class OpProtoAndCheckerMaker {
 
  protected:
   void AddInput(const std::string& name, const std::string& comment,
-                bool multiple = false) {
+                bool multiple = false, bool ignore_gradient = false) {
     auto input = proto_->mutable_inputs()->Add();
     *input->mutable_name() = name;
     *input->mutable_comment() = comment;
+    input->set_ignore_gradient(ignore_gradient);
     input->set_multiple(multiple);
     if (multiple) {
       SetHasMultipleInput();
     }
   }
 
-  void AddInputs(const std::string& name, const std::string& comment) {
-    AddInput(name, comment, true);
+  void AddInputs(const std::string& name, const std::string& comment,
+                 bool ignore_gradient = false) {
+    AddInput(name, comment, true, ignore_gradient);
   }
 
   void AddOutput(const std::string& name, const std::string& comment,
-                 bool temporary = false, bool multiple = false) {
+                 bool temporary = false, bool multiple = false,
+                 bool ignore_gradient = false) {
     auto output = proto_->mutable_outputs()->Add();
     *output->mutable_name() = name;
     *output->mutable_comment() = comment;
+    output->set_ignore_gradient(ignore_gradient);
     output->set_multiple(multiple);
     if (multiple) {
       SetHasMultipleOutput();
@@ -103,8 +121,8 @@ class OpProtoAndCheckerMaker {
   }
 
   void AddOutputs(const std::string& name, const std::string& comment,
-                  bool temporary = false) {
-    AddOutput(name, comment, temporary, true);
+                  bool temporary = false, bool ignore_gradient = false) {
+    AddOutput(name, comment, temporary, true, ignore_gradient);
   }
 
   template <typename T>
@@ -204,9 +222,9 @@ class OpRegistry {
  public:
   template <typename OpType, typename ProtoMakerType>
   static void RegisterOp(const std::string& op_type) {
-    creators()[op_type] = [] { return new OpType; };
-    OpProto& op_proto = protos()[op_type];
+    op_creators()[op_type] = [] { return new OpType; };
     OpAttrChecker& op_checker = op_checkers()[op_type];
+    OpProto& op_proto = protos()[op_type];
     auto maker = ProtoMakerType(&op_proto, &op_checker);
     maker.Validate();
     *op_proto.mutable_type() = op_type;
@@ -227,18 +245,26 @@ class OpRegistry {
     }
   }
 
-  static OperatorPtr CreateOp(const std::string& type,
+  template <typename GradOpType>
+  static void RegisterGradOp(const std::string& op_type,
+                             const std::string& grad_op_type) {
+    op_creators()[grad_op_type] = [] { return new GradOpType; };
+    grad_ops()[op_type] = grad_op_type;
+  }
+
+  static std::shared_ptr<OperatorBase> 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_create_it = op_creators().find(type);
+    PADDLE_ENFORCE(op_create_it != op_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_);
 
@@ -252,10 +278,10 @@ class OpRegistry {
     }
 
     op->Init();
-    return OperatorPtr(op);
+    return std::shared_ptr<OperatorBase>(op);
   }
 
-  static OperatorPtr CreateOp(const OpDesc& op_desc) {
+  static std::shared_ptr<OperatorBase> CreateOp(const OpDesc& op_desc) {
     std::vector<std::string> inputs;
     inputs.reserve((size_t)op_desc.inputs_size());
     std::copy(op_desc.inputs().begin(), op_desc.inputs().end(),
@@ -274,18 +300,41 @@ class OpRegistry {
     return CreateOp(op_desc.type(), inputs, outputs, attrs);
   }
 
+  static std::shared_ptr<OperatorBase> CreateGradOp(
+      std::shared_ptr<OperatorBase> op) {
+    GradOpBuilder builder(op.get());
+    std::shared_ptr<OperatorBase> grad_op(builder.Build());
+    grad_op->Init();
+    return grad_op;
+  }
+
   static std::unordered_map<std::string, OpProto>& protos() {
     static std::unordered_map<std::string, OpProto> protos_;
     return protos_;
   };
 
- private:
+  static std::unordered_map<std::string, std::string>& grad_ops() {
+    static std::unordered_map<std::string, std::string> grad_ops_;
+    return grad_ops_;
+  }
+
   static std::unordered_map<std::string, std::shared_ptr<VarIndexMap>>&
   VarIndexMaps() {
     static std::unordered_map<std::string, std::shared_ptr<VarIndexMap>> maps_;
     return maps_;
   }
 
+  static std::unordered_map<std::string, OpCreator>& op_creators() {
+    static std::unordered_map<std::string, OpCreator> op_creators_;
+    return op_creators_;
+  }
+
+ private:
+  static std::unordered_map<std::string, OpAttrChecker>& op_checkers() {
+    static std::unordered_map<std::string, OpAttrChecker> op_checkers_;
+    return op_checkers_;
+  };
+
   static void GenerateTempVariableName(OperatorBase* op) {
     static std::atomic<size_t> gUniqId(0UL);
     for (auto& outname : op->outputs_) {
@@ -296,16 +345,6 @@ class OpRegistry {
       }
     }
   }
-
-  static std::unordered_map<std::string, OpCreator>& creators() {
-    static std::unordered_map<std::string, OpCreator> creators_;
-    return creators_;
-  }
-
-  static std::unordered_map<std::string, OpAttrChecker>& op_checkers() {
-    static std::unordered_map<std::string, OpAttrChecker> op_checkers_;
-    return op_checkers_;
-  };
 };
 
 template <typename OpType, typename ProtoMakerType>
@@ -316,6 +355,14 @@ class OpRegisterHelper {
   }
 };
 
+template <typename GradOpType>
+class GradOpRegisterHelper {
+ public:
+  GradOpRegisterHelper(const char* op_type, const char* grad_op_type) {
+    OpRegistry::RegisterGradOp<GradOpType>(op_type, grad_op_type);
+  }
+};
+
 /**
  * check if MACRO is used in GLOBAL NAMESPACE.
  */
@@ -335,6 +382,20 @@ class OpRegisterHelper {
       __op_register_##__op_type##__(#__op_type);                             \
   int __op_register_##__op_type##_handle__() { return 0; }
 
+/**
+ * Macro to Register Gradient Operator.
+ */
+#define REGISTER_GRADIENT_OP(__op_type, __grad_op_type, __grad_op_class)       \
+  STATIC_ASSERT_GLOBAL_NAMESPACE(                                              \
+      __reg_gradient_op__##__op_type##__grad_op_type,                          \
+      "REGISTER_GRADIENT_OP must be in global namespace");                     \
+  static ::paddle::framework::GradOpRegisterHelper<__grad_op_class>            \
+      __op_gradient_register_##__op_type##__grad_op_type##__(#__op_type,       \
+                                                             #__grad_op_type); \
+  int __op_gradient_register_##__op_type##__grad_op_type##_handle__() {        \
+    return 0;                                                                  \
+  }
+
 /**
  * Macro to Register OperatorKernel.
  */

paddle/framework/op_registry_test.cc

@@ -7,9 +7,9 @@ namespace paddle {
 namespace framework {
 class CosineOp : public OperatorBase {
  public:
-  void Run(const ScopePtr& scope,
+  void Run(const std::shared_ptr<Scope>& scope,
            const platform::DeviceContext& dev_ctx) const override {}
-  void InferShape(const ScopePtr& scope) const override {}
+  void InferShape(const std::shared_ptr<Scope>& scope) const override {}
 };
 
 class CosineOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
@@ -27,8 +27,8 @@ class CosineOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
 
 class MyTestOp : public OperatorBase {
  public:
-  void InferShape(const ScopePtr& scope) const override {}
-  void Run(const ScopePtr& scope,
+  void InferShape(const std::shared_ptr<Scope>& scope) const override {}
+  void Run(const std::shared_ptr<Scope>& scope,
            const platform::DeviceContext& dev_ctx) const override {}
 };
 
@@ -67,7 +67,7 @@ TEST(OpRegistry, CreateOp) {
   attr->set_type(paddle::framework::AttrType::FLOAT);
   attr->set_f(scale);
 
-  paddle::framework::OperatorPtr op =
+  std::shared_ptr<paddle::framework::OperatorBase> op =
       paddle::framework::OpRegistry::CreateOp(op_desc);
   auto scope = std::make_shared<paddle::framework::Scope>();
   paddle::platform::CPUDeviceContext dev_ctx;
@@ -89,7 +89,6 @@ TEST(OpRegistry, IllegalAttr) {
 
   bool caught = false;
   try {
-    paddle::framework::OperatorPtr op __attribute__((unused)) =
     paddle::framework::OpRegistry::CreateOp(op_desc);
   } catch (std::runtime_error& err) {
     caught = true;
@@ -110,7 +109,7 @@ TEST(OpRegistry, DefaultValue) {
 
   ASSERT_TRUE(op_desc.IsInitialized());
 
-  paddle::framework::OperatorPtr op =
+  std::shared_ptr<paddle::framework::OperatorBase> op =
       paddle::framework::OpRegistry::CreateOp(op_desc);
   auto scope = std::make_shared<paddle::framework::Scope>();
   paddle::platform::CPUDeviceContext dev_ctx;
@@ -136,7 +135,6 @@ TEST(OpRegistry, CustomChecker) {
   // attr 'test_attr' is not set
   bool caught = false;
   try {
-    paddle::framework::OperatorPtr op __attribute__((unused)) =
     paddle::framework::OpRegistry::CreateOp(op_desc);
   } catch (std::runtime_error& err) {
     caught = true;
@@ -155,7 +153,6 @@ TEST(OpRegistry, CustomChecker) {
   attr->set_i(3);
   caught = false;
   try {
-    paddle::framework::OperatorPtr op __attribute__((unused)) =
     paddle::framework::OpRegistry::CreateOp(op_desc);
   } catch (std::runtime_error& err) {
     caught = true;
@@ -174,8 +171,7 @@ TEST(OpRegistry, CustomChecker) {
   attr->set_type(paddle::framework::AttrType::INT);
   attr->set_i(4);
   SetInputFormat(&op_desc);
-  paddle::framework::OperatorPtr op =
-      paddle::framework::OpRegistry::CreateOp(op_desc);
+  auto op = paddle::framework::OpRegistry::CreateOp(op_desc);
   paddle::platform::CPUDeviceContext dev_ctx;
   auto scope = std::make_shared<paddle::framework::Scope>();
   op->Run(scope, dev_ctx);

paddle/framework/operator.h

@@ -47,7 +47,6 @@ struct EigenDeviceConverter<platform::GPUPlace> {
 #endif
 
 class OperatorBase;
-using OperatorPtr = std::shared_ptr<OperatorBase>;
 /**
  * OperatorBase has the basic element that Net will call to do computation.
  * Only CreateOperator from OpRegistry will new Operator directly. User
@@ -63,6 +62,11 @@ class OperatorBase {
   /// but it will be convert to a unique name in scope after OpCreator.
   static std::string TMP_VAR_NAME() { return "@TEMP@"; }
 
+  /// If a variable's name has a certain suffix, it means that the
+  /// variable is the gradient of another varibale.
+  /// e.g. Variable "x@GRAD" is the gradient of varibale "x".
+  static std::string GRAD_VAR_SUFFIX() { return "@GRAD"; }
+
   virtual ~OperatorBase() {}
 
   template <typename T>
@@ -80,10 +84,10 @@ class OperatorBase {
 
   /// InferShape infer the size of Variables used by this Operator with
   /// information inside scope
-  virtual void InferShape(const ScopePtr& scope) const = 0;
+  virtual void InferShape(const std::shared_ptr<Scope>& scope) const = 0;
 
   /// Net will call this function to Run an op.
-  virtual void Run(const ScopePtr& scope,
+  virtual void Run(const std::shared_ptr<Scope>& scope,
                    const platform::DeviceContext& dev_ctx) const = 0;
 
   // Get a input with argument's name described in `op_proto`
@@ -208,7 +212,7 @@ class OperatorWithKernel : public OperatorBase {
   using OpKernelMap =
       std::unordered_map<OpKernelKey, std::unique_ptr<OpKernel>, OpKernelHash>;
 
-  void Run(const ScopePtr& scope,
+  void Run(const std::shared_ptr<Scope>& scope,
            const platform::DeviceContext& dev_ctx) const final {
     auto& opKernel = AllOpKernels().at(type_).at(OpKernelKey(dev_ctx));
     opKernel->Compute(KernelContext(this, scope, dev_ctx));

paddle/framework/operator_test.cc

@@ -24,8 +24,8 @@ static int op_run_num = 0;
 class OpWithoutKernelTest : public OperatorBase {
  public:
   void Init() override { x = 1; }
-  void InferShape(const ScopePtr& scope) const override {}
-  void Run(const ScopePtr& scope,
+  void InferShape(const std::shared_ptr<Scope>& scope) const override {}
+  void Run(const std::shared_ptr<Scope>& scope,
            const platform::DeviceContext& dev_ctx) const override {
     op_run_num++;
     ASSERT_EQ((int)inputs_.size(), 1);
@@ -70,8 +70,7 @@ TEST(OperatorBase, all) {
   paddle::platform::CPUDeviceContext device_context;
   auto scope = std::make_shared<paddle::framework::Scope>();
 
-  paddle::framework::OperatorPtr op =
-      paddle::framework::OpRegistry::CreateOp(op_desc);
+  auto op = paddle::framework::OpRegistry::CreateOp(op_desc);
   scope->CreateVariable("OUT1");
   ASSERT_EQ(paddle::framework::op_run_num, 0);
   op->Run(scope, device_context);
@@ -189,8 +188,7 @@ TEST(OpKernel, all) {
   paddle::platform::CPUDeviceContext cpu_device_context;
   auto scope = std::make_shared<paddle::framework::Scope>();
 
-  paddle::framework::OperatorPtr op =
-      paddle::framework::OpRegistry::CreateOp(op_desc);
+  auto op = paddle::framework::OpRegistry::CreateOp(op_desc);
   ASSERT_EQ(paddle::framework::cpu_kernel_run_num, 0);
   op->Run(scope, cpu_device_context);
   ASSERT_EQ(paddle::framework::cpu_kernel_run_num, 1);
@@ -236,6 +234,6 @@ TEST(OpKernel, multi_inputs) {
   paddle::platform::CPUDeviceContext cpu_device_context;
   auto scope = std::make_shared<Scope>();
 
-  OperatorPtr op(paddle::framework::OpRegistry::CreateOp(op_desc));
+  auto op = paddle::framework::OpRegistry::CreateOp(op_desc);
   op->Run(scope, cpu_device_context);
 }

paddle/framework/scope.h

@@ -24,7 +24,6 @@ namespace paddle {
 namespace framework {
 
 class Scope;
-using ScopePtr = std::shared_ptr<Scope>;
 
 /**
  * @brief Scope that manage all variables.
@@ -44,7 +43,7 @@ class Scope {
   /**
    * @brief Initialize a Scope with parent.
    */
-  explicit Scope(const ScopePtr& parent) : parent_(parent) {}
+  explicit Scope(const std::shared_ptr<Scope>& parent) : parent_(parent) {}
 
   /**
    * @brief Create Variable
@@ -91,7 +90,7 @@ class Scope {
 
  private:
   std::unordered_map<std::string, std::unique_ptr<Variable>> vars_;
-  ScopePtr parent_{nullptr};
+  std::shared_ptr<Scope> parent_{nullptr};
 };
 
 }  // namespace framework

paddle/operators/add_op.cc

@@ -49,9 +49,22 @@ The equation is: Out = X + Y
 )DOC");
   }
 };
+
+class AddOpGrad : public framework::OperatorWithKernel {
+protected:
+  void InferShape(
+      const std::vector<const framework::Tensor *> &inputs,
+      const std::vector<framework::Tensor *> &outputs) const override {}
+  std::string DebugString() const override {
+    LOG(INFO) << "AddOpGrad";
+    return "";
+  }
+};
+
 }  // namespace operators
 }  // namespace paddle
 
 REGISTER_OP(add_two, paddle::operators::AddOp, paddle::operators::AddOpMaker);
+REGISTER_GRADIENT_OP(add_two, add_two_grad, paddle::operators::AddOpGrad);
 REGISTER_OP_CPU_KERNEL(
     add_two, paddle::operators::AddKernel<paddle::platform::CPUPlace, float>);

paddle/operators/add_op_test.cc

@@ -16,8 +16,13 @@ limitations under the License. */
 #define private public
 #include <paddle/framework/op_registry.h>
 USE_OP(add_two);
+// USE_OP(add_two_grad);
+
 TEST(AddOp, GetOpProto) {
   auto& protos = paddle::framework::OpRegistry::protos();
   auto it = protos.find("add_two");
   ASSERT_NE(it, protos.end());
+  auto& op_creators = paddle::framework::OpRegistry::op_creators();
+  auto it1 = op_creators.find("add_two_grad");
+  ASSERT_NE(it1, op_creators.end());
 }

paddle/operators/mul_op.cc

@@ -52,9 +52,22 @@ The equation is: Out = X * Y
   }
 };
 
+class MulOpGrad : public framework::OperatorWithKernel {
+protected:
+  void InferShape(
+      const std::vector<const framework::Tensor *> &inputs,
+      const std::vector<framework::Tensor *> &outputs) const override {}
+  std::string DebugString() const override {
+    LOG(INFO) << "MulGrad";
+    return "";
+  }
+};
+
 }  // namespace operators
 }  // namespace paddle
 
 REGISTER_OP(mul, paddle::operators::MulOp, paddle::operators::MulOpMaker);
+REGISTER_GRADIENT_OP(mul, mul_grad, paddle::operators::MulOpGrad);
+
 REGISTER_OP_CPU_KERNEL(
     mul, paddle::operators::MulKernel<paddle::platform::CPUPlace, float>);

paddle/operators/sigmoid_op.cc

@@ -39,12 +39,25 @@ public:
   }
 };
 
+class SigmoidOpGrad : public framework::OperatorWithKernel {
+protected:
+  void InferShape(
+      const std::vector<const framework::Tensor *> &inputs,
+      const std::vector<framework::Tensor *> &outputs) const override {}
+  std::string DebugString() const override {
+    LOG(INFO) << "SigmoidGrad";
+    return "";
+  }
+};
+
 }  // namespace operators
 }  // namespace paddle
 
 REGISTER_OP(sigmoid,
             paddle::operators::SigmoidOp,
             paddle::operators::SigmoidOpMaker);
+REGISTER_GRADIENT_OP(sigmoid, sigmoid_grad, paddle::operators::SigmoidOpGrad);
+
 REGISTER_OP_CPU_KERNEL(
     sigmoid,
     paddle::operators::SigmoidKernel<paddle::platform::CPUPlace, float>);

paddle/operators/softmax_op.cc

@@ -42,11 +42,23 @@ public:
   }
 };
 
+class SoftmaxOpGrad : public framework::OperatorWithKernel {
+protected:
+  void InferShape(
+      const std::vector<const framework::Tensor *> &inputs,
+      const std::vector<framework::Tensor *> &outputs) const override {}
+  std::string DebugString() const override {
+    LOG(INFO) << "SoftmaxOpGrad";
+    return "";
+  }
+};
+
 }  // namespace operators
 }  // namespace paddle
 
 namespace ops = paddle::operators;
 
 REGISTER_OP(softmax, ops::SoftmaxOp, ops::SoftmaxOpMaker);
+REGISTER_GRADIENT_OP(softmax, softmax_grad, paddle::operators::SoftmaxOpGrad);
 REGISTER_OP_CPU_KERNEL(softmax,
                        ops::SoftmaxKernel<paddle::platform::CPUPlace, float>);

paddle/pybind/pybind.cc

@@ -126,9 +126,10 @@ All parameter, weight, gradient are variables in Paddle.
         return new paddle::platform::CPUDeviceContext();
       });
 
-  py::class_<pd::OperatorBase, pd::OperatorPtr> operator_base(m, "Operator");
+  py::class_<pd::OperatorBase, std::shared_ptr<pd::OperatorBase>> operator_base(
+      m, "Operator");
 
-  operator_base.def_static("create", [](py::bytes protobin) -> pd::OperatorPtr {
+  operator_base.def_static("create", [](py::bytes protobin) {
     pd::OpDesc desc;
     PADDLE_ENFORCE(desc.ParsePartialFromString(protobin),
                    "Cannot parse user input to OpDesc");

python/paddle/trainer_config_helpers/networks.py

@@ -340,24 +340,40 @@ def img_conv_group(input,
                    conv_with_batchnorm=False,
                    conv_batchnorm_drop_rate=0,
                    pool_stride=1,
-                   pool_type=None):
+                   pool_type=None,
+                   param_attr=None):
     """
     Image Convolution Group, Used for vgg net.
 
-    TODO(yuyang18): Complete docs
-
-    :param conv_batchnorm_drop_rate:
-    :param input:
-    :param conv_num_filter:
-    :param pool_size:
-    :param num_channels:
-    :param conv_padding:
-    :param conv_filter_size:
-    :param conv_act:
-    :param conv_with_batchnorm:
-    :param pool_stride:
-    :param pool_type:
-    :return:
+    :param conv_batchnorm_drop_rate: if conv_with_batchnorm[i] is true,
+        conv_batchnorm_drop_rate[i] represents the drop rate of each batch norm.
+    :type conv_batchnorm_drop_rate: list
+    :param input: layer's input.
+    :type input: LayerOutput
+    :param conv_num_filter: output channels num.
+    :type conv_num_filter: int
+    :param pool_size: pooling filter size.
+    :type pool_size: int
+    :param num_channels: input channels num.
+    :type num_channels: int
+    :param conv_padding: convolution padding size.
+    :type conv_padding: int
+    :param conv_filter_size: convolution filter size.
+    :type conv_filter_size: int
+    :param conv_act: activation funciton after convolution.
+    :type conv_act: BaseActivation
+    :param conv_with_batchnorm: conv_with_batchnorm[i] represents
+        if there is a batch normalization after each convolution.
+    :type conv_with_batchnorm: list
+    :param pool_stride: pooling stride size.
+    :type pool_stride: int
+    :param pool_type: pooling type.
+    :type pool_type: BasePoolingType
+    :param param_attr: Convolution param attribute.
+        None means default attribute.
+    :type param_attr: ParameterAttribute
+    :return: Layer's output
+    :type: LayerOutput
     """
     tmp = input
 
@@ -397,6 +413,7 @@ def img_conv_group(input,
             padding=conv_padding[i],
             filter_size=conv_filter_size[i],
             num_filters=conv_num_filter[i],
+            param_attr=param_attr,
             **extra_kwargs)
 
         # logger.debug("tmp.num_filters = %d" % tmp.num_filters)

python/paddle/v2/__init__.py

@@ -33,6 +33,7 @@ import networks
 import minibatch
 import plot
 import image
+import model
 
 __all__ = [
     'optimizer',
@@ -54,6 +55,7 @@ __all__ = [
     'evaluator',
     'image',
     'master',
+    'model',
 ]
 
 

python/paddle/v2/master/client.py

@@ -10,11 +10,31 @@ class client(object):
     client is a client to the master server.
     """
 
-    def __init__(self, etcd_endpoints, timeout, buf_size):
-        self.c = lib.paddle_new_etcd_master_client(etcd_endpoints, timeout,
+    def __init__(self, etcd_endpoints, timeout_sec, buf_size=0):
+        self.c = lib.paddle_new_etcd_master_client(etcd_endpoints, timeout_sec,
                                                    buf_size)
 
-    def close(self):
+    def request_save_model(self, trainer_id, block_ms):
+        """request to save model
+
+        Conventionally the 0-th trainer will save model. But in
+        distributed training, any trainer could be killed. This
+        function asks the master server if the trainer should proceed
+        with saving model.
+
+        :param trainer_id: trainer id.
+        :param block_ms: number of millisecond that other save model
+        will be blocked if this save model request succeeded.
+
+        Returns:
+            int: 1 if the save the model request is approved, 0 if
+            does the request is rejected because other trainer is
+            saving the model, -1 if error happened.
+
+        """
+        return lib.paddle_request_save_model(self.c, trainer_id, block_ms)
+
+    def release(self):
         lib.paddle_release_master_client(self.c)
         self.c = None
 
@@ -27,10 +47,13 @@ class client(object):
             holder[idx] = c_ptr
         lib.paddle_set_dataset(self.c, holder, len(paths))
 
-    # return format: (record, errno)
-    # errno =  0: ok
-    #       <  0: error
     def next_record(self):
+        """gets next record for training
+
+        Returns:
+            string: the record.
+            int: error code, 0 if successful, < 0 otherwise.
+        """
         p = ctypes.c_char_p()
         ret = ctypes.pointer(p)
         size = lib.paddle_next_record(self.c, ret)

python/paddle/v2/model.py

+# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
+#
+# 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.
+
+import os
+import errno
+import uuid
+
+import paddle.v2.master
+
+__all__ = ["save_model", "load_model"]
+
+trainer_id = str(uuid.uuid4())
+
+
+def mkdir_p(path):
+    try:
+        os.makedirs(path)
+    except OSError as exc:
+        if exc.errno == errno.EEXIST and os.path.isdir(path):
+            pass
+        else:
+            raise
+
+
+def save_model(parameters, path):
+    need_request = "KUBERNETES_SERVICE_HOST" in os.environ.keys()
+
+    if need_request:
+        # TODO(helin): figure out how MPI trains, since MPI only save
+        # model when trainer_id == "0", we can consolidate the logic
+        # here.
+
+        # TODO(helin): change this environment variable name from
+        # MASTER_IP to ETCD_IP
+        etcd_name = "MASTER_IP"
+        if etcd_name not in os.environ.keys():
+            raise Exception('not find ' + etcd_name +
+                            ' in environment variable.')
+
+        etcd_ip = os.environ.get(etcd_name)
+        client = master.client("http://" + etcd_ip + ":2379", 5, 0)
+        r = client.request_save_model(trainer_id, 5000)
+        if r == 0:
+            # do not need to save
+            return
+        elif r < 0:
+            # error
+            return
+        else:
+            # save model
+            path = os.path.join(path, trainer_id)
+            path = os.path.join(path, "model.tar")
+
+    mkdir_p(path)
+
+    with open(path, 'wb') as f:
+        parameters.to_tar(f)
+
+
+def load_model(parameters, path):
+    with open(path, 'rb') as f:
+        parameters.from_tar(f)

python/paddle/v2/reader/creator.py

@@ -12,8 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """
-Creator package contains some simple reader creator, which could be used in user
-program.
+Creator package contains some simple reader creator, which could
+be used in user program.
 """
 
 __all__ = ['np_array', 'text_file', "recordio"]
@@ -96,7 +96,7 @@ def recordio(paths, buf_size=100):
 
     host_name = "MASTER_SERVICE_HOST"
     if host_name not in os.environ.keys():
-        raise Exception('not find ' + host_name + ' in environ.')
+        raise Exception('not find ' + host_name + ' in environment variable.')
 
     addr = os.environ(host)
 
@@ -110,6 +110,6 @@ def recordio(paths, buf_size=100):
                 break
             yield r
 
-        c.close()
+        c.release()
 
     return reader