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

cmake/generic.cmake

@@ -192,9 +192,9 @@ function(cc_test TARGET_NAME)
     set(multiValueArgs SRCS DEPS)
     cmake_parse_arguments(cc_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
     add_executable(${TARGET_NAME} ${cc_test_SRCS})
-    target_link_libraries(${TARGET_NAME} ${cc_test_DEPS} gtest gtest_main)
+    target_link_libraries(${TARGET_NAME} ${cc_test_DEPS} gtest gtest_main -lstdc++ -lm)
     add_dependencies(${TARGET_NAME} ${cc_test_DEPS} gtest gtest_main)
-    add_test(${TARGET_NAME} ${TARGET_NAME})
+    add_test(NAME ${TARGET_NAME} COMMAND ${TARGET_NAME} WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
   endif()
 endfunction(cc_test)
 
@@ -281,10 +281,11 @@ function(go_library TARGET_NAME)
 
   file(GLOB GO_SOURCE RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "*.go")
   string(REPLACE "${PADDLE_GO_PATH}/" "" CMAKE_CURRENT_SOURCE_REL_DIR ${CMAKE_CURRENT_SOURCE_DIR})
+  # FIXME: link path
   add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
     COMMAND rm "${${TARGET_NAME}_LIB_PATH}"
     # Golang build source code
-    COMMAND env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build ${BUILD_MODE}
+    COMMAND env LIBRARY_PATH=${CMAKE_BINARY_DIR}/go/pserver/client/c/:$ENV{LIBRARY_PATH} GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build ${BUILD_MODE}
     -o "${${TARGET_NAME}_LIB_PATH}"
     "./${CMAKE_CURRENT_SOURCE_REL_DIR}/${GO_SOURCE}"
     # must run under GOPATH
@@ -299,11 +300,13 @@ function(go_binary TARGET_NAME)
   cmake_parse_arguments(go_binary "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
   string(REPLACE "${PADDLE_GO_PATH}/" "" CMAKE_CURRENT_SOURCE_REL_DIR ${CMAKE_CURRENT_SOURCE_DIR})
 
+  # FIXME: link path
   add_custom_command(OUTPUT ${TARGET_NAME}_timestamp
-    COMMAND env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build
+      COMMAND env LIBRARY_PATH=${CMAKE_BINARY_DIR}/go/pserver/client/c/:$ENV{LIBRARY_PATH}
+      GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build
     -o "${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME}"
     "./${CMAKE_CURRENT_SOURCE_REL_DIR}/${go_binary_SRCS}"
-  WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go")
+    WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go")
   # TODO: don't know what ${TARGET_NAME}_link does
   add_custom_target(${TARGET_NAME} ALL DEPENDS go_vendor ${TARGET_NAME}_timestamp ${go_binary_DEPS})
   install(PROGRAMS ${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME} DESTINATION bin)

go/cmd/master/CMakeLists.txt

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

go/pserver/client/c/CMakeLists.txt

@@ -2,5 +2,5 @@ cc_library(paddle_go_optimizer DEPS paddle_optimizer paddle_proto glog gflags pr
 target_link_libraries(paddle_go_optimizer stdc++ m)
 go_library(paddle_pserver_cclient STATIC DEPS paddle_go_optimizer)
 if(WITH_TESTING)
-  add_subdirectory(test)
+    add_subdirectory(test)
 endif()

paddle/api/CMakeLists.txt

@@ -66,6 +66,7 @@ SWIG_LINK_LIBRARIES(swig_paddle
     paddle_trainer_lib
     paddle_network
     paddle_parameter
+    paddle_optimizer
     paddle_math
     paddle_utils
     paddle_proto

paddle/gserver/layers/AverageLayer.h

@@ -25,6 +25,10 @@ namespace paddle {
  * If SequenceLevel = kNonSeq:
  *    Output: output size is the number of input sequences (NOT input instances)
  *    output[i] = average_{for each instance in this sequence}{input[i]}
+ *    If stride_ > 0:
+ *      Output: a shorten sequence. Stride is the step size by which we slide a
+ *              window upon the input sequence, and the average pooling
+ *              operation is then applied to each interval independently.
  * If SequenceLevel = kSeq:
  *    Check input sequence must has sub-sequence
  *    Output: output size is the number of input sub-sequences

paddle/gserver/layers/CrossChannelNormLayer.cpp

@@ -36,6 +36,16 @@ MatrixPtr CrossChannelNormLayer::createSpatialMatrix(MatrixPtr data,
       data->getData() + iter * spatialDim, 1, spatialDim, false, useGpu_);
 }
 
+bool CrossChannelNormLayer::init(const LayerMap& layerMap,
+                                 const ParameterMap& parameterMap) {
+  Layer::init(layerMap, parameterMap);
+  CHECK(parameters_[0]);
+  const NormConfig& conf = config_.inputs(0).norm_conf();
+  channels_ = conf.channels();
+  scale_.reset(new Weight(channels_, 1, parameters_[0]));
+  return true;
+}
+
 void CrossChannelNormLayer::forward(PassType passType) {
   Layer::forward(passType);
   MatrixPtr inV = getInputValue(0);
@@ -51,9 +61,7 @@ void CrossChannelNormLayer::forward(PassType passType) {
   Matrix::resizeOrCreate(dataBuffer_, batchSize, dataDim, false, useGpu_);
   Matrix::resizeOrCreate(spatialBuffer_, 1, spatialDim, false, useGpu_);
   Matrix::resizeOrCreate(normBuffer_, batchSize, spatialDim, false, useGpu_);
-  normBuffer_->zeroMem();
-  // add eps to avoid overflow
-  normBuffer_->addScalar(*normBuffer_, 1e-6);
+
   inV->square2(*dataBuffer_);
   for (size_t i = 0; i < batchSize; i++) {
     const MatrixPtr inVTmp = createSampleMatrix(inV, i, spatialDim);
@@ -63,6 +71,8 @@ void CrossChannelNormLayer::forward(PassType passType) {
 
     // compute norm.
     spatialBuffer_->sumCols(*dataTmp, 1, 0);
+    // add eps to avoid overflow
+    spatialBuffer_->add(1e-6);
     spatialBuffer_->sqrt2(*spatialBuffer_);
     normTmp->copyFrom(*spatialBuffer_);
     outVTmp->copyFrom(*inVTmp);
@@ -82,6 +92,9 @@ void CrossChannelNormLayer::backward(const UpdateCallback& callback) {
   size_t dataDim = inG->getWidth();
   size_t spatialDim = dataDim / channels_;
 
+  MatrixPtr inGBuffer;
+  Matrix::resizeOrCreate(inGBuffer, channels_, spatialDim, false, useGpu_);
+
   dataBuffer_->dotMul(*outG, *outV);
   Matrix::resizeOrCreate(scaleDiff_, channels_, 1, false, useGpu_);
   Matrix::resizeOrCreate(channelBuffer_, channels_, 1, false, useGpu_);
@@ -100,22 +113,24 @@ void CrossChannelNormLayer::backward(const UpdateCallback& callback) {
     scaleDiff_->add(*channelBuffer_, 1.);
 
     sampleBuffer_->dotMul(*inVTmp, *outGTmp);
-    spatialBuffer_->sumCols(*sampleBuffer_, 1., 1.);
+    spatialBuffer_->sumCols(*sampleBuffer_, 1., 0.);
     // scale the grad
-    inGTmp->copyFrom(*inVTmp);
-    inGTmp->mulRowVector(*spatialBuffer_);
+    inGBuffer->copyFrom(*inVTmp);
+    inGBuffer->mulRowVector(*spatialBuffer_);
     // divide by square of norm
     spatialBuffer_->dotMul(*normTmp, *normTmp);
-    inGTmp->divRowVector(*spatialBuffer_);
+    inGBuffer->divRowVector(*spatialBuffer_);
     // subtract
-    inGTmp->add(*outGTmp, -1, 1);
+    inGBuffer->add(*outGTmp, -1, 1);
     // divide by norm
-    inGTmp->divRowVector(*normTmp);
+    inGBuffer->divRowVector(*normTmp);
     // scale the diff
-    inGTmp->mulColVector(*scale_->getW());
+    inGBuffer->mulColVector(*scale_->getW());
+
+    inGTmp->add(*inGBuffer);
   }
   // updata scale
-  if (scale_->getWGrad()) scale_->getWGrad()->copyFrom(*scaleDiff_);
+  if (scale_->getWGrad()) scale_->getWGrad()->add(*scaleDiff_);
   scale_->getParameterPtr()->incUpdate(callback);
 }
 

paddle/gserver/layers/MaxLayer.h

@@ -26,6 +26,10 @@ namespace paddle {
  * If SequenceLevel = kNonSeq:
  *    Output: output size is the number of input sequences (NOT input instances)
  *    output[i] = max_{for each instance in this sequence}{input[i]}
+ *    If stride_ > 0:
+ *      Output: a shorten sequence. Stride is the step size by which we slide a
+ *              window upon the input sequence, and the max pooling operation is
+ *              then applied to each interval independently.
  * If SequenceLevel = kSeq:
  *    Check input sequence must has sub-sequence
  *    Output: output size is the number of input sub-sequences

paddle/gserver/layers/NormLayer.cpp

@@ -56,14 +56,4 @@ bool ResponseNormLayer::init(const LayerMap& layerMap,
   return true;
 }
 
-bool CrossChannelNormLayer::init(const LayerMap& layerMap,
-                                 const ParameterMap& parameterMap) {
-  Layer::init(layerMap, parameterMap);
-  CHECK(parameters_[0]);
-  const NormConfig& conf = config_.inputs(0).norm_conf();
-  channels_ = conf.channels();
-  scale_.reset(new Weight(channels_, 1, parameters_[0]));
-  return true;
-}
-
 }  // namespace paddle

paddle/gserver/layers/SequenceLastInstanceLayer.cpp

@@ -26,10 +26,9 @@ namespace paddle {
  * If SequenceLevel = kNonseq:
  *   Output: a sequence containing only the last instance of the input sequence
  *   If stride_ > 0:
- *      Output: a shorten sequence. The operation of getting last instance of a
- *              sequence is independently performed on every slice of the input
- *              sequence, which is obtained by sliding a window with the window
- *              size set to stride_.
+ *      Output: a shorten sequence. Stride is the step size by which we slide a
+ *              window upon the input sequence, and getting last instance
+ *              operation is then applied to each interval independently.
  * If SequenceLevel = kSeq:
  *   Check input sequence must has sub-sequence
  *   Output: a sequence containing only the last instance of each sub-sequence
@@ -73,8 +72,7 @@ bool SequenceLastInstanceLayer::init(const LayerMap& layerMap,
 void SequenceLastInstanceLayer::forward(PassType passType) {
   SequencePoolLayer::forward(passType);
 
-  auto starts = (stride_ > 0) ? stridePositions_->getData()
-                              : startPositions_->getData(false);
+  auto starts = startPositions_->getData(false);
   MatrixPtr inputValue = getInputValue(0);
   MatrixPtr outputValue = getOutputValue();
 

paddle/gserver/layers/SequencePoolLayer.cpp

@@ -72,9 +72,8 @@ void SequencePoolLayer::forward(PassType passType) {
   if (stride_ > 0) {
     CHECK_EQ(input.hasSubseq(), 0UL)
         << "sequence stride pooling is invalid for hasSubseq now";
-    output_.poolSequenceWithStride(
-        input, stride_, &stridePositions_, reversed_);
-    newBatchSize_ = stridePositions_->getSize() - 1;
+    output_.poolSequenceWithStride(input, stride_, &startPositions_, reversed_);
+    newBatchSize_ = startPositions_->getSize() - 1;
   }
 
   resetOutput(newBatchSize_, dim);

paddle/gserver/layers/SequencePoolLayer.h

@@ -28,8 +28,9 @@ namespace paddle {
  * sequence}{input[i]}
  *    If stride_ > 0:
  *        Check input sequence must not have sub-sequence
- *        Output: a shorten sequence, pooling is performed upon a small local
- *                area
+ *        Output: a shorten sequence. Stride is the step size by which we slide
+ *                a window upon the input sequence, and the pooling operation
+ *                is then applied to each interval independently.
  * If SequenceLevel = kSeq:
  *    Check input sequence must has sub-sequence
  *    Output: output size is the number of input sub-sequences
@@ -47,8 +48,6 @@ protected:
   size_t newBatchSize_;
   ICpuGpuVectorPtr startPositions_;
   int stride_;
-  // Store the start position of each window.
-  IVectorPtr stridePositions_;
   // Whether the input sequence is reversed or not.
   bool reversed_ = false;
 

paddle/gserver/tests/LayerGradUtil.cpp

@@ -465,7 +465,6 @@ void initTestLayer(TestConfig testConf,
                            ParameterConfig paraConfig) {
     paraConfig.set_name(paraName);
     paraConfig.set_size(paraSize);
-    paraConfig.set_initial_std(1);
     paraConfig.set_is_static(isStatic);
     auto para =
         std::make_shared<Parameter>(paraConfig, FLAGS_use_gpu, initialize);
@@ -499,6 +498,9 @@ void initTestLayer(TestConfig testConf,
         paraConfig.add_dims((*layerMap)[input.input_layer_name()]->getSize());
         paraConfig.add_dims(testConf.layerConfig.size());
       }
+      CHECK_GE(testConf.paramInitialStd, 0);
+      paraConfig.set_initial_mean(testConf.paramInitialMean);
+      paraConfig.set_initial_std(testConf.paramInitialStd);
       initParameter(paraName, paraSize, inputDef.isStatic, false, paraConfig);
     }
   }

paddle/gserver/tests/LayerGradUtil.h

@@ -125,12 +125,16 @@ struct TestConfig {
   LayerConfig layerConfig;
   std::vector<InputDef> inputDefs;
   size_t biasSize;
+  real paramInitialMean;
+  real paramInitialStd;
   bool testAccumulate;
   bool testState;
   bool staticBias;
   bool testBatchState;
   TestConfig()
       : biasSize(0),
+        paramInitialMean(0.0),
+        paramInitialStd(1.0),
         testAccumulate(true),
         testState(false),
         staticBias(false),

paddle/gserver/tests/test_LayerGrad.cpp

@@ -845,8 +845,12 @@ void testDegradeLayer(bool hasSubseq,
 
 TEST(Layer, MaxLayer) {
   testDegradeLayer(false, "max", "non-seq", -1);  // seq max to non-seq
-  testDegradeLayer(true, "max", "non-seq", -1);   // hasSubseq max to non-seq
-  testDegradeLayer(true, "max", "seq", -1);       // hasSubseq max to seq
+  testDegradeLayer(false,
+                   "max",
+                   "non-seq",
+                   5);  // seq max to a shorten seq, stride window = 5
+  testDegradeLayer(true, "max", "non-seq", -1);  // hasSubseq max to non-seq
+  testDegradeLayer(true, "max", "seq", -1);      // hasSubseq max to seq
 }
 
 TEST(Layer, SequenceLastInstanceLayer) {
@@ -868,6 +872,10 @@ TEST(Layer, SequenceLastInstanceLayer) {
 
 TEST(Layer, AverageLayer) {
   testDegradeLayer(false, "average", "non-seq", -1);  // seq average to non-seq
+  testDegradeLayer(false,
+                   "average",
+                   "non-seq",
+                   5);  // seq average to a shorten seq, stride window = 5
   testDegradeLayer(
       true, "average", "non-seq", -1);           // hasSubseq average to non-seq
   testDegradeLayer(true, "average", "seq", -1);  // hasSubseq average to seq
@@ -1661,6 +1669,8 @@ TEST(Layer, PadLayer) {
 
 TEST(Layer, CrossChannelNormLayer) {
   TestConfig config;
+  config.paramInitialMean = 1.;
+  config.paramInitialStd = 0.;
   config.layerConfig.set_type("norm");
   config.layerConfig.set_size(100);
   LayerInputConfig* input = config.layerConfig.add_inputs();
@@ -1674,7 +1684,7 @@ TEST(Layer, CrossChannelNormLayer) {
   config.inputDefs.push_back({INPUT_DATA, "layer_0", 100, 10});
 
   for (auto useGpu : {false, true}) {
-    testLayerGrad(config, "cross-channel-norm", 10, false, useGpu, false, 5);
+    testLayerGrad(config, "cross-channel-norm", 10, false, useGpu, false);
   }
 }
 

paddle/parameter/Argument.cpp

@@ -561,7 +561,7 @@ void Argument::degradeSequence(const Argument& input) {
 
 void Argument::poolSequenceWithStride(const Argument& input,
                                       size_t stride,
-                                      IVectorPtr* stridePostions,
+                                      ICpuGpuVectorPtr* stridePostions,
                                       bool reversed) {
   // If input.sequenceStartPositions = [0, 9, 14, 17, 30] and stride = 5,
   // then sequenceStartPositions = [0, 2, 3, 4, 7].
@@ -598,8 +598,8 @@ void Argument::poolSequenceWithStride(const Argument& input,
   stridePos.emplace_back(starts[numSequences]);
   int size = stridePos.size();
   CHECK_EQ(size - 1, tgtBuf[numSequences]);
-  IVector::resizeOrCreate(*stridePostions, size, false);
-  (*stridePostions)->copyFrom(stridePos.data(), size);
+  ICpuGpuVector::resizeOrCreate(*stridePostions, size, false);
+  (*stridePostions)->getMutableVector(false)->copyFrom(stridePos.data(), size);
 }
 
 void Argument::getValueString(

paddle/parameter/Argument.h

@@ -299,7 +299,7 @@ struct Argument {
    */
   void poolSequenceWithStride(const Argument& input,
                               size_t stride,
-                              IVectorPtr* stridePositions,
+                              ICpuGpuVectorPtr* stridePositions,
                               bool reversed = false);
   /**
    * @brief getValueString will return the argument's output in string. There

paddle/parameter/tests/test_argument.cpp

@@ -31,7 +31,7 @@ TEST(Argument, poolSequenceWithStride) {
   int strideResultReversed[] = {0, 4, 9, 14, 17, 20, 25, 30};
 
   for (auto reversed : {false, true}) {
-    IVectorPtr stridePositions;
+    ICpuGpuVectorPtr stridePositions;
     output.poolSequenceWithStride(
         input, 5 /* stride */, &stridePositions, reversed);
 
@@ -45,7 +45,7 @@ TEST(Argument, poolSequenceWithStride) {
     CHECK_EQ(stridePositions->getSize(), 8UL);
     auto result = reversed ? strideResultReversed : strideResult;
     for (int i = 0; i < 8; i++) {
-      CHECK_EQ(stridePositions->getData()[i], result[i]);
+      CHECK_EQ(stridePositions->getData(false)[i], result[i]);
     }
   }
 }

paddle/pserver/LightNetwork.cpp

@@ -142,7 +142,7 @@ SocketServer::SocketServer(const std::string &addr, int port, int rdmaCpu)
   }
 
   /// trigger to initialize RDMA lib
-  PCHECK(RdmaClientDaemons::get()) << "initilizate RDMA failed\n";
+  CHECK(RdmaClientDaemons::get()) << "initilizate RDMA failed\n";
 }
 
 SocketServer::~SocketServer() {
@@ -168,7 +168,7 @@ void SocketServer::tcpServer() {
 
   /// First call to socket() function
   socket_ = socket(AF_INET, SOCK_STREAM, 0);
-  PCHECK(socket_ >= 0) << "ERROR opening socket";
+  CHECK(socket_ >= 0) << "ERROR opening socket";
 
   /// Initialize socket structure
   bzero((char *)&serv_addr, sizeof(serv_addr));
@@ -176,7 +176,7 @@ void SocketServer::tcpServer() {
   serv_addr.sin_port = htons(port_);
   if (!addr_.empty()) {
     server = gethostbyname(addr_.c_str());
-    PCHECK(server) << "ERROR, no such host: " << addr_;
+    CHECK(server) << "ERROR, no such host: " << addr_;
     bcopy((char *)server->h_addr,
           (char *)&serv_addr.sin_addr.s_addr,
           server->h_length);
@@ -187,7 +187,7 @@ void SocketServer::tcpServer() {
   setOption(socket_);
 
   /// Now bind the host address using bind() call.
-  PCHECK(bind(socket_, (struct sockaddr *)&serv_addr, sizeof(serv_addr)) >= 0)
+  CHECK(bind(socket_, (struct sockaddr *)&serv_addr, sizeof(serv_addr)) >= 0)
       << "ERROR on binding " << addr_;
 
   /// Now start listening for the clients, here process will
@@ -201,7 +201,7 @@ void SocketServer::tcpServer() {
     if (stopping_) {
       break;
     }
-    PCHECK(newsockfd >= 0) << "ERROR on accept";
+    CHECK(newsockfd >= 0) << "ERROR on accept";
     constexpr int kPeerNameLen = 128;
     char peerName[kPeerNameLen];
     CHECK(inet_ntop(AF_INET, &cli_addr.sin_addr, peerName, kPeerNameLen));
@@ -227,14 +227,14 @@ void SocketServer::rdmaServer() {
 
   /// First call to socket() function
   rdmaSocket_ = rdma::ssocket(rdmaCpu_);
-  PCHECK(rdmaSocket_) << "ERROR opening RDMA socket";
+  CHECK(rdmaSocket_) << "ERROR opening RDMA socket";
 
-  PCHECK(rdma::bind(rdmaSocket_, rdmaUri_.c_str()) == 0)
+  CHECK(rdma::bind(rdmaSocket_, rdmaUri_.c_str()) == 0)
       << "ERROR bind RDMA socket";
 
   /// Now start listening for the clients, here process will
   /// go in sleep mode and will wait for the incoming connection
-  PCHECK(rdma::listen(rdmaSocket_) == 0) << "ERROR listen RDMA socket";
+  CHECK(rdma::listen(rdmaSocket_) == 0) << "ERROR listen RDMA socket";
 
   while (true) {
     /// Accept actual connection from the client
@@ -242,7 +242,7 @@ void SocketServer::rdmaServer() {
     if (stopping_) {
       break;
     }
-    PCHECK(newsock) << "ERROR on accept";
+    CHECK(newsock) << "ERROR on accept";
 
     constexpr int kPeerNameLen = 128;
     char peerName[kPeerNameLen];
@@ -290,7 +290,7 @@ RdmaClientDaemons::RdmaClientDaemons() {
     onlineCpus_ = rdma::numCpus();
     for (auto i = 0; i < onlineCpus_; i++) {
       socket = rdma::csocket(i);
-      PCHECK(socket) << "ERROR open client socket daemon";
+      CHECK(socket) << "ERROR open client socket daemon";
 
       rdmaClientSocket_.push_back(socket);
     }
@@ -355,7 +355,7 @@ void SocketClient::TcpClient(const std::string &serverAddr, int serverPort) {
 
   /// Create a socket point
   int sockfd = socket(AF_INET, SOCK_STREAM, 0);
-  PCHECK(sockfd >= 0) << "ERROR opening socket";
+  CHECK(sockfd >= 0) << "ERROR opening socket";
 
 #if defined(__OSX__) || defined(__APPLE__)
   server = getipnodebyname(serverAddr.c_str(), AF_INET, AI_DEFAULT, &errRet);
@@ -396,8 +396,8 @@ void SocketClient::TcpClient(const std::string &serverAddr, int serverPort) {
       }
       std::this_thread::sleep_for(std::chrono::seconds(1));
     } else {
-      PCHECK(errno != 0) << "ERROR connecting to " << serverAddr << ":"
-                         << serverPort << "errorno: " << errno;
+      CHECK(errno != 0) << "ERROR connecting to " << serverAddr << ":"
+                        << serverPort << "errorno: " << errno;
     }
   } while (errno == ECONNREFUSED);
 
@@ -426,7 +426,7 @@ void SocketClient::RdmaClient(const std::string &serverAddr, int serverPort) {
 
   /// connect to server with socket daemon
   sock = rdma::connect(socketDaemon_, rdmaUri.c_str());
-  PCHECK(sock) << "ERROR connect to server" << rdmaUri;
+  CHECK(sock) << "ERROR connect to server" << rdmaUri;
 
   std::vector<std::string> seg;
   str::split(rdmaUri, '/', &seg);

paddle/pserver/SocketChannel.cpp

@@ -51,7 +51,7 @@ size_t SocketChannel::read(void* buf, size_t size) {
     else
       len = rdma::read(rdmaSocket_, (char*)buf + total, size - total);
 
-    PCHECK(len >= 0) << " peer=" << peerName_;
+    CHECK(len >= 0) << " peer=" << peerName_;
     if (len <= 0) {
       return total;
     }
@@ -69,7 +69,7 @@ size_t SocketChannel::write(const void* buf, size_t size) {
     else
       len = rdma::write(rdmaSocket_, (char*)buf + total, size - total);
 
-    PCHECK(len >= 0) << " peer=" << peerName_;
+    CHECK(len >= 0) << " peer=" << peerName_;
     if (len <= 0) {
       return total;
     }
@@ -98,10 +98,10 @@ static size_t readwritev(IOFunc iofunc,
   while (size < total) {
     ssize_t len =
         iofunc(socket, &iovs[curIov], std::min(iovcnt - curIov, maxiovs));
-    PCHECK(len > 0) << " peer=" << peerName << " curIov=" << curIov
-                    << " iovCnt=" << iovcnt
-                    << " iovs[curIov].base=" << iovs[curIov].iov_base
-                    << " iovs[curIov].iov_len=" << iovs[curIov].iov_len;
+    CHECK(len > 0) << " peer=" << peerName << " curIov=" << curIov
+                   << " iovCnt=" << iovcnt
+                   << " iovs[curIov].base=" << iovs[curIov].iov_base
+                   << " iovs[curIov].iov_len=" << iovs[curIov].iov_len;
     size += len;
 
     /// restore iovs[curIov] to the original value
@@ -183,7 +183,7 @@ void SocketChannel::writeMessage(const std::vector<struct iovec>& userIovs) {
     header.totalLength += iov.iov_len;
   }
 
-  PCHECK(writev(iovs) == (size_t)header.totalLength);
+  CHECK(writev(iovs) == (size_t)header.totalLength);
 }
 
 std::unique_ptr<MsgReader> SocketChannel::readMessage() {
@@ -194,7 +194,7 @@ std::unique_ptr<MsgReader> SocketChannel::readMessage() {
     return nullptr;
   }
 
-  PCHECK(len == sizeof(header));
+  CHECK(len == sizeof(header));
 
   std::unique_ptr<MsgReader> msgReader(new MsgReader(this, header.numIovs));
 
@@ -209,7 +209,7 @@ std::unique_ptr<MsgReader> SocketChannel::readMessage() {
 MsgReader::MsgReader(SocketChannel* channel, size_t numBlocks)
     : channel_(channel), blockLengths_(numBlocks), currentBlockIndex_(0) {
   size_t size = numBlocks * sizeof(blockLengths_[0]);
-  PCHECK(channel_->read(&blockLengths_[0], size) == size);
+  CHECK(channel_->read(&blockLengths_[0], size) == size);
 }
 
 void MsgReader::readBlocks(const std::vector<void*>& bufs) {
@@ -223,12 +223,12 @@ void MsgReader::readBlocks(const std::vector<void*>& bufs) {
     ++currentBlockIndex_;
   }
 
-  PCHECK(channel_->readv(&iovs) == totalLength);
+  CHECK(channel_->readv(&iovs) == totalLength);
 }
 
 void MsgReader::readNextBlock(void* buf) {
   CHECK_LT(currentBlockIndex_, blockLengths_.size());
-  PCHECK(channel_->read(buf, getNextBlockLength()) == getNextBlockLength());
+  CHECK(channel_->read(buf, getNextBlockLength()) == getNextBlockLength());
   ++currentBlockIndex_;
 }
 

paddle/pserver/test/SocketTest.cpp

@@ -113,7 +113,7 @@ void SocketServer::run() {
 
   /* First call to socket() function */
   socket_ = socket(AF_INET, SOCK_STREAM, 0);
-  PCHECK(socket_ >= 0) << "ERROR opening socket";
+  CHECK(socket_ >= 0) << "ERROR opening socket";
 
   /* Initialize socket structure */
   bzero((char*)&serv_addr, sizeof(serv_addr));
@@ -122,7 +122,7 @@ void SocketServer::run() {
   serv_addr.sin_port = htons(port_);
 
   /* Now bind the host address using bind() call.*/
-  PCHECK(bind(socket_, (struct sockaddr*)&serv_addr, sizeof(serv_addr)) >= 0)
+  CHECK(bind(socket_, (struct sockaddr*)&serv_addr, sizeof(serv_addr)) >= 0)
       << "ERROR on binding";
 
   /* Now start listening for the clients, here process will
@@ -134,7 +134,7 @@ void SocketServer::run() {
   while (true) {
     /* Accept actual connection from the client */
     newsockfd = accept(socket_, (struct sockaddr*)&cli_addr, &clilen);
-    PCHECK(newsockfd >= 0) << "ERROR on accept";
+    CHECK(newsockfd >= 0) << "ERROR on accept";
 
     SocketWorker* worker = new SocketWorker(newsockfd);
     worker->start();
@@ -146,17 +146,17 @@ void SocketWorker::run() {
 
   while (true) {
     int64_t n = channel_.readAll(&header, sizeof(header));
-    PCHECK(n == sizeof(header)) << "ERROR reading from socket";
+    CHECK(n == sizeof(header)) << "ERROR reading from socket";
 
     buffer_.resize(header.dataLength);
     n = channel_.readAll(&buffer_[0], header.dataLength);
-    PCHECK(n == header.dataLength) << "ERROR reading from socket";
+    CHECK(n == header.dataLength) << "ERROR reading from socket";
 
     /* Write a response to the client */
     n = channel_.writeAll(&header, sizeof(header));
-    PCHECK(n == sizeof(header)) << "ERROR reading from socket";
+    CHECK(n == sizeof(header)) << "ERROR reading from socket";
     n = channel_.writeAll(buffer_.data(), buffer_.size());
-    PCHECK(n == header.dataLength) << "ERROR writing to socket";
+    CHECK(n == header.dataLength) << "ERROR writing to socket";
   }
 }
 
@@ -177,9 +177,9 @@ SocketClient::SocketClient(const std::string& serverAddr, int serverPort) {
 
   /* Create a socket point */
   int sockfd = socket(AF_INET, SOCK_STREAM, 0);
-  PCHECK(sockfd >= 0) << "ERROR opening socket";
+  CHECK(sockfd >= 0) << "ERROR opening socket";
   server = gethostbyname(serverAddr.c_str());
-  PCHECK(server) << "ERROR, no such host: " << serverAddr;
+  CHECK(server) << "ERROR, no such host: " << serverAddr;
 
   bzero((char*)&serv_addr, sizeof(serv_addr));
   serv_addr.sin_family = AF_INET;
@@ -189,7 +189,7 @@ SocketClient::SocketClient(const std::string& serverAddr, int serverPort) {
   serv_addr.sin_port = htons(serverPort);
 
   /* Now connect to the server */
-  PCHECK(connect(sockfd, (sockaddr*)&serv_addr, sizeof(serv_addr)) >= 0)
+  CHECK(connect(sockfd, (sockaddr*)&serv_addr, sizeof(serv_addr)) >= 0)
       << "ERROR connecting";
 
   channel_.reset(new SocketChannel(sockfd));
@@ -234,18 +234,18 @@ int main(int argc, char** argv) {
     cpuGrad.copyFrom(gpuGrad);
 
     header.dataLength = dataSize;
-    PCHECK(channel->writeAll(&header, sizeof(header)) == sizeof(header))
+    CHECK(channel->writeAll(&header, sizeof(header)) == sizeof(header))
         << "Client write header error";
 
-    PCHECK(channel->writeAll(cpuGrad.getData(), dataSize) == dataSize)
+    CHECK(channel->writeAll(cpuGrad.getData(), dataSize) == dataSize)
         << "Client write data error";
 
     /* Now read server response */
-    PCHECK(channel->readAll(&header, sizeof(header)) == sizeof(header))
+    CHECK(channel->readAll(&header, sizeof(header)) == sizeof(header))
         << "Client read header error";
 
     CHECK_EQ((uint64_t)header.dataLength, dataSize);
-    PCHECK(channel->readAll(cpuParam.getData(), dataSize) == dataSize)
+    CHECK(channel->readAll(cpuParam.getData(), dataSize) == dataSize)
         << "Client read data error";
 
     gpuParam.copyFrom(cpuParam);

paddle/scripts/docker/build.sh

@@ -78,7 +78,7 @@ paddle version
 # PaddlePaddle.  This awkwardness is due to
 # https://github.com/PaddlePaddle/Paddle/issues/1854.  It also
 # describes a solution.
-if [ ${WITH_DOC} == "ON" ]; then
+if [[ ${WITH_DOC} == "ON" ]]; then
     cat <<EOF
 ========================================
 Building documentation ...

paddle/trainer/Tester.cpp

@@ -175,7 +175,7 @@ real Tester::forwardOneBatch(const DataBatch& dataBatch,
     }
     hl_stream_synchronize(HPPL_STREAM_DEFAULT);
     FILE* fp = fopen(featFile.c_str(), "ab+");
-    PCHECK(!ferror(fp)) << "Fail to open " << featFile;
+    CHECK(!ferror(fp)) << "Fail to open " << featFile;
 
     size_t sampleNum = featMatrices[0]->getHeight();
     for (size_t i = 0; i < sampleNum; ++i) {

paddle/utils/ThreadLocal.h

@@ -51,7 +51,7 @@ template <class T>
 class ThreadLocal {
 public:
   ThreadLocal() {
-    PCHECK(pthread_key_create(&threadSpecificKey_, dataDestructor) == 0);
+    CHECK(pthread_key_create(&threadSpecificKey_, dataDestructor) == 0);
   }
   ~ThreadLocal() { pthread_key_delete(threadSpecificKey_); }
 
@@ -65,7 +65,7 @@ public:
     if (!p && createLocal) {
       p = new T();
       int ret = pthread_setspecific(threadSpecificKey_, p);
-      PCHECK(ret == 0);
+      CHECK(ret == 0);
     }
     return p;
   }
@@ -79,7 +79,7 @@ public:
     if (T* q = get(false)) {
       dataDestructor(q);
     }
-    PCHECK(pthread_setspecific(threadSpecificKey_, p) == 0);
+    CHECK(pthread_setspecific(threadSpecificKey_, p) == 0);
   }
 
   /**
@@ -112,7 +112,7 @@ private:
 template <class T>
 class ThreadLocalD {
 public:
-  ThreadLocalD() { PCHECK(pthread_key_create(&threadSpecificKey_, NULL) == 0); }
+  ThreadLocalD() { CHECK(pthread_key_create(&threadSpecificKey_, NULL) == 0); }
   ~ThreadLocalD() {
     pthread_key_delete(threadSpecificKey_);
     for (auto t : threadMap_) {
@@ -127,7 +127,7 @@ public:
     T* p = (T*)pthread_getspecific(threadSpecificKey_);
     if (!p) {
       p = new T();
-      PCHECK(pthread_setspecific(threadSpecificKey_, p) == 0);
+      CHECK(pthread_setspecific(threadSpecificKey_, p) == 0);
       updateMap(p);
     }
     return p;
@@ -141,7 +141,7 @@ public:
     if (T* q = (T*)pthread_getspecific(threadSpecificKey_)) {
       dataDestructor(q);
     }
-    PCHECK(pthread_setspecific(threadSpecificKey_, p) == 0);
+    CHECK(pthread_setspecific(threadSpecificKey_, p) == 0);
     updateMap(p);
   }
 

python/paddle/trainer/config_parser.py

@@ -2466,10 +2466,14 @@ class MaxLayer(LayerBase):
                  trans_type='non-seq',
                  bias=False,
                  output_max_index=None,
+                 stride=-1,
                  **xargs):
         super(MaxLayer, self).__init__(name, 'max', 0, inputs=inputs, **xargs)
         config_assert(len(self.inputs) == 1, 'MaxLayer must have 1 input')
+        if trans_type == 'seq':
+            config_assert(stride == -1, 'subseq does not support stride window')
         self.config.trans_type = trans_type
+        self.config.seq_pool_stride = stride
         for input_index in xrange(len(self.inputs)):
             input_layer = self.get_input_layer(input_index)
             self.set_layer_size(input_layer.size)
@@ -2731,11 +2735,15 @@ class AverageLayer(LayerBase):
                  average_strategy='average',
                  trans_type='non-seq',
                  bias=False,
+                 stride=-1,
                  **xargs):
         super(AverageLayer, self).__init__(
             name, 'average', 0, inputs=inputs, **xargs)
         self.config.average_strategy = average_strategy
+        if trans_type == 'seq':
+            config_assert(stride == -1, 'subseq does not support stride window')
         self.config.trans_type = trans_type
+        self.config.seq_pool_stride = stride
         config_assert(len(inputs) == 1, 'AverageLayer must have 1 input')
         for input_index in xrange(len(self.inputs)):
             input_layer = self.get_input_layer(input_index)

python/paddle/trainer_config_helpers/layers.py

@@ -1246,10 +1246,19 @@ def pooling_layer(input,
                   name=None,
                   bias_attr=None,
                   agg_level=AggregateLevel.TO_NO_SEQUENCE,
+                  stride=-1,
                   layer_attr=None):
     """
     Pooling layer for sequence inputs, not used for Image.
 
+    If stride > 0, this layer slides a window whose size is determined by stride,
+    and return the pooling value of the window as the output. Thus, a long sequence
+    will be shorten. 
+    
+    The parameter stride specifies the intervals at which to apply the pooling 
+    operation. Note that for sequence with sub-sequence, the default value
+    of stride is -1.
+
     The example usage is:
 
     .. code-block:: python
@@ -1268,6 +1277,8 @@ def pooling_layer(input,
     :param pooling_type: Type of pooling, MaxPooling(default), AvgPooling,
                          SumPooling, SquareRootNPooling.
     :type pooling_type: BasePoolingType|None
+    :param stride: The step size between successive pooling regions.
+    :type stride: Int
     :param bias_attr: Bias parameter attribute. False if no bias.
     :type bias_attr: ParameterAttribute|None|False
     :param layer_attr: The Extra Attributes for layer, such as dropout.
@@ -1285,12 +1296,16 @@ def pooling_layer(input,
         extra_dict['output_max_index'] = pooling_type.output_max_index
     extra_dict.update(ExtraLayerAttribute.to_kwargs(layer_attr))
 
+    if agg_level == AggregateLevel.TO_SEQUENCE:
+        assert stride == -1
+
     Layer(
         name=name,
         type=pooling_type.name,
         inputs=[Input(input.name)],
         bias=ParamAttr.to_bias(bias_attr),
         trans_type=agg_level,
+        stride=stride,
         **extra_dict)
 
     return LayerOutput(
@@ -1552,7 +1567,7 @@ def last_seq(input,
     :type name: basestring
     :param input: Input layer name.
     :type input: LayerOutput
-    :param stride: window size.
+    :param stride: The step size between successive pooling regions.
     :type stride: Int
     :param layer_attr: extra layer attributes.
     :type layer_attr: ExtraLayerAttribute.
@@ -1608,7 +1623,7 @@ def first_seq(input,
     :type name: basestring
     :param input: Input layer name.
     :type input: LayerOutput
-    :param stride: window size.
+    :param stride: The step size between successive pooling regions.
     :type stride: Int
     :param layer_attr: extra layer attributes.
     :type layer_attr: ExtraLayerAttribute.

python/paddle/trainer_config_helpers/tests/configs/protostr/test_sequence_pooling.protostr

@@ -14,6 +14,7 @@ layers {
     input_layer_name: "dat_in"
   }
   trans_type: "seq"
+  seq_pool_stride: -1
 }
 layers {
   name: "__seq_pooling_1__"
@@ -24,6 +25,7 @@ layers {
     input_layer_name: "dat_in"
   }
   trans_type: "non-seq"
+  seq_pool_stride: -1
 }
 layers {
   name: "__seq_pooling_2__"
@@ -35,6 +37,7 @@ layers {
   }
   average_strategy: "average"
   trans_type: "seq"
+  seq_pool_stride: -1
 }
 layers {
   name: "__seq_pooling_3__"
@@ -46,6 +49,7 @@ layers {
   }
   average_strategy: "average"
   trans_type: "non-seq"
+  seq_pool_stride: -1
 }
 layers {
   name: "__seq_pooling_4__"
@@ -57,6 +61,7 @@ layers {
   }
   average_strategy: "sum"
   trans_type: "seq"
+  seq_pool_stride: -1
 }
 layers {
   name: "__seq_pooling_5__"
@@ -68,6 +73,7 @@ layers {
   }
   average_strategy: "sum"
   trans_type: "non-seq"
+  seq_pool_stride: -1
 }
 layers {
   name: "__seq_pooling_6__"
@@ -77,8 +83,44 @@ layers {
   inputs {
     input_layer_name: "dat_in"
   }
+  trans_type: "non-seq"
+  seq_pool_stride: 5
+}
+layers {
+  name: "__seq_pooling_7__"
+  type: "average"
+  size: 100
+  active_type: ""
+  inputs {
+    input_layer_name: "dat_in"
+  }
+  average_strategy: "average"
+  trans_type: "non-seq"
+  seq_pool_stride: 5
+}
+layers {
+  name: "__seq_pooling_8__"
+  type: "average"
+  size: 100
+  active_type: ""
+  inputs {
+    input_layer_name: "dat_in"
+  }
+  average_strategy: "sum"
+  trans_type: "non-seq"
+  seq_pool_stride: 5
+}
+layers {
+  name: "__seq_pooling_9__"
+  type: "max"
+  size: 100
+  active_type: ""
+  inputs {
+    input_layer_name: "dat_in"
+  }
   output_max_index: true
   trans_type: "non-seq"
+  seq_pool_stride: -1
 }
 input_layer_names: "dat_in"
 output_layer_names: "__seq_pooling_0__"
@@ -88,6 +130,9 @@ output_layer_names: "__seq_pooling_3__"
 output_layer_names: "__seq_pooling_4__"
 output_layer_names: "__seq_pooling_5__"
 output_layer_names: "__seq_pooling_6__"
+output_layer_names: "__seq_pooling_7__"
+output_layer_names: "__seq_pooling_8__"
+output_layer_names: "__seq_pooling_9__"
 sub_models {
   name: "root"
   layer_names: "dat_in"
@@ -98,6 +143,9 @@ sub_models {
   layer_names: "__seq_pooling_4__"
   layer_names: "__seq_pooling_5__"
   layer_names: "__seq_pooling_6__"
+  layer_names: "__seq_pooling_7__"
+  layer_names: "__seq_pooling_8__"
+  layer_names: "__seq_pooling_9__"
   input_layer_names: "dat_in"
   output_layer_names: "__seq_pooling_0__"
   output_layer_names: "__seq_pooling_1__"
@@ -106,6 +154,9 @@ sub_models {
   output_layer_names: "__seq_pooling_4__"
   output_layer_names: "__seq_pooling_5__"
   output_layer_names: "__seq_pooling_6__"
+  output_layer_names: "__seq_pooling_7__"
+  output_layer_names: "__seq_pooling_8__"
+  output_layer_names: "__seq_pooling_9__"
   is_recurrent_layer_group: false
 }
 

python/paddle/trainer_config_helpers/tests/configs/test_sequence_pooling.py

@@ -14,6 +14,14 @@ for pt in POOL_TYPE:
     for al in AGG_LEVEL:
         opts.append(pooling_layer(input=din, agg_level=al, pooling_type=pt()))
 
+for pt in POOL_TYPE:
+    opts.append(
+        pooling_layer(
+            input=din,
+            agg_level=AggregateLevel.TO_NO_SEQUENCE,
+            pooling_type=pt(),
+            stride=5))
+
 opts.append(
     pooling_layer(
         input=din, pooling_type=MaxPooling(output_max_index=True)))