Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into dev_enable_tensor_test

Dockerfile

@@ -25,7 +25,7 @@ COPY ./paddle/scripts/docker/root/ /root/
 RUN apt-get update && \
     apt-get install -y \
     git python-pip python-dev openssh-server bison  \
-    wget unzip tar xz-utils bzip2 gzip coreutils ntp \
+    wget unzip unrar tar xz-utils bzip2 gzip coreutils ntp \
     curl sed grep graphviz libjpeg-dev zlib1g-dev  \
     python-numpy python-matplotlib gcc g++ \
     automake locales clang-format-3.8 swig doxygen cmake  \

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
 

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()
@@ -193,6 +194,10 @@ ELSE()
         SET(CMAKE_ANDROID_STANDALONE_TOOLCHAIN ${ANDROID_STANDALONE_TOOLCHAIN})
     ENDIF()
     SET(CMAKE_ANDROID_ARCH_ABI ${ANDROID_ABI})
+    IF(ANDROID_ABI MATCHES "^armeabi(-v7a)?$")
         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()

go/cmd/master/master.go

@@ -11,6 +11,7 @@ import (
 
 	"github.com/namsral/flag"
 	log "github.com/sirupsen/logrus"
+	"github.com/topicai/candy"
 
 	"github.com/PaddlePaddle/Paddle/go/master"
 	"github.com/PaddlePaddle/Paddle/go/utils/networkhelper"
@@ -20,11 +21,18 @@ func main() {
 	port := flag.Int("port", 8080, "port of the master server.")
 	ttlSec := flag.Int("ttl", 60, "etcd lease TTL in seconds.")
 	endpoints := flag.String("endpoints", "http://127.0.0.1:2379", "comma separated etcd endpoints. If empty, fault tolerance will not be enabled.")
-	taskTimeoutDur := flag.Duration("task_timout_dur", 20*time.Minute, "task timout duration.")
-	taskTimeoutMax := flag.Int("task_timeout_max", 3, "max timtout count for each task before it being declared failed task.")
-	chunkPerTask := flag.Int("chunk_per_task", 10, "chunk per task.")
+	taskTimeoutDur := flag.Duration("task-timout-dur", 20*time.Minute, "task timout duration.")
+	taskTimeoutMax := flag.Int("task-timeout-max", 3, "max timtout count for each task before it being declared failed task.")
+	chunkPerTask := flag.Int("chunk-per-task", 10, "chunk per task.")
+	logLevel := flag.String("log-level", "info",
+		"log level, possible values: debug, info, warning, error, fatal, panic")
 	flag.Parse()
 
+	level, e := log.ParseLevel(*logLevel)
+	candy.Must(e)
+
+	log.SetLevel(level)
+
 	if *endpoints == "" {
 		log.Warningln("-endpoints not set, fault tolerance not be enabled.")
 	}

go/cmd/pserver/pserver.go

@@ -40,7 +40,7 @@ func main() {
 		idx = *index
 	} else {
 		e = pserver.NewEtcdClient(*etcdEndpoint, *numPservers, *etcdTimeout)
-		idx, err = e.Register()
+		idx, err = e.Register(*port)
 		candy.Must(err)
 
 		cp, err = pserver.NewCheckpointFromFile(*checkpointPath, idx, e)

go/master/client.go

@@ -2,6 +2,7 @@ package master
 
 import (
 	"os"
+	"time"
 
 	"github.com/PaddlePaddle/Paddle/go/connection"
 	"github.com/PaddlePaddle/recordio"
@@ -36,9 +37,9 @@ func (c *Client) getRecords() {
 	for {
 		t, err := c.getTask()
 		if err != nil {
-			// TODO(helin): wait before move on with next
 			// getTask call.
-			log.Errorln(err)
+			log.Errorf("Get task failed, sleep 3 seconds and continue, %s", err)
+			time.Sleep(3 * time.Second)
 			continue
 		}
 

go/master/service.go

@@ -215,6 +215,7 @@ func readChunks(globPaths []string) ([]Chunk, error) {
 		}
 
 		count := index.NumChunks()
+		log.Infof("readChunks: file %s has %d chunks", path, count)
 		for i := 0; i < count; i++ {
 			chunk := Chunk{
 				Path:  path,

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

 import paddle.v2 as paddle
 import paddle.v2.dataset.uci_housing as uci_housing
+import paddle.v2.master as master
+import os
+import cPickle as pickle
+
+etcd_ip = os.getenv("MASTER_IP", "127.0.0.1")
+etcd_endpoint = "http://" + etcd_ip + ":2379"
+
+
+def cloud_reader():
+    print "connecting to master, etcd endpoints: ", etcd_endpoint
+    master_client = master.client(etcd_endpoint, 5, 64)
+    master_client.set_dataset(
+        ["/pfs/dlnel/public/dataset/uci_housing/uci_housing-*-of-*"])
+    while 1:
+        r, e = master_client.next_record()
+        if not r:
+            break
+        yield pickle.loads(r)
 
 
 def main():
@@ -22,13 +40,13 @@ def main():
     # create optimizer of new remote updater to pserver
     optimizer = paddle.optimizer.Momentum(momentum=0)
 
-    #TODO(zhihong) : replace optimizer with new OptimizerConfig
-
+    print "etcd endoint: ", etcd_endpoint
     trainer = paddle.trainer.SGD(cost=cost,
                                  parameters=parameters,
                                  update_equation=optimizer,
                                  is_local=False,
-                                 pserver_spec="localhost:3000")
+                                 pserver_spec=etcd_endpoint,
+                                 use_etcd=True)
 
     # event_handler to print training and testing info
     def event_handler(event):
@@ -47,11 +65,11 @@ def main():
                 print "Test %d, %.2f" % (event.pass_id, result.cost)
 
     # training
+    # NOTE: use uci_housing.train() as reader for non-paddlecloud training
     trainer.train(
         reader=paddle.batch(
             paddle.reader.shuffle(
-                uci_housing.train(), buf_size=500),
-            batch_size=2),
+                cloud_reader, buf_size=500), batch_size=2),
         feeding={'x': 0,
                  'y': 1},
         event_handler=event_handler,

go/pserver/client/etcd_client.go

@@ -12,6 +12,7 @@ import (
 )
 
 const (
+	// DefaultEtcdTimeout is the default etcd timeout
 	DefaultEtcdTimeout time.Duration = 5 * time.Second
 )
 
@@ -66,12 +67,12 @@ 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
 			}

go/pserver/etcd_client.go

@@ -49,7 +49,7 @@ func NewEtcdClient(endpoints string, numPservers int, timeout time.Duration) *Et
 // Register registers the pserver on etcd
 //
 // Register returns the index of the current pserver.
-func (e *EtcdClient) Register() (int, error) {
+func (e *EtcdClient) Register(port int) (int, error) {
 
 	var err error
 	e.externalIP, err = networkhelper.GetExternalIP()
@@ -116,7 +116,7 @@ func (e *EtcdClient) Register() (int, error) {
 	for {
 		ctx, cancel := context.WithTimeout(context.Background(), time.Second)
 		var err error
-		pserverIdx, err = e.registerPserverEtcd(ctx)
+		pserverIdx, err = e.registerPserverEtcd(ctx, port)
 		cancel()
 		if err != nil {
 			log.Warn(err)
@@ -140,7 +140,7 @@ func (e *EtcdClient) initDesiredPservers(ctx context.Context, numPservers int) (
 }
 
 // registerPserverEtcd registers pserver node on etcd using transaction.
-func (e *EtcdClient) registerPserverEtcd(ctx context.Context) (int, error) {
+func (e *EtcdClient) registerPserverEtcd(ctx context.Context, port int) (int, error) {
 	var idx int
 	_, err := concurrency.NewSTM(e.etcdClient, func(c concurrency.STM) error {
 		registered := false
@@ -156,8 +156,9 @@ func (e *EtcdClient) registerPserverEtcd(ctx context.Context) (int, error) {
 					log.Fatal(err)
 				}
 				// find the first id and write info
-				c.Put(psKey, e.externalIP, clientv3.WithLease(resp.ID))
-				log.Debugf("set pserver node %s with value %s", psKey, e.externalIP)
+				pserverAddr := e.externalIP + ":" + strconv.Itoa(port)
+				c.Put(psKey, pserverAddr, clientv3.WithLease(resp.ID))
+				log.Debugf("set pserver node %s with value %s", psKey, pserverAddr)
 				ch, kaerr := e.etcdClient.KeepAlive(context.TODO(), resp.ID)
 				if kaerr != nil {
 					log.Errorf("keepalive etcd node error: %v", kaerr)

paddle/api/PaddleAPI.h

@@ -843,7 +843,8 @@ public:
                                                bool useSparseUpdater);
   static ParameterUpdater* createNewRemoteUpdater(
       OptimizationConfig* config,
-      const std::string pserverSpec) throw(UnsupportError);
+      const std::string pserverSpec,
+      const bool useEtcd) throw(UnsupportError);
   ~ParameterUpdater();
 
   /**

paddle/api/ParameterUpdater.cpp

@@ -33,11 +33,12 @@ ParameterUpdater *ParameterUpdater::createLocalUpdater(
 
 ParameterUpdater *ParameterUpdater::createNewRemoteUpdater(
     OptimizationConfig *config,
-    const std::string pserverSpec) throw(UnsupportError) {
+    const std::string pserverSpec,
+    const bool useEtcd) throw(UnsupportError) {
 #ifndef PADDLE_WITHOUT_GOLANG
   auto updater = new ParameterUpdater();
   updater->m->updater.reset(new paddle::NewRemoteParameterUpdater(
-      config->m->getConfig(), pserverSpec));
+      config->m->getConfig(), pserverSpec, useEtcd));
   return updater;
 #else
   throw UnsupportError();

paddle/framework/CMakeLists.txt

-# 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 place paddle_memory)
+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_test(enforce_test SRCS enforce_test.cc)
 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)
+
+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_library(op_registry SRCS op_registry.cc DEPS op_proto op_desc enforce)
 cc_test(op_registry_test SRCS op_registry_test.cc DEPS op_registry operator)
+
 py_proto_compile(framework_py_proto SRCS attr_type.proto op_proto.proto op_desc.proto)
 # Generate an empty __init__.py to make framework_py_proto as a valid python module.
 add_custom_target(framework_py_proto_init ALL COMMAND ${CMAKE_COMMAND} -E touch __init__.py)
 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 net_proto)
+cc_library(net SRCS net.cc DEPS operator net_proto op_registry)
+cc_test(net_op_test SRCS net_op_test.cc DEPS net)

paddle/framework/ddim.cc

@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/framework/ddim.h"
+#include "paddle/framework/enforce.h"
 
 namespace paddle {
 namespace framework {
@@ -192,13 +193,56 @@ std::vector<int> vectorize(const DDim& ddim) {
   return result;
 }
 
+struct ProductVisitor : public boost::static_visitor<ssize_t> {
+  template <int D>
+  ssize_t operator()(const Dim<D>& dim) {
+    return product(dim);
+  }
+};
+
 ssize_t product(const DDim& ddim) {
-  ssize_t result = 1;
-  std::vector<int> v = vectorize(ddim);
-  for (auto i : v) {
-    result *= i;
+  ProductVisitor visitor;
+  return boost::apply_visitor(visitor, ddim);
+}
+
+struct SliceVectorizeVisitor : public boost::static_visitor<> {
+  std::vector<int>& vector;
+  int begin;
+  int end;
+
+  SliceVectorizeVisitor(std::vector<int>& v, int b, int e)
+      : vector(v), begin(b), end(e) {
+    PADDLE_ENFORCE(begin < end,
+                   "Begin index must be less than end index in ddim slice.");
+    PADDLE_ENFORCE(begin >= 0,
+                   "Begin index can't be less than zero in ddim slice.");
   }
-  return result;
+
+  template <int S>
+  void operator()(const Dim<S>& dim) {
+    if (begin == 0) {
+      vector.push_back(dim.head);
+    } else {
+      --begin;
+    }
+    --end;
+    if (end > 0) {
+      this->operator()(dim.tail);
+    }
+  }
+
+  void operator()(const Dim<1>& dim) {
+    PADDLE_ENFORCE(end == 1, "End index in ddim slice is out of bound.");
+    vector.push_back(dim.head);
+  }
+};
+
+DDim slice_ddim(const DDim& dim, int begin, int end) {
+  std::vector<int> vec;
+  vec.reserve(end - begin);
+  SliceVectorizeVisitor visitor(vec, begin, end);
+  boost::apply_visitor(visitor, dim);
+  return make_ddim(vec);
 }
 
 /// \cond HIDDEN

paddle/framework/ddim.h

@@ -81,6 +81,15 @@ std::vector<int> vectorize(const DDim& ddim);
 
 ssize_t product(const DDim& ddim);
 
+/**
+ * \brief Slice a ddim
+ *
+ * Slice dim with [begin, end).
+ * e.g.  DDim d = make_ddim({1,2,3,4,5});
+ *       slice_ddim(d, 1, 3); ====> {2,3}
+ */
+DDim slice_ddim(const DDim& dim, int begin, int end);
+
 /**
  * \brief What is the length of this dimension?
  *

paddle/framework/ddim_test.cc

@@ -52,6 +52,26 @@ TEST(DDim, Equality) {
 
   // product of a DDim
   EXPECT_EQ(paddle::framework::product(vddim), 45);
+  EXPECT_EQ(
+      paddle::framework::product(paddle::framework::make_ddim({3, 2, 5, 3})),
+      90);
+
+  // slice a DDim
+  paddle::framework::DDim ddim2 =
+      paddle::framework::make_ddim({1, 2, 3, 4, 5, 6});
+  paddle::framework::DDim ss = paddle::framework::slice_ddim(ddim2, 2, 5);
+  EXPECT_EQ(arity(ss), 3);
+  EXPECT_EQ(ss[0], 3);
+  EXPECT_EQ(ss[1], 4);
+  EXPECT_EQ(ss[2], 5);
+  paddle::framework::DDim ss2 = paddle::framework::slice_ddim(ddim2, 0, 6);
+  EXPECT_EQ(arity(ss2), 6);
+  EXPECT_EQ(ss2[0], 1);
+  EXPECT_EQ(ss2[1], 2);
+  EXPECT_EQ(ss2[2], 3);
+  EXPECT_EQ(ss2[3], 4);
+  EXPECT_EQ(ss2[4], 5);
+  EXPECT_EQ(ss2[5], 6);
 }
 
 TEST(DDim, Print) {

paddle/framework/dim_test.cu

 #include <thrust/device_vector.h>
 #include <sstream>
 
-#include "paddle/framework/dim.h"
 #include "gtest/gtest.h"
+#include "paddle/framework/dim.h"
 
 __global__ void test(paddle::framework::Dim<2>* o) {
   o[0] = paddle::framework::make_dim(5, 6);
@@ -21,7 +21,7 @@ TEST(Dim, Equality) {
 
   // construct a Dim on the GPU
   thrust::device_vector<paddle::framework::Dim<2>> t(2);
-    test<<<1,1>>>(thrust::raw_pointer_cast(t.data()));
+  test<<<1, 1>>>(thrust::raw_pointer_cast(t.data()));
   a = t[0];
   EXPECT_EQ(paddle::framework::get<0>(a), 5);
   EXPECT_EQ(paddle::framework::get<1>(a), 6);
@@ -48,12 +48,13 @@ TEST(Dim, Equality) {
 
   // dynamic access on GPU
   thrust::device_vector<int> r(1);
-    dyn_idx_gpu<<<1,1>>>(thrust::raw_pointer_cast(r.data()));
+  dyn_idx_gpu<<<1, 1>>>(thrust::raw_pointer_cast(r.data()));
   int res = r[0];
   EXPECT_EQ(res, 6);
 
   // ex_prefix_mul
-    paddle::framework::Dim<3> c = paddle::framework::ex_prefix_mul(paddle::framework::Dim<3>(3, 4, 5));
+  paddle::framework::Dim<3> c =
+      paddle::framework::ex_prefix_mul(paddle::framework::Dim<3>(3, 4, 5));
   EXPECT_EQ(paddle::framework::get<0>(c), 1);
   EXPECT_EQ(paddle::framework::get<1>(c), 3);
   EXPECT_EQ(paddle::framework::get<2>(c), 12);

paddle/framework/enforce.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/enforce.h"

paddle/framework/enforce.h

@@ -10,6 +10,7 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #pragma once
+#include <glog/logging.h>
 #include <paddle/string/printf.h>
 #include <exception>
 #include <sstream>
@@ -58,12 +59,17 @@ class EnforceNotMet : public std::exception {
 /**
  * @brief Enforce a condition, otherwise throw an EnforceNotMet
  */
+#ifdef NDEBUG
 #define PADDLE_ENFORCE(condition, ...) \
   do {                                 \
     if (UNLIKELY(!(condition))) {      \
       PADDLE_THROW(__VA_ARGS__);       \
     }                                  \
   } while (0)
+#else
+#define PADDLE_ENFORCE(condition, ...) \
+  CHECK(condition) << ::paddle::string::Sprintf(__VA_ARGS__);
+#endif
 
 }  // namespace framework
 }  // namespace paddle

paddle/framework/net.cc

@@ -19,18 +19,41 @@
 namespace paddle {
 namespace framework {
 
-PlainNet::PlainNet(const NetDesc& def) {}
-
-void PlainNet::InferShape(const ScopePtr& scope) const {
+void PlainNet::CompleteAddOp() {
+  std::unordered_set<std::string> input_set;
+  std::unordered_set<std::string> output_set;
+  std::unordered_set<std::string> temp_output;
   for (auto& op : ops_) {
-    op.InferShape();
+    for (auto& ipt : op->inputs_) {
+      if (!Contains(output_set, ipt)) {  // Not other op's output
+        input_set.insert(ipt);
+      } else {
+        temp_output.insert(ipt);
+      }
     }
-}
 
-void PlainNet::Run(const ScopePtr& scope, const DeviceContext& ctx) const {
-  for (auto& op : ops_) {
-    op.Run(ctx);
+    for (auto& opt : op->outputs_) {
+      output_set.insert(opt);
+    }
   }
+  inputs_.reserve(input_set.size());
+  std::copy(input_set.begin(), input_set.end(), std::back_inserter(inputs_));
+
+  outputs_.reserve(output_set.size());
+  std::vector<int> tmp_index;
+  tmp_index.reserve(temp_output.size());
+  int idx = 0;
+  for (auto& opt : output_set) {
+    if (Contains(temp_output, opt)) {
+      tmp_index.push_back(idx);
+    }
+    outputs_.push_back(opt);
+    ++idx;
+  }
+
+  attrs_["temporary_index"] = tmp_index;
+  add_op_done_ = true;
 }
+
 }  // namespace framework
 }  // namespace paddle

paddle/framework/net.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
+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. */
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
 
 #pragma once
 
+#include <paddle/framework/op_desc.pb.h>
+#include <paddle/framework/operator.h>
 #include "paddle/framework/net_proto.pb.h"
 #include "paddle/framework/op_proto.pb.h"
+#include "paddle/framework/op_registry.h"
 #include "paddle/framework/scope.h"
 #include "paddle/platform/device_context.h"
 
 namespace paddle {
 namespace framework {
-using namespace paddle::platform;
-
-// operator's index stored in a network.
-typedef int OpIndex;
-/**
- * NOTE following codes are some definitions of unimplemented concepts.
- * We write some basic implementation to make Net compilable. These APIs will
- * keep updating if the concepts related are implemented.
- */
-
-struct OpDesc;
-struct OpAttrs {};
-
-class Operator {
- public:
-  Operator(const OpDesc &def) {}
-  void InferShape() const {}
-  void Run(const DeviceContext &ctx) const {}
-};
-
 /**
- * @brief Network that manage the operators it has.
+ * @brief Network is also a type of Operator
+ *
+ * It will manage the operators it has.
  *
- * Network is the container and controller of a set of operators, user can build
- * a real network from a NetDesc which is a protobuf message and use
- * Network.Run() * to run all the operators in the network.
+ * Network is the container and controller of a set of operators.
 
  * A network object knows all Operators belonging to this network. Variables,
  * which are inputs and outputs of these operators, are created and managed by a
  * hierarchy of Scope objects.
  *
- * This is the base class of network, all the networks should implement the apis
+ * This is the base class of network, all the networks should implement the APIs
  * it defines.
  */
-class Net {
+class Net : public OperatorBase {
  public:
-  /**
-   * @brief Infer shapes of all inputs and outputs of operators.
-   */
-  virtual void InferShape(const ScopePtr &scope) const = 0;
-  /**
-   * @brief Run the network.
-   *
-   * Run all the operators and return success(true) or not, with all the
-   * variables are located in `scope`. `context` describes the detail execution
-   * environment for ops. `begin` and `end` specify the scope of `ops_` to run,
-   * If no positive indexes are provided, all operators in `ops_` will run.
-   */
-  virtual void Run(const ScopePtr &scope, const DeviceContext &ctx) const = 0;
-
-  /**
-   * @brief Add an Operator according to `def`.
-   */
-  virtual OpIndex AddOp(const OpProto &def) = 0;
-
-  /**
-   * @brief Add optimizer operators acctording to `attrs`.
-   */
-  virtual void AddOptimizerOps(const OpAttrs &attrs) = 0;
-
-  /**
-   * @brief Add backward operators.
-   */
-  virtual void AddBackwardOps() = 0;
-
-  /**
-   * @brief Create a network.
-   */
-  static std::unique_ptr<Net> Create(const NetDesc &def = NetDesc());
-
-  virtual ~Net() {}
+  virtual void AddOp(const OperatorPtr& op) = 0;
+  virtual void CompleteAddOp() = 0;
 };
 
+using NetPtr = std::shared_ptr<Net>;
+
 /**
  * @brief a basic implementation of Net.
  *
@@ -103,18 +55,14 @@ class Net {
 class PlainNet : public Net {
  public:
   /**
-   * @brief Initialize a PlainNet.
-   *
-   * Initialize from  a network describe by `def`. NetDesc is the definition of
-   * a network.
-   */
-  PlainNet(const NetDesc &def);
-
-  /**
-   * Infer all the operators' input and output varialbes' shapes, will be called
+   * Infer all the operators' input and output variables' shapes, will be called
    * before every mini-batch
    */
-  virtual void InferShape(const ScopePtr &scope) const override;
+  void InferShape(const ScopePtr& scope) const override {
+    for (auto& op : ops_) {
+      op->InferShape(scope);
+    }
+  }
 
   /**
    * @brief Run the network.
@@ -123,49 +71,32 @@ class PlainNet : public Net {
    * scope will be used instead. If no OpContext is provicded, default context
    * will be used.
    */
-  virtual void Run(const ScopePtr &scope,
-                   const DeviceContext &ctx) const override;
+  void Run(const ScopePtr& scope,
+           const platform::DeviceContext& dev_ctx) const override {
+    for (auto& op : ops_) {
+      op->Run(scope, dev_ctx);
+    }
+  }
 
   /**
-   * @brief Add an operator to this network.
+   * @brief Add an operator by ptr
    */
-  virtual OpIndex AddOp(const OpProto &def) override;
+  void AddOp(const OperatorPtr& op) override {
+    PADDLE_ENFORCE(!add_op_done_, "Cannot AddOp when this network is sealed");
+    ops_.push_back(op);
+  }
 
-  /**
-   * @brief Add all optimizer operators related into the network.
-   */
-  virtual void AddOptimizerOps(const OpAttrs &attrs) override;
+  void CompleteAddOp() override;
 
-  /**
-   * @brief Add all backward operators related into the network.
-   */
-  virtual void AddBackwardOps() override;
-
-  virtual ~PlainNet() override {}
-
- protected:
-  /**
-   * @brief Build the network.
-   *
-   * Create operators accordding to `def`, will be called by the constructor.
-   */
-  void BuildNet(const NetDesc &def);
-
-  /**
-   * @brief Add an operator into this network.
-   *
-   * Add a operator which is identified as `type` and has attributes described
-   * in `attrs`, the `inputs` are the keys of readonly input variables,
-   * `outputs` are keys of mutable output variables. An `OpIndex` will be
-   * returned to indicate the offset of the new operator in `ops_`.
-   */
-  OpIndex AddOp(const std::string &type, const std::vector<std::string> &inputs,
-                const std::vector<std::string> &outputs,
-                const OpAttrs &attrs = OpAttrs());
+  std::vector<OperatorPtr> ops_;
 
  private:
-  // the operators owned by `Network`.
-  std::vector<Operator> ops_;
+  bool add_op_done_{false};
+
+  template <typename T, typename KeyType>
+  static bool Contains(T container, KeyType key) {
+    return container.find(key) != container.end();
+  }
 };
 
 }  // namespace framework

paddle/framework/net_op_test.cc

+#include <gtest/gtest.h>
+#include <paddle/framework/net.h>
+#include <paddle/framework/op_registry.h>
+#include <paddle/framework/operator.h>
+
+namespace pd = paddle::framework;
+
+static int infer_shape_cnt = 0;
+static int run_cnt = 0;
+
+class TestOp : public pd::OperatorBase {
+ public:
+  void InferShape(const paddle::framework::ScopePtr& scope) const override {
+    ++infer_shape_cnt;
+  }
+  void Run(const paddle::framework::ScopePtr& scope,
+           const paddle::platform::DeviceContext& dev_ctx) const override {
+    ++run_cnt;
+  }
+};
+
+template <typename T>
+void AssertSameVectorWithoutOrder(const std::vector<T>& expected,
+                                  const std::vector<T>& actual) {
+  ASSERT_EQ(expected.size(), actual.size());
+  std::unordered_set<T> expected_set;
+  for (auto& tmp : expected) {
+    expected_set.insert(tmp);
+  }
+  for (auto& act : actual) {
+    ASSERT_NE(expected_set.end(), expected_set.find(act));
+  }
+}
+
+TEST(OpKernel, all) {
+  auto net = std::make_shared<paddle::framework::PlainNet>();
+  ASSERT_NE(net, nullptr);
+
+  auto op1 = std::make_shared<TestOp>();
+  op1->inputs_ = {"x", "w1", "b1"};
+  op1->outputs_ = {"y"};
+  net->AddOp(op1);
+
+  auto op2 = std::make_shared<TestOp>();
+  op2->inputs_ = {"y", "w2", "b2"};
+  op2->outputs_ = {"z"};
+  net->AddOp(op2);
+
+  net->CompleteAddOp();
+  AssertSameVectorWithoutOrder({"x", "w1", "b1", "w2", "b2"}, net->inputs_);
+  AssertSameVectorWithoutOrder({"y", "z"}, net->outputs_);
+  auto tmp_idx_iter = net->attrs_.find("temporary_index");
+  ASSERT_NE(net->attrs_.end(), tmp_idx_iter);
+  auto& tmp_idx = boost::get<std::vector<int>>(tmp_idx_iter->second);
+  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;
+
+  net->InferShape(scope);
+  net->Run(scope, dev_ctx);
+  ASSERT_EQ(2, infer_shape_cnt);
+  ASSERT_EQ(2, run_cnt);
+
+  ASSERT_THROW(net->AddOp(op2), paddle::framework::EnforceNotMet);
+}

paddle/framework/op_registry.h

 #pragma once
 
 #include <algorithm>
+#include <atomic>
 #include <type_traits>
 #include <unordered_map>
 #include <unordered_set>
@@ -61,7 +62,14 @@ class OpProtoAndCheckerMaker {
   OpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
       : proto_(proto), op_checker_(op_checker) {}
 
-  ~OpProtoAndCheckerMaker() { CheckNoDuplicatedAttrs(); }
+  ~OpProtoAndCheckerMaker() {
+    PADDLE_ENFORCE(validated_, "should call Validate after build");
+  }
+
+  void Validate() {
+    validated_ = true;
+    CheckNoDuplicatedInOutAttrs();
+  }
 
  protected:
   void AddInput(const std::string& name, const std::string& comment,
@@ -163,19 +171,26 @@ Add a mark to which output is temporary is helpful for future optimization.
     }
   }
 
-  void CheckNoDuplicatedAttrs() {
+  void CheckNoDuplicatedInOutAttrs() {
     std::unordered_set<std::string> names;
-    size_t cnt = 0;
+    auto checker = [&](const std::string& name) {
+      PADDLE_ENFORCE(!names.count(name), "[%s] is duplicated", name);
+      names.insert(name);
+    };
     for (auto& attr : proto_->attrs()) {
-      names.insert(attr.name());
-      ++cnt;
+      checker(attr.name());
+    }
+    for (auto& input : proto_->inputs()) {
+      checker(input.name());
+    }
+    for (auto& output : proto_->outputs()) {
+      checker(output.name());
     }
-    PADDLE_ENFORCE(names.size() == cnt,
-                   "Cannot register two attribute in same name!");
   }
 
   OpProto* proto_;
   OpAttrChecker* op_checker_;
+  bool validated_{false};
   bool has_multiple_input_{false};
   bool has_multiple_output_{false};
   bool has_temporary_output_{false};
@@ -190,7 +205,8 @@ class OpRegistry {
     creators()[op_type] = [] { return new OpType; };
     OpProto& op_proto = protos()[op_type];
     OpAttrChecker& op_checker = op_checkers()[op_type];
-    ProtoMakerType(&op_proto, &op_checker);
+    auto maker = ProtoMakerType(&op_proto, &op_checker);
+    maker.Validate();
     *op_proto.mutable_type() = op_type;
     PADDLE_ENFORCE(
         op_proto.IsInitialized(),
@@ -199,27 +215,42 @@ class OpRegistry {
   }
 
   static OperatorPtr CreateOp(const OpDesc& op_desc) {
+    //! Create a OpPtr by type.
     std::string op_type = op_desc.type();
     OperatorPtr op(creators().at(op_type)());
-    op->desc_ = op_desc;
+    //! Fill op's data member. Not use constructor because it will be noising
+    //! for Op developer.
+    const OpProto& op_proto = protos().at(op_type);
+    op->type_ = op_desc.type();
+    // set op's inputs_ from desc.
     op->inputs_.reserve((size_t)op_desc.inputs_size());
     std::copy(op_desc.inputs().begin(), op_desc.inputs().end(),
               std::back_inserter(op->inputs_));
+    // set op's outputs_ from desc.
     op->outputs_.reserve((size_t)op_desc.outputs_size());
     std::copy(op_desc.outputs().begin(), op_desc.outputs().end(),
               std::back_inserter(op->outputs_));
+
+    //! Fill attrs, and validate attrs.
     for (auto& attr : op_desc.attrs()) {
       op->attrs_[attr.name()] = AttrTypeHelper::GetAttrValue(attr);
     }
     op_checkers().at(op_type).Check(op->attrs_);
+
+    //! Convert Temporary variable name to an unique variable name.
+    GenerateTempVariableName(op.get());
+
+    // set argument offsets stored in op.
+    CreateInOutOffsetMap(op, op_proto);
+    //! Other op's custom Init for a complex Op. For simple Op, the Init
+    //! method do nothing.
     op->Init();
     return op;
   }
 
- private:
-  static std::unordered_map<std::string, OpCreator>& creators() {
-    static std::unordered_map<std::string, OpCreator> creators_;
-    return creators_;
+  // init op.in_out_idxs_ to accelerate argument's offset lookup.
+  static void CreateInOutOffsetMap(OperatorPtr op, const OpProto& proto) {
+    op->CreateInOutOffsetMap(proto);
   }
 
   static std::unordered_map<std::string, OpProto>& protos() {
@@ -227,6 +258,23 @@ class OpRegistry {
     return protos_;
   };
 
+ private:
+  static void GenerateTempVariableName(OperatorBase* op) {
+    static std::atomic<size_t> 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<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_;
@@ -241,12 +289,18 @@ class OpRegisterHelper {
   }
 };
 
+/**
+ * check if MACRO is used in GLOBAL NAMESPACE.
+ */
 #define STATIC_ASSERT_GLOBAL_NAMESPACE(uniq_name, msg)                        \
   struct __test_global_namespace_##uniq_name##__ {};                          \
   static_assert(std::is_same<::__test_global_namespace_##uniq_name##__,       \
                              __test_global_namespace_##uniq_name##__>::value, \
                 msg)
 
+/**
+ * Macro to Register Operator.
+ */
 #define REGISTER_OP(__op_type, __op_class, __op_maker_class)                 \
   STATIC_ASSERT_GLOBAL_NAMESPACE(__reg_op__##__op_type,                      \
                                  "REGISTER_OP must be in global namespace"); \
@@ -254,9 +308,12 @@ class OpRegisterHelper {
       __op_register_##__op_type##__(#__op_type);                             \
   int __op_register_##__op_type##_handle__() { return 0; }
 
-#define REGISTER_OP_KERNEL(type, GPU_OR_CPU, PlaceType, KernelType)       \
+/**
+ * Macro to Register OperatorKernel.
+ */
+#define REGISTER_OP_KERNEL(type, DEVICE_TYPE, PlaceType, KernelType)      \
   STATIC_ASSERT_GLOBAL_NAMESPACE(                                         \
-      __reg_op_kernel_##type##_##GPU_OR_CPU##__,                          \
+      __reg_op_kernel_##type##_##DEVICE_TYPE##__,                         \
       "REGISTER_OP_KERNEL must be in global namespace");                  \
   struct __op_kernel_register__##type##__ {                               \
     __op_kernel_register__##type##__() {                                  \
@@ -267,7 +324,7 @@ class OpRegisterHelper {
     }                                                                     \
   };                                                                      \
   static __op_kernel_register__##type##__ __reg_kernel_##type##__;        \
-  int __op_kernel_register_##type##_handle_##GPU_OR_CPU##__() { return 0; }
+  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)
@@ -275,6 +332,10 @@ class OpRegisterHelper {
 #define REGISTER_OP_CPU_KERNEL(type, KernelType) \
   REGISTER_OP_KERNEL(type, CPU, ::paddle::platform::CPUPlace, KernelType)
 
+/**
+ * Macro to mark what Operator and Kernel we will use and tell the compiler to
+ * link them into target.
+ */
 #define USE_OP_WITHOUT_KERNEL(op_type)                      \
   STATIC_ASSERT_GLOBAL_NAMESPACE(                           \
       __use_op_without_kernel_##op_type,                    \
@@ -292,15 +353,16 @@ class OpRegisterHelper {
       __attribute__((unused)) =                                           \
           __op_kernel_register_##op_type##_handle_##DEVICE_TYPE##__()
 
-#ifdef PADDLE_ONLY_CPU
-#define USE_OP(op_type)           \
+// use Operator with only cpu kernel.
+#define USE_OP_CPU(op_type)       \
   USE_OP_WITHOUT_KERNEL(op_type); \
-  USE_OP_KERNEL(op_type, CPU);
+  USE_OP_KERNEL(op_type, CPU)
 
+#ifdef PADDLE_ONLY_CPU
+#define USE_OP(op_type) USE_OP_CPU(op_type)
 #else
 #define USE_OP(op_type) \
-  USE_OP_WITHOUT_KERNEL(op_type); \
-  USE_OP_KERNEL(op_type, CPU);    \
+  USE_OP_CPU(op_type);  \
   USE_OP_KERNEL(op_type, GPU)
 #endif
 

paddle/framework/op_registry_test.cc

 #include "paddle/framework/op_registry.h"
 #include <gtest/gtest.h>
 
+namespace pd = paddle::framework;
+
 namespace paddle {
 namespace framework {
 class CosineOp : public OperatorBase {
@@ -28,8 +30,6 @@ class MyTestOp : public OperatorBase {
   void InferShape(const ScopePtr& scope) const override {}
   void Run(const ScopePtr& scope,
            const platform::DeviceContext& dev_ctx) const override {}
-
- public:
 };
 
 class MyTestOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
@@ -182,3 +182,35 @@ TEST(OpRegistry, CustomChecker) {
   int test_attr = op->GetAttr<int>("test_attr");
   ASSERT_EQ(test_attr, 4);
 }
+
+class TestAttrProtoMaker : public pd::OpProtoAndCheckerMaker {
+ public:
+  TestAttrProtoMaker(pd::OpProto* proto, pd::OpAttrChecker* op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    AddAttr<float>("scale", "scale of test op");
+    AddAttr<float>("scale", "scale of test op");
+  }
+};
+
+TEST(ProtoMaker, DuplicatedAttr) {
+  pd::OpProto op_proto;
+  pd::OpAttrChecker op_checker;
+  auto proto_maker = TestAttrProtoMaker(&op_proto, &op_checker);
+  ASSERT_THROW(proto_maker.Validate(), paddle::framework::EnforceNotMet);
+}
+
+class TestInOutProtoMaker : public pd::OpProtoAndCheckerMaker {
+ public:
+  TestInOutProtoMaker(pd::OpProto* proto, pd::OpAttrChecker* op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    AddInput("input", "input of test op");
+    AddInput("input", "input of test op");
+  }
+};
+
+TEST(ProtoMaker, DuplicatedInOut) {
+  pd::OpProto op_proto;
+  pd::OpAttrChecker op_checker;
+  auto proto_maker = TestInOutProtoMaker(&op_proto, &op_checker);
+  ASSERT_THROW(proto_maker.Validate(), paddle::framework::EnforceNotMet);
+}

paddle/framework/operator.cc

@@ -12,30 +12,86 @@ 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 <algorithm>
+
 #include "paddle/framework/operator.h"
 
 namespace paddle {
 namespace framework {
 
+void OperatorBase::CreateInOutOffsetMap(const OpProto& proto) {
+  PADDLE_ENFORCE(in_out_idxs_.empty(), "duplicate call CreateInOutOffsetMap");
+  for (int i = 0; i < proto.inputs_size(); i++) {
+    const auto& name = proto.inputs()[i].name();
+    in_out_idxs_[name] = i;
+  }
+  for (int i = 0; i < proto.outputs_size(); i++) {
+    const auto& name = proto.outputs()[i].name();
+    in_out_idxs_[name] = i;
+  }
+}
+
+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<std::vector<int>>("input_format");
+    int idx = input_format[it->second];
+    return inputs_.at(idx);
+  }
+}
+
+std::vector<std::string> OperatorBase::Inputs(const std::string& name) const {
+  auto input_format = GetAttr<std::vector<int>>("input_format");
+  auto offset = in_out_idxs_.at(name);
+
+  return std::vector<std::string>{
+      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<std::vector<int>>("output_format");
+    int idx = output_format[it->second];
+    return outputs_.at(idx);
+  }
+}
+
+std::vector<std::string> OperatorBase::Outputs(const std::string& name) const {
+  auto output_format = GetAttr<std::vector<int>>("output_format");
+  auto offset = in_out_idxs_.at(name);
+
+  return std::vector<std::string>{
+      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 = " << desc_.type() << "\n";
-  ss << "inputs = [";
-  for (auto& ipt : inputs_) {
-    ss << ipt << ", ";
-  }
-  ss << "]\n";
-  ss << "outputs = [";
-  for (auto& opt : outputs_) {
-    ss << opt << ", ";
-  }
-  ss << "]\n";
-  ss << "attr_keys = [";
-  for (auto& attr : attrs_) {
-    ss << attr.first << ", ";
-  }
-  ss << "]\n";
+  ss << "Op(" << type_ << "), inputs:(";
+  for (size_t i = 0; i < inputs_.size(); ++i) {
+    ss << inputs_[i];
+    if (i != inputs_.size() - 1) {
+      ss << ", ";
+    }
+  }
+  ss << "), outputs:(";
+  for (size_t i = 0; i < outputs_.size(); ++i) {
+    ss << outputs_[i];
+    if (i != outputs_.size() - 1) {
+      ss << ", ";
+    }
+  }
+  ss << ").";
   return ss.str();
 }
 

paddle/framework/operator.h

@@ -14,18 +14,20 @@ limitations under the License. */
 
 #pragma once
 
-#include <paddle/framework/attr_checker.h>
-#include <paddle/framework/op_desc.pb.h>
-#include <paddle/framework/scope.h>
-#include <paddle/framework/tensor.h>
-#include <paddle/platform/device_context.h>
-#include <paddle/platform/place.h>
-#include <paddle/utils/Error.h>
 #include <boost/variant.hpp>
 #include <string>
 #include <unordered_map>
 #include <vector>
 
+#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<OperatorBase>;
  */
 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 <typename T>
@@ -62,27 +71,32 @@ class OperatorBase {
   virtual void Run(const ScopePtr& scope,
                    const platform::DeviceContext& dev_ctx) const = 0;
 
- protected:
-  std::string Type() const { return desc_.type(); }
+  // 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<std::string> 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<std::string> Outputs(const std::string& name) const;
+
+  // init in_out_idxs_ to accelerate argument's offset lookup.
+  void CreateInOutOffsetMap(const OpProto& proto);
 
  public:
-  OpDesc desc_;
+  std::string type_;
   std::vector<std::string> inputs_;
   std::vector<std::string> outputs_;
   AttributeMap attrs_;
+  // store the arguments' offset described in op_desc.
+  std::unordered_map<std::string, int> in_out_idxs_;
 };
 
-class OpKernel {
- public:
-  /**
-   * KernelContext is the only parameter of Kernel Run function.
-   * Run will get input/output variables, state such as momentum and
-   * device resource such as CUDA stream, cublas handle, etc. from
-   * KernelContext. User should construct it before run the Operator.
-   */
-  class KernelContext {
+class KernelContext {
  public:
-    KernelContext(const OperatorBase* op, const ScopePtr& scope,
+  KernelContext(const OperatorBase* op, const std::shared_ptr<Scope>& scope,
                 const platform::DeviceContext& device_context)
       : op_(*op), scope_(scope), device_context_(device_context) {}
 
@@ -94,11 +108,45 @@ class OpKernel {
     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<const Variable*> Inputs(const std::string& name) const {
+    auto names = op_.Inputs(name);
+    std::vector<const Variable*> res;
+    std::transform(
+        names.begin(), names.end(), res.begin(),
+        [this](const std::string& name) { return scope_->GetVariable(name); });
+    return res;
+  }
+
+  const std::vector<const Variable*> Outputs(const std::string& name) const {
+    auto names = op_.Outputs(name);
+    std::vector<const Variable*> res;
+    std::transform(
+        names.begin(), names.end(), res.begin(),
+        [this](const std::string& name) { return scope_->GetVariable(name); });
+    return res;
+  }
+
   const OperatorBase& op_;
-    const ScopePtr& scope_;
+  const std::shared_ptr<Scope>& scope_;
   const platform::DeviceContext& device_context_;
-  };
+};
 
+class OpKernel {
+ public:
+  /**
+   * KernelContext is the only parameter of Kernel Run function.
+   * Run will get input/output variables, state such as momentum and
+   * device resource such as CUDA stream, cublas handle, etc. from
+   * KernelContext. User should construct it before run the Operator.
+   */
   virtual void Compute(const KernelContext& context) const = 0;
 
   virtual ~OpKernel() {}
@@ -142,8 +190,8 @@ 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));
+    auto& opKernel = AllOpKernels().at(type_).at(OpKernelKey(dev_ctx));
+    opKernel->Compute(KernelContext(this, scope, dev_ctx));
   }
 
   static std::unordered_map<std::string /* op_type */, OpKernelMap>&
@@ -151,6 +199,7 @@ class OperatorWithKernel : public OperatorBase {
     static std::unordered_map<std::string, OpKernelMap> g_all_op_kernels;
     return g_all_op_kernels;
   }
+
   void InferShape(const std::shared_ptr<Scope>& scope) const final {
     std::vector<const Tensor*> ins;
     VarNamesToTensors(scope, inputs_, &ins);

paddle/framework/operator_test.cc

@@ -19,14 +19,17 @@ limitations under the License. */
 namespace paddle {
 namespace framework {
 
-class OperatorTest : public OperatorBase {
+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,
            const platform::DeviceContext& dev_ctx) const override {
-    float scale = GetAttr<float>("scale");
-    ASSERT_NEAR(scale, 3.14, 1e-5);
+    op_run_num++;
+    ASSERT_EQ((int)inputs_.size(), 1);
+    ASSERT_EQ((int)outputs_.size(), 1);
     ASSERT_EQ(scope->GetVariable(inputs_[0]), nullptr);
     ASSERT_EQ(x, 1);
     ASSERT_NE(scope->GetVariable(outputs_[0]), nullptr);
@@ -36,15 +39,14 @@ class OperatorTest : public OperatorBase {
   float x = 0;
 };
 
-class OperatorTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
+class OpeWithoutKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
  public:
-  OperatorTestProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
+  OpeWithoutKernelTestProtoAndCheckerMaker(OpProto* proto,
+                                           OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("input", "input of test op");
     AddOutput("output", "output of test op");
-    AddAttr<float>("scale", "scale of cosine op")
-        .SetDefault(1.0)
-        .LargerThan(0.0);
+    AddAttr<float>("scale", "scale of cosine op");
     AddComment("This is test op");
   }
 };
@@ -52,8 +54,8 @@ class OperatorTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
 }  // namespace framework
 }  // namespace paddle
 
-REGISTER_OP(test_operator, paddle::framework::OperatorTest,
-            paddle::framework::OperatorTestProtoAndCheckerMaker);
+REGISTER_OP(test_operator, paddle::framework::OpWithoutKernelTest,
+            paddle::framework::OpeWithoutKernelTestProtoAndCheckerMaker);
 
 TEST(OperatorBase, all) {
   paddle::framework::OpDesc op_desc;
@@ -63,18 +65,17 @@ TEST(OperatorBase, all) {
   auto attr = op_desc.mutable_attrs()->Add();
   attr->set_name("scale");
   attr->set_type(paddle::framework::AttrType::FLOAT);
-  float scale = 3.14;
-  attr->set_f(scale);
+  attr->set_f(3.14);
 
   paddle::platform::CPUDeviceContext device_context;
   auto scope = std::make_shared<paddle::framework::Scope>();
 
   paddle::framework::OperatorPtr op =
       paddle::framework::OpRegistry::CreateOp(op_desc);
-  ASSERT_EQ(op->GetAttr<float>("scale"), scale);
   scope->CreateVariable("OUT1");
+  ASSERT_EQ(paddle::framework::op_run_num, 0);
   op->Run(scope, device_context);
-  std::cout << op->DebugString() << std::endl;
+  ASSERT_EQ(paddle::framework::op_run_num, 1);
 }
 
 namespace paddle {
@@ -84,8 +85,8 @@ 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");
+    AddInput("x", "input of test op");
+    AddOutput("y", "output of test op");
     AddAttr<float>("scale", "scale of cosine op")
         .SetDefault(1.0)
         .LargerThan(0.0);
@@ -93,6 +94,8 @@ class OpKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
   }
 };
 
+static int cpu_kernel_run_num = 0;
+
 class OpWithKernelTest : public OperatorWithKernel {
  protected:
   void InferShape(const std::vector<const Tensor*>& inputs,
@@ -101,11 +104,65 @@ class OpWithKernelTest : public OperatorWithKernel {
 
 class CPUKernelTest : public OpKernel {
  public:
-  void Compute(const KernelContext& context) const {
-    float scale = context.op_.GetAttr<float>("scale");
-    ASSERT_NEAR(scale, 3.14, 1e-5);
+  void Compute(const KernelContext& ctx) const {
     std::cout << "this is cpu kernel" << std::endl;
-    std::cout << context.op_.DebugString() << std::endl;
+    std::cout << ctx.op_.DebugString() << std::endl;
+    cpu_kernel_run_num++;
+    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>& scope) const override {}
+  void Run(const std::shared_ptr<Scope>& 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<float>("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");
   }
 };
 
@@ -116,6 +173,7 @@ REGISTER_OP(op_with_kernel, paddle::framework::OpWithKernelTest,
             paddle::framework::OpKernelTestProtoAndCheckerMaker);
 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");
@@ -131,5 +189,51 @@ TEST(OpKernel, all) {
 
   paddle::framework::OperatorPtr 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);
+}
+
+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<Scope>();
+
+  OperatorPtr op(paddle::framework::OpRegistry::CreateOp(op_desc));
   op->Run(scope, cpu_device_context);
 }

paddle/framework/tensor.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/tensor.h>
+
+namespace paddle {
+namespace framework {}
+}  // namespace paddle

paddle/function/RowConvOpGpu.cu

@@ -144,12 +144,15 @@ __global__ void KeRowConvBwWeight(real* dw, const real* x, const real* dy,
       int yoff = start + j;
 
       // transpose
-      sh_x[tidx][tidy] = (xoff < width && yoff < end) ? x[yoff * width + xoff] : 0.0;
-      sh_dy[tidx][tidy + context - 1] = (xoff < width && yoff < end) ? dy[yoff * width + xoff] : 0.0;
+      sh_x[tidx][tidy] = (xoff < width && yoff < end) ?
+      x[yoff * width + xoff] : 0.0;
+      sh_dy[tidx][tidy + context - 1] = (xoff < width && yoff < end) ?
+      dy[yoff * width + xoff] : 0.0;
       __syncthreads();
       if (tidy < (context - 1)) {
         yoff = yoff - context + 1;
-        sh_dy[tidx][tidy] = (xoff < width && yoff >= start) ? dy[yoff * width + xoff] : 0.0;
+        sh_dy[tidx][tidy] = (xoff < width && yoff >= start) ?
+        dy[yoff * width + xoff] : 0.0;
       }
       __syncthreads();
 
@@ -199,11 +202,13 @@ __global__ void KeRowConvBwWeight2(real* dw, const real* x, const real* dy,
       int yoff = start + j;
 
       // transpose
-      sh_x[tidx][tidy] = (xoff < width && yoff < end) ? x[yoff * width + xoff] : 0.0;
+      sh_x[tidx][tidy] = (xoff < width && yoff < end) ?
+      x[yoff * width + xoff] : 0.0;
       __syncthreads();
 
       for (int t = 0; t < context; t++) {
-        sh_dy[tidx][tidy] = (xoff < width && (yoff - t) >= start && yoff - t < end) ? dy[(yoff - t) * width + xoff] : 0.0;
+        sh_dy[tidx][tidy] = (xoff < width && (yoff - t) >= start &&
+        yoff - t < end) ? dy[(yoff - t) * width + xoff] : 0.0;
         __syncthreads();
 
         real val = sh_x[tidy][tidx] * sh_dy[tidy][tidx];

paddle/operators/CMakeLists.txt

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

paddle/operators/add_op.h

@@ -8,10 +8,10 @@ namespace operators {
 template <typename Place>
 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

paddle/pybind/CMakeLists.txt

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

paddle/pybind/pybind.cc

@@ -13,12 +13,18 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include <Python.h>
+#include <paddle/framework/op_registry.h>
 #include <paddle/framework/scope.h>
 #include <pybind11/pybind11.h>
+#include <pybind11/stl.h>
+#include <fstream>
+#include <vector>
 
 namespace py = pybind11;
 namespace pd = paddle::framework;
 
+USE_OP(add_two);
+
 PYBIND11_PLUGIN(core) {
   py::module m("core", "C++ core of Paddle Paddle");
 
@@ -43,5 +49,37 @@ All parameter, weight, gradient are variables in Paddle.
            &pd::Scope::CreateVariable,
            py::return_value_policy::reference);
 
+  //! @note: Be careful! PyBind will return std::string as an unicode, not
+  //! Python str. If you want a str object, you should cast them in Python.
+  m.def("get_all_op_protos", []() -> std::vector<std::string> {
+    auto& protos = pd::OpRegistry::protos();
+    std::vector<std::string> ret_values;
+    for (auto it = protos.begin(); it != protos.end(); ++it) {
+      PADDLE_ENFORCE(it->second.IsInitialized(),
+                     "OpProto must all be initialized");
+      ret_values.emplace_back();
+      PADDLE_ENFORCE(it->second.SerializeToString(&ret_values.back()),
+                     "Serialize OpProto Error. This could be a bug of 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_<pd::OperatorBase, pd::OperatorPtr>(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();
 }

paddle/scripts/docker/build.sh

@@ -155,7 +155,8 @@ RUN apt-get update &&\
     paddle version
 ${DOCKERFILE_CUDNN_DSO}
 ${DOCKERFILE_GPU_ENV}
-
+ADD go/cmd/pserver/pserver /usr/bin/
+ADD go/cmd/master/master /usr/bin/
 # default command shows the paddle version and exit
 CMD ["paddle", "version"]
 EOF

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

paddle/trainer/NewRemoteParameterUpdater.cpp

@@ -28,6 +28,17 @@ NewRemoteParameterUpdater::NewRemoteParameterUpdater(
       newGradients_(nullptr),
       pserverSpec_(pserverSpec) {}
 
+NewRemoteParameterUpdater::NewRemoteParameterUpdater(
+    const OptimizationConfig &config,
+    const std::string pserverSpec,
+    const bool useEtcd)
+    : trainerConfig_(config),
+      parameterClient_(-1),
+      newParameters_(nullptr),
+      newGradients_(nullptr),
+      pserverSpec_(pserverSpec),
+      useEtcd_(useEtcd) {}
+
 void NewRemoteParameterUpdater::init(
     const std::vector<ParameterPtr> &parameters) {
   ParameterUpdater::init(parameters);
@@ -38,8 +49,13 @@ void NewRemoteParameterUpdater::init(
   }
 
   // create parameter server client.
+  if (useEtcd_) {
+    parameterClient_ = paddle_new_etcd_pserver_client(
+        (char *)pserverSpec_.c_str(), FLAGS_trainer_id == 0);
+  } else {
     parameterClient_ = paddle_new_pserver_client((char *)pserverSpec_.c_str(),
                                                  FLAGS_trainer_id == 0);
+  }
 
   // init new parameter and gradient.
   newParameters_ = initNewParameter(PARAMETER_VALUE);

paddle/trainer/NewRemoteParameterUpdater.h

@@ -32,6 +32,9 @@ class NewRemoteParameterUpdater : public ParameterUpdater {
 public:
   NewRemoteParameterUpdater(const OptimizationConfig& config,
                             const std::string pserverSpec);
+  NewRemoteParameterUpdater(const OptimizationConfig& config,
+                            const std::string pserverSpec,
+                            const bool useEtcd);
   ~NewRemoteParameterUpdater() {
     releaseNewParameter(newParameters_);
     releaseNewParameter(newGradients_);
@@ -111,6 +114,8 @@ protected:
   paddle_parameter** newGradients_;
   /// the specification of parameter server "host1:port,host1:port"
   std::string pserverSpec_;
+  /// true if pserverSpec_ is etcd endpoint, else pserverSpec_ is pserver addr
+  bool useEtcd_;
 };
 
 }  // namespace paddle

python/paddle/v2/__init__.py

@@ -20,7 +20,6 @@ import trainer
 import event
 import data_type
 import topology
-import data_feeder
 import networks
 import evaluator
 from . import dataset
@@ -31,7 +30,6 @@ import op
 import pooling
 import inference
 import networks
-import py_paddle.swig_paddle as api
 import minibatch
 import plot
 import image
@@ -47,7 +45,6 @@ __all__ = [
     'data_type',
     'attr',
     'pooling',
-    'data_feeder',
     'dataset',
     'reader',
     'topology',
@@ -61,6 +58,7 @@ __all__ = [
 
 
 def init(**kwargs):
+    import py_paddle.swig_paddle as api
     args = []
     args_dict = {}
     # NOTE: append arguments if they are in ENV

python/paddle/v2/data_feeder.py

@@ -11,7 +11,6 @@
 # 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.
-
 from py_paddle import DataProviderConverter
 import collections
 import paddle.trainer.PyDataProvider2 as pydp2

python/paddle/v2/dataset/common.py

@@ -22,6 +22,8 @@ import importlib
 import paddle.v2.dataset
 import cPickle
 import glob
+import cPickle as pickle
+import random
 
 __all__ = [
     'DATA_HOME', 'download', 'md5file', 'split', 'cluster_files_reader',
@@ -170,8 +172,6 @@ def convert(output_path,
             name_prefix,
             max_lines_to_shuffle=1000):
     import recordio
-    import cPickle as pickle
-    import random
     """
     Convert data from reader to recordio format files.
 
@@ -201,8 +201,10 @@ def convert(output_path,
     def write_data(w, lines):
         random.shuffle(lines)
         for i, d in enumerate(lines):
-            d = pickle.dumps(d, pickle.HIGHEST_PROTOCOL)
-            w[i % num_shards].write(d)
+            # FIXME(Yancey1989):
+            # dumps with protocol: pickle.HIGHEST_PROTOCOL
+            o = pickle.dumps(d)
+            w[i % num_shards].write(o)
 
     w = open_writers()
     lines = []

python/paddle/v2/dataset/mq2007.py

@@ -212,19 +212,19 @@ def gen_pair(querylist, partial_order="full"):
         for j in range(i + 1, len(querylist)):
             query_right = querylist[j]
             if query_left.relevance_score > query_right.relevance_score:
-                labels.append(1)
+                labels.append([1])
                 docpairs.append([
                     np.array(query_left.feature_vector),
                     np.array(query_right.feature_vector)
                 ])
             elif query_left.relevance_score < query_right.relevance_score:
-                labels.append(1)
+                labels.append([1])
                 docpairs.append([
                     np.array(query_right.feature_vector),
                     np.array(query_left.feature_vector)
                 ])
     for label, pair in zip(labels, docpairs):
-        yield label, pair[0], pair[1]
+        yield np.array(label), pair[0], pair[1]
 
 
 def gen_list(querylist):

python/paddle/v2/event.py

@@ -9,8 +9,6 @@ There are:
 * BeginPass
 * EndPass
 """
-import py_paddle.swig_paddle as api
-
 __all__ = [
     'EndIteration', 'BeginIteration', 'BeginPass', 'EndPass', 'TestResult'
 ]
@@ -18,6 +16,7 @@ __all__ = [
 
 class WithMetric(object):
     def __init__(self, evaluator):
+        import py_paddle.swig_paddle as api
         if not isinstance(evaluator, api.Evaluator):
             raise TypeError("Evaluator should be api.Evaluator type")
         self.__evaluator__ = evaluator

python/paddle/v2/framework/create_op_creation_methods.py

+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__()

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

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

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

+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 TestGetAllProtos(unittest.TestCase):
+    def test_all(self):
+        all_protos = creation.get_all_op_protos()
+        self.assertNotEqual(0, len(all_protos))
+
+        for each in all_protos:
+            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()

python/paddle/v2/inference.py

 import numpy
-import py_paddle.swig_paddle as api
 import collections
 import topology
 import minibatch
-from data_feeder import DataFeeder
 
 __all__ = ['infer', 'Inference']
 
@@ -28,6 +26,7 @@ class Inference(object):
     """
 
     def __init__(self, output_layer, parameters):
+        import py_paddle.swig_paddle as api
         topo = topology.Topology(output_layer)
         gm = api.GradientMachine.createFromConfigProto(
             topo.proto(), api.CREATE_MODE_TESTING, [api.PARAMETER_VALUE])
@@ -40,6 +39,7 @@ class Inference(object):
         self.__data_types__ = topo.data_type()
 
     def iter_infer(self, input, feeding=None):
+        from data_feeder import DataFeeder
         feeder = DataFeeder(self.__data_types__, feeding)
         batch_size = len(input)
 

python/paddle/v2/master/client.py

@@ -10,8 +10,9 @@ class client(object):
     client is a client to the master server.
     """
 
-    def __init__(self, addr, buf_size):
-        self.c = lib.paddle_new_master_client(addr, buf_size)
+    def __init__(self, etcd_endpoints, timeout, buf_size):
+        self.c = lib.paddle_new_etcd_master_client(etcd_endpoints, timeout,
+                                                   buf_size)
 
     def close(self):
         lib.paddle_release_master_client(self.c)

python/paddle/v2/optimizer.py

-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
 """
@@ -18,6 +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.
 
@@ -36,23 +35,27 @@ 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):
+    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)
+            self.__opt_conf__, pserver_spec, use_etcd)
 
     def create_updater(self, is_local, num_passes, use_sparse_updater,
-                       pserver_spec):
+                       pserver_spec, use_etcd):
         """
         create proper parameter_updater by configuration.
         :param is_local: create local or remote parameter updater
@@ -78,7 +81,7 @@ class Optimizer(object):
                     num_passes, use_sparse_updater)
             else:
                 parameter_updater = self.__create_new_remote_updater__(
-                    pserver_spec)
+                    pserver_spec, use_etcd)
         return parameter_updater
 
 
@@ -268,6 +271,7 @@ ModelAverage = v1_optimizers.ModelAverage
 L2Regularization = v1_optimizers.L2Regularization
 
 if __name__ == '__main__':
+    import py_paddle.swig_paddle as swig_api
     swig_api.initPaddle('--use_gpu=false')
     for opt in [
             Momentum(), Adam(), Adamax(), AdaGrad(), DecayedAdaGrad(),

python/paddle/v2/parameters.py

 import numpy as np
-import py_paddle.swig_paddle as api
 from paddle.proto.ParameterConfig_pb2 import ParameterConfig
 import paddle.trainer.config_parser as cp
 import struct
@@ -124,6 +123,7 @@ class Parameters(object):
         :return: parameter value
         :rtype: np.ndarray
         """
+        import py_paddle.swig_paddle as api
         shape = self.get_shape(key)
 
         if len(self.__gradient_machines__) == 0:
@@ -223,7 +223,7 @@ class Parameters(object):
         :type gradient_machine: api.GradientMachine
         :return:
         """
-
+        import py_paddle.swig_paddle as api
         if not isinstance(gradient_machine, api.GradientMachine):
             raise ValueError("gradient_machine should be api.GradientMachine")
 
@@ -359,6 +359,7 @@ def __copy_parameter_to_gradient_machine__(gradient_machine, name, arr):
     :return:
     :rtype: api.Parameter
     """
+    import py_paddle.swig_paddle as api
     param = __get_parameter_in_gradient_machine__(gradient_machine, name)
     vec = param.getBuf(api.PARAMETER_VALUE)
     assert isinstance(vec, api.Vector)

python/paddle/v2/trainer.py

@@ -2,12 +2,6 @@
 Module Trainer
 """
 import collections
-import gzip
-import os
-
-import py_paddle.swig_paddle as api
-
-from data_feeder import DataFeeder
 from topology import Topology
 from . import event as v2_event
 from . import optimizer as v2_optimizer
@@ -51,7 +45,8 @@ class SGD(object):
                  update_equation,
                  extra_layers=None,
                  is_local=True,
-                 pserver_spec=None):
+                 pserver_spec=None,
+                 use_etcd=True):
 
         if not isinstance(parameters, v2_parameters.Parameters):
             raise TypeError('parameters should be parameters')
@@ -59,6 +54,7 @@ class SGD(object):
         if not isinstance(update_equation, v2_optimizer.Optimizer):
             raise TypeError("update equation parameter must be "
                             "paddle.v2.optimizer.Optimizer")
+        import py_paddle.swig_paddle as api
         topology = Topology(cost, extra_layers=extra_layers)
         self.__optimizer__ = update_equation
         self.__topology__ = topology
@@ -66,6 +62,7 @@ class SGD(object):
         self.__topology_in_proto__ = topology.proto()
         self.__is_local__ = is_local
         self.__pserver_spec__ = pserver_spec
+        self.__use_etcd__ = use_etcd
 
         self.__use_sparse_updater__ = self.__topology__.use_sparse_updater()
         # # In local mode, disable sparse_remote_update.
@@ -124,13 +121,15 @@ class SGD(object):
         :type feeding: dict|list
         :return:
         """
+        import py_paddle.swig_paddle as api
+        from data_feeder import DataFeeder
         if event_handler is None:
             event_handler = default_event_handler
         __check_train_args__(**locals())
 
         self.__parameter_updater__ = self.__optimizer__.create_updater(
             self.__is_local__, num_passes, self.__use_sparse_updater__,
-            self.__pserver_spec__)
+            self.__pserver_spec__, self.__use_etcd__)
         self.__parameter_updater__.init(self.__gradient_machine__)
 
         self.__gradient_machine__.start()
@@ -187,6 +186,8 @@ class SGD(object):
         :type feeding: dict
         :return:
         """
+        import py_paddle.swig_paddle as api
+        from data_feeder import DataFeeder
         feeder = DataFeeder(self.__data_types__, feeding)
         evaluator = self.__gradient_machine__.makeEvaluator()
         out_args = api.Arguments.createArguments(0)

python/setup.py.in

@@ -19,7 +19,8 @@ setup_requires=["requests",
                 "recordio",
                 "matplotlib",
                 "rarfile",
-                "scipy>=0.19.0"]
+                "scipy>=0.19.0",
+                "nltk"]
 
 if '${CMAKE_SYSTEM_PROCESSOR}' not in ['arm', 'armv7-a', 'aarch64']:
     setup_requires+=["opencv-python"]