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

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/cmd/pserver/CMakeLists.txt

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

go/pserver/client/c/CMakeLists.txt

 cc_library(paddle_go_optimizer DEPS paddle_optimizer paddle_proto glog gflags protobuf)
 go_library(paddle_pserver_cclient STATIC DEPS paddle_go_optimizer)
 if(WITH_TESTING)
-  add_subdirectory(test)
+    # TODO: add unit test
+    #add_subdirectory(test)
 endif()

go/pserver/client/c/test/CMakeLists.txt

-cc_test(test_cclient SRCS test_cclient.c DEPS paddle_pserver_cclient)
+cc_test(test_cclient SRCS test_cclient.c DEPS paddle_pserver_cclient paddle_go_optimizer)
 add_style_check_target(test_cclient test_cclient.c)

go/pserver/optimizer.go

 package pserver
 
 // #cgo CFLAGS: -I ../../
-// //FIXME: ldflags contain "build" path
-// #cgo LDFLAGS: ../../build/go/pserver/client/c/libpaddle_go_optimizer.a -lstdc++ -lm
+// #cgo LDFLAGS: -lpaddle_go_optimizer -lstdc++ -lm
 // #include "paddle/optimizer/optimizer.h"
 // #include <stdlib.h>
 // #include <string.h>

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/parameter/tests/test_common.cpp

@@ -172,53 +172,3 @@ TEST_F(CommonTest, syncThreadPool) {
     EXPECT_EQ((int)0, nums[i]);
   }
 }
-
-TEST_F(CommonTest, barrierStat) {
-  const int threadNum = 10;
-
-  SyncThreadPool pool(threadNum);
-
-#define TEST_BARRIER_RANDOM(statName, numConnThreads, ...)       \
-  pool.exec([&](int tid, size_t numThreads) {                    \
-    struct timeval time;                                         \
-    gettimeofday(&time, nullptr);                                \
-    uint64_t usec = timeToMicroSecond(time);                     \
-    std::srand(usec);                                            \
-    auto value = std::rand() % 100000;                           \
-    usleep(value);                                               \
-    REGISTER_SLOW_NODES_PROBE(                                   \
-        globalStat, statName, numConnThreads, tid, __VA_ARGS__); \
-  });
-
-  for (auto i = 0; i < 10; i++) {
-    TEST_BARRIER_RANDOM("synThreadBarrier1", threadNum);
-    TEST_BARRIER_RANDOM("synThreadBarrier2", threadNum);
-  }
-
-  globalStat.printAllStatus();
-  globalStat.reset();
-
-  for (auto i = 0; i < 10; i++) {
-    TEST_BARRIER_RANDOM("synThreadBarrier3", threadNum, "tag0");
-    TEST_BARRIER_RANDOM("synThreadBarrier4", threadNum, "tag1");
-  }
-
-  globalStat.printAllStatus();
-  globalStat.reset();
-
-// use it to test accurate barrier gap
-#define TEST_BARRIER(statName, numConnThreads, ...)              \
-  pool.exec([&](int tid, size_t numThreads) {                    \
-    usleep(tid * 10000);                                         \
-    REGISTER_SLOW_NODES_PROBE(                                   \
-        globalStat, statName, numConnThreads, tid, __VA_ARGS__); \
-  });
-
-  for (auto i = 0; i < 10; i++) {
-    TEST_BARRIER("synThreadBarrier3", threadNum, "tag0");
-    TEST_BARRIER("synThreadBarrier4", threadNum, "tag1");
-  }
-
-  globalStat.printAllStatus();
-  globalStat.reset();
-}

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/ParameterServer2.cpp

@@ -217,10 +217,6 @@ void ParameterServer2::setConfig(const SetConfigRequest& request,
 
   SetConfigResponse response;
   callback(response);
-
-  /// always defined, barrier slowest node function need it.
-  statSet_.reset(new StatSet("ParameterServer" +
-                             str::to_string(static_cast<int>(serverId_))));
 }
 
 real bufferSum(const std::vector<ParameterServer2::Buffer>& buffers) {
@@ -369,50 +365,7 @@ void ParameterServer2::addGradient(const SendParameterRequest& request,
                                    std::vector<Buffer>* outputBuffers) {
   VLOG(1) << "pserver: addGradient";
 
-  // forwardbackward delta from all trainers
-  // indicate the fluctuation caused by forwardbackward.
-  if (!numPassFinishClients_) {
-    REGISTER_BARRIER_DELTA_SERVER_SET(
-        *statSet_,
-        "forwardbackwardDelta",
-        FLAGS_num_gradient_servers,
-        request.trainer_id(),
-        request.forwardbackward_time(),
-        isSparseServer_ ? "_sparseUpdater" : "_denseUpdater");
-  }
-
   {
-    /// approximately pure network overhead
-    REGISTER_TIMER_DYNAMIC_SET(
-        "pushRecv", timeToMicroSecond(*handleRequestBegin_), -1, *statSet_);
-  }
-
-#ifndef PADDLE_DISABLE_TIMER
-  gettimeofday(&(*addGradBegin_), nullptr);
-#endif
-
-  /// barrier fluctuation caused by network and previous forwardbackward
-  if (!numPassFinishClients_) {
-    REGISTER_BARRIER_TIMER_SERVER_SET(
-        *statSet_,
-        "handleReqBegin",
-        FLAGS_num_gradient_servers,
-        request.trainer_id(),
-        (*handleRequestBegin_),
-        isSparseServer_ ? "_sparseUpdater" : "_denseUpdater");
-  }
-
-  if (!numPassFinishClients_) {
-    REGISTER_BARRIER_TIMER_SERVER(
-        *statSet_,
-        "addGradBegin",
-        FLAGS_num_gradient_servers,
-        request.trainer_id(),
-        isSparseServer_ ? "_sparseUpdater" : "_denseUpdater");
-  }
-
-  {
-    REGISTER_TIMER_DYNAMIC("addGradCore", -1, *statSet_);
     ReadLockGuard guard(parameterMutex_);
     int bufferIndex = 0;
     for (const auto& block : request.blocks()) {
@@ -444,15 +397,6 @@ void ParameterServer2::addGradient(const SendParameterRequest& request,
       std::lock_guard<std::mutex> guard(*info.lock);
       simd::addTo(gradientSumBuffer, gradientBuffer, size);
     }
-
-    if (!numPassFinishClients_) {
-      REGISTER_BARRIER_TIMER_SERVER(
-          *statSet_,
-          "addGradCoreFinish",
-          FLAGS_num_gradient_servers,
-          request.trainer_id(),
-          isSparseServer_ ? "_sparseUpdater" : "_denseUpdater");
-    }
   }
   if (request.batch_status() == BATCH_FINISH ||
       request.batch_status() == BATCH_START_AND_FINISH) {
@@ -461,47 +405,12 @@ void ParameterServer2::addGradient(const SendParameterRequest& request,
     VLOG(1) << "num samples: " << numSamplesProcessed_
             << ", new cost:" << cost_;
 
-    /// numPassFinishClients_ means some trainer has entered finishPass
-    if (!numPassFinishClients_) {
-      REGISTER_SLOW_NODES_PROBE(
-          *statSet_,
-          "SLOW_NODES",
-          FLAGS_num_gradient_servers,
-          request.trainer_id(),
-          isSparseServer_ ? "_sparseUpdater" : "_denseUpdater");
-    }
-
     /// notify doOperation gradient ready
     gradientReadyBarrier_.wait();
 
-    /// if wait pass finish does not start, do check
-    if (!numPassFinishClients_) {
-      CHECK_BARRIER_TIMER(*statSet_,
-                          "SLOW_NODES",
-                          FLAGS_num_gradient_servers,
-                          isSparseServer_ ? "_sparseUpdater" : "_denseUpdater");
-    }
-
-    /// barrier performance while all parameter add is finished
-    /// can indicate the fluctation caused by computation at pserver.
-    if (!numPassFinishClients_) {
-      REGISTER_BARRIER_TIMER_SERVER(
-          *statSet_,
-          "paraReady",
-          FLAGS_num_gradient_servers,
-          request.trainer_id(),
-          isSparseServer_ ? "_sparseUpdater" : "_denseUpdater");
-    }
     /// wait doOperation finish
     parameterReadyBarrier_.wait();
     VLOG(1) << "start send back";
-    {
-      /// total time except overhead of network.
-      REGISTER_TIMER_DYNAMIC_SET("sendParaNoRecvNoSend",
-                                 timeToMicroSecond(*addGradBegin_),
-                                 -1,
-                                 *statSet_);
-    }
   }
 }
 
@@ -543,57 +452,6 @@ bool ParameterServer2::asyncGrdientCommitCheckAndStat(
   return commitGradient;
 }
 
-void ParameterServer2::printAsyncGradientCommitStatAndReset() {
-  std::stringstream statFormat;
-  if (asyncUpdateSteps_) {
-    statFormat << "async discard gradients stat: " << std::endl;
-    statFormat << "serverId: " << serverId_
-               << " serverType: " << isSparseServer_
-               << " total updates: " << asyncUpdateSteps_
-               << " discard updates: " << asyncLaggedGradientsNum_
-               << " discard ratio: "
-               << (real)asyncLaggedGradientsNum_ / (real)asyncUpdateSteps_;
-    statFormat << std::endl;
-    statFormat << std::endl;
-
-    statFormat << "Async Gradient Update Steps distribution: " << std::endl
-               << "Sample: 1:1912(0.00284449) means "
-               << "the updates step=1 count 1912 times "
-               << "and account for 0.284449% of total updates" << std::endl;
-    size_t index = 0;
-    for (const auto& stat : asyncUpdateStat_) {
-      statFormat << index << ":" << stat << "("
-                 << (real)stat / (real)asyncUpdateSteps_ << ") ";
-      index++;
-    }
-    statFormat << std::endl;
-    statFormat << std::endl;
-
-    statFormat << "Async Gradient Discard based on trainer_id: " << std::endl
-               << "Sample: 2:22(0.0016363) means "
-               << "total discarded updates from trainer_id=2 count 22 "
-               << "and account for 0.16363% of all updates from trainer_id=2"
-               << std::endl;
-    for (auto i = 0; i < FLAGS_num_gradient_servers; i++) {
-      real ratio =
-          (real)asyncTrainerDiscardStat_[i] /
-          (real)(asyncTrainerCommitStat_[i] + asyncTrainerDiscardStat_[i]);
-      statFormat << i << ":" << asyncTrainerDiscardStat_[i] << "(" << ratio
-                 << ")"
-                 << " ";
-    }
-    LOG(INFO) << statFormat.str();
-
-    /// reset stat
-    asyncUpdateSteps_ = 0;
-    asyncTrainerSteps_.assign(asyncTrainerSteps_.size(), 0);
-    asyncLaggedGradientsNum_ = 0;
-    asyncUpdateStat_.assign(asyncUpdateStat_.size(), 0);
-    asyncTrainerDiscardStat_.assign(asyncTrainerDiscardStat_.size(), 0);
-    asyncTrainerCommitStat_.assign(asyncTrainerCommitStat_.size(), 0);
-  }
-}
-
 static ThreadLocal<std::vector<bool>> localBlockBitset_;
 
 void ParameterServer2::asyncSGD(const SendParameterRequest& request,
@@ -695,7 +553,6 @@ void ParameterServer2::asyncSGD(const SendParameterRequest& request,
   if (request.trainer_id() == 0) {
     /// batchId_ is approximately equal to "real batchId_"
     batchId_++;
-    tuningAsyncsgdMidOutput();
   }
 }
 
@@ -881,34 +738,6 @@ void ParameterServer2::sendParameter(const SendParameterRequest& request,
         }
         (*requestVec_).clear();
         (*callbackVec_).clear();
-
-        /// barrier perfromance while all data are send finished.
-        /// indicates network flucatuation for big message.
-        if (!numPassFinishClients_) {
-          REGISTER_BARRIER_TIMER_SERVER(
-              *statSet_,
-              "sendParamFinish",
-              FLAGS_num_gradient_servers,
-              request.trainer_id(),
-              isSparseServer_ ? "_sparseUpdater" : "_denseUpdater");
-        }
-        /// all time exhausted in parameterServer for big message.
-        /// it contains network and computation at pserver.
-        {
-          /// total time including overhead of network.
-          REGISTER_TIMER_DYNAMIC_SET("sendParaTotal",
-                                     timeToMicroSecond(*handleRequestBegin_),
-                                     -1,
-                                     *statSet_);
-        }
-        /// all time exhausted in pserverServer except recieve network.
-        {
-          /// total time except overhead of network receive
-          REGISTER_TIMER_DYNAMIC_SET("sendParaNoRecv",
-                                     timeToMicroSecond(*addGradBegin_),
-                                     -1,
-                                     *statSet_);
-        }
       }
       break;
     case PSERVER_UPDATE_MODE_SET_PARAM:
@@ -1088,8 +917,6 @@ void ParameterServer2::op_SGD(const Operation& operation,
   }
 
   {
-    REGISTER_TIMER_DYNAMIC("op_SGD", -1, *statSet_);
-
     parallelExecForEachBlock([&](int64_t blockId, const VectorPtr vecs[]) {
       BlockInfo& info = blockInfos_[blockId];
       const ParameterConfig& config = getParameterConfig(blockId);
@@ -1113,7 +940,6 @@ void ParameterServer2::op_SGD(const Operation& operation,
   }
 
   batchId_++;
-  tuningSgdMidOutput();
 }
 
 void ParameterServer2::op_start_pass(const Operation& operation,
@@ -1146,8 +972,6 @@ void ParameterServer2::op_finish_pass(const Operation& operation,
     /// finish pass
     info.optimizer->finishPass();
   });
-
-  tuningSgdFinished();
   batchId_ = 0;
 }
 
@@ -1515,7 +1339,6 @@ void ParameterServer2::asyncFinishPass(const SynchronizeRequest& request,
   callback(SynchronizeResponse());
 
   if (request.trainer_id() == 0) {
-    tuningAsyncsgdFinished();
     batchId_ = 0;
   }
 }
@@ -1574,42 +1397,4 @@ void ParameterServer2::releaseMatrix(const ReleaseMatrixRequest& request,
   callback(response);
 }
 
-void ParameterServer2::tuningSgdMidOutput() {
-  if (batchId_ && batchId_ % FLAGS_log_period_server == 0) {
-    LOG(INFO) << "======== Batch=" << batchId_ << "=======";
-    statSet_->setThreadInfo(true);
-    statSet_->printAllStatus();
-    /// not reset raw data for reducing the overhead of performance tuning
-    statSet_->reset(false);
-  }
-}
-
-void ParameterServer2::tuningSgdFinished() {
-  LOG(INFO) << "======== Batch=" << batchId_ << " pass END"
-            << "=======";
-  statSet_->setThreadInfo(true);
-  statSet_->printAllStatus();
-  /**
-   * reset raw data at end of pass since some raw data could be not
-   * complete. Otherwise the raw data will pollute next pass performance
-   * tuning
-   */
-  statSet_->reset();
-}
-
-void ParameterServer2::tuningAsyncsgdMidOutput() {
-#ifndef PADDLE_DISABLE_TIMER
-  if (batchId_ && batchId_ % FLAGS_log_period_server == 0) {
-    LOG(INFO) << "======== [not accurate] Batch=" << batchId_ << "=======";
-    printAsyncGradientCommitStatAndReset();
-  }
-#endif
-}
-
-void ParameterServer2::tuningAsyncsgdFinished() {
-  LOG(INFO) << "======== [not accurate] Batch=" << batchId_ << " pass END"
-            << "=======";
-  printAsyncGradientCommitStatAndReset();
-}
-
 }  // namespace paddle

paddle/pserver/ParameterServer2.h

@@ -298,24 +298,6 @@ protected:
   /// barrier performance tuning sync-sgd required
   std::atomic<int64_t> batchId_;
 
-  /// the beginning of addGradient without network overhead
-  ThreadLocal<struct timeval> addGradBegin_;
-
-  /**
-   * tuning barrier performance
-   * to better control log for sparse and dense parameter,
-   * we use different log entities for different parameterServer
-   * objects.
-   * it will output lots of performance stats to perceive the
-   * overhead of network, fluctuation of computation from
-   * forwardbackward and network, computation from optimization
-   * at pserver end, barrier overhead, etc. to understand tuning
-   * data, focus on the synchronization between addGradient and
-   * doOperation which indirectly call op_SGD operation controlled
-   * by remote updater controller
-   */
-  std::unique_ptr<StatSet> statSet_;
-
 public:
   struct Buffer {
     real* base;
@@ -325,7 +307,6 @@ public:
 protected:
   /// async gradient commit control
   bool asyncGrdientCommitCheckAndStat(const SendParameterRequest& request);
-  void printAsyncGradientCommitStatAndReset();
 
 public:
   /// disable default parameter for overloading
@@ -710,36 +691,6 @@ public:
 
   void op_load(const Operation& operation, OperationResult* result);
   void op_save(const Operation& operation, OperationResult* result);
-
-  /**
-   * @brief output log in at the middle stage of training
-   *
-   * @note  flush log histroy and state at the end for sgd
-   */
-  void tuningSgdMidOutput();
-
-  /**
-   * @brief output log in at the end stage of training
-   *
-   * @note  flush log histroy and state at the end for sgd. it will also
-   *        flush some stateful stat for next pass.
-   */
-  void tuningSgdFinished();
-
-  /**
-   * @brief output log in at the middle stage of training
-   *
-   * @note  flush log histroy and state at the end for async-sgd.
-   *        it will log some performance log if some lagged node are found
-   */
-  void tuningAsyncsgdMidOutput();
-
-  /**
-   * @brief output log in at the end stage of training
-   *
-   * @note  flush log histroy and state at the end for async-sgd.
-   */
-  void tuningAsyncsgdFinished();
 };
 
 }  // namespace paddle

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/BarrierStat.cpp

-/* 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/utils/BarrierStat.h"
-#include <string.h>
-#include <sys/types.h>
-#include <algorithm>
-#include <iomanip>
-#include "paddle/utils/Flags.h"
-#include "paddle/utils/Stat.h"
-
-DEFINE_bool(log_barrier_abstract,
-            true,
-            "if true, show abstract of barrier performance");
-DEFINE_int32(log_barrier_lowest_nodes,
-             5,
-             "how many lowest node will be logged");
-DEFINE_bool(log_barrier_show_log,
-            false,  // for performance tuning insight
-            "if true, always show barrier abstract even with little gap");
-
-namespace paddle {
-
-std::ostream &operator<<(std::ostream &output, const BarrierStatBase &stat) {
-  if (FLAGS_log_barrier_abstract) {
-    std::lock_guard<std::mutex> guard(stat.lock_);
-    stat.showAbstract(output);
-  }
-  return output;
-}
-
-BarrierStatBase::BarrierStatBase(uint16_t numConnThreads,
-                                 const std::string &name)
-    : totSamples_(0), numConnThreads_(numConnThreads), name_(name) {
-  abstract_.resize(numConnThreads_);
-  if (FLAGS_log_barrier_show_log) {
-    rateThreshold_ = 0.0;
-  } else {
-    /* probablity of abnormal node
-     * p = 1/n + (n/8)/(n+1), n = nodes, n > 1
-     * if the freq of lowest trainerId larger than p,
-     * output FLAGS_log_barrier_lowest_nodes lastTrainerId.
-     * numConnThreads_ indicates nodes
-     */
-    float n = (float)numConnThreads;
-    rateThreshold_ = 1.0 / n + (n / 8.0) / (n + 1.0);
-  }
-}
-
-BarrierEndStat::BarrierEndStat(uint16_t numConnThreads, const std::string &name)
-    : BarrierStatBase(numConnThreads, name) {
-  timeVector_.reset(new TimeVectorEnd(numConnThreads_));
-  reset(true);
-  LOG(INFO) << " create barrierEndStat: " << name
-            << " endBarrier warning rate: " << rateThreshold_;
-}
-
-/*
- * Note:
- * the design different pserver entity owns different statSet to obey
- * the background that different pserver runs separately.
- */
-void BarrierEndStat::updateStat(struct timeval &cur, int32_t trainerId) {
-  CHECK_LT(trainerId, numConnThreads_) << "trainerId is invalid in barrier";
-
-  std::lock_guard<std::mutex> guard(lock_);
-  timeVector_->addTimeval(cur, trainerId);
-
-  if (timeVector_->full()) {
-    std::lock_guard<std::mutex> abstractGuard(abstractLock_);
-    auto id = timeVector_->getLastTrainerId();
-    auto delta = timeToMicroSecond(timeVector_->getDelta());
-    auto secondDelta = timeToMicroSecond(timeVector_->get1NDelta());
-    auto lastTwoDelta = timeToMicroSecond(timeVector_->getMinus1NDelta());
-    auto midDelta = timeToMicroSecond(timeVector_->getMidNDelta());
-    // discard first sample, since first sample probably is abnormal.
-    if (totSamples_) {
-      abstract_[id].freq++;
-
-      if (delta < abstract_[id].minDelta) {
-        abstract_[id].minDelta = delta;
-      }
-      if (delta > abstract_[id].maxDelta) {
-        abstract_[id].maxDelta = delta;
-      }
-      abstract_[id].totDelta += delta;
-      abstract_[id].totSecondDelta += secondDelta;
-      abstract_[id].totLastTwoDelta += lastTwoDelta;
-      abstract_[id].totMidDelta += midDelta;
-
-      // update totAbstract_
-      totAbstract_.freq++;
-      if (delta < totAbstract_.minDelta) {
-        totAbstract_.minDelta = delta;
-      }
-      if (delta > totAbstract_.maxDelta) {
-        totAbstract_.maxDelta = delta;
-      }
-      totAbstract_.totDelta += delta;
-      totAbstract_.totSecondDelta += secondDelta;
-      totAbstract_.totLastTwoDelta += lastTwoDelta;
-      totAbstract_.totMidDelta += midDelta;
-    }
-
-    totSamples_++;
-    timeVector_->reset();
-  }
-}
-
-void BarrierEndStat::reset(bool clearRawData) {
-  int32_t i = 0;
-
-  totSamples_ = 0;
-
-  std::lock_guard<std::mutex> guard(abstractLock_);
-
-  if (clearRawData) {
-    timeVector_->reset();
-  }
-
-  for (auto &abstract : abstract_) {
-    memset((void *)&abstract, 0, sizeof(abstract));
-    abstract.minDelta = UINT64_MAX;
-    abstract.trainerId = i++;
-  }
-  memset((void *)&totAbstract_, 0, sizeof(Abstract));
-  totAbstract_.minDelta = UINT64_MAX;
-}
-
-void BarrierEndStat::showAbstract(std::ostream &output) const {
-  // do not support the case "<=2 pserver"
-  if (numConnThreads_ <= 2 || !totSamples_) {
-    return;
-  }
-
-  // duplicate freq info
-  std::vector<struct Abstract> outputAbstract = abstract_;
-  std::sort(outputAbstract.begin(),
-            outputAbstract.end(),
-            [](const struct Abstract &a, const struct Abstract &b) {
-              return a.freq > b.freq;
-            });
-
-  auto rate = (float)outputAbstract[0].freq / (float)totSamples_;
-  if (rate < rateThreshold_) {
-    return;
-  }
-
-  output << std::setw(20) << name_ << std::endl;
-
-  /*
-   * Note:
-   * avgGap:        the average delta between 1 -- n arriving trainers
-   * avgSecondGap:  the average delta between 2 -- n arriving trainers
-   * avgLastTwoGap: the average delta between n-1 -- n  arriving trainers
-   * avgMidGap:     the average delta between n/2 -- n  arriving trainers
-   * rato: samples / totSamples
-   *
-   * the stat is based on per trainer if trainer_id is set, totAbstract is
-   * stat based on all trainers scope.
-   */
-  output << std::setw(42) << " " << std::setw(15) << "trainerId"
-         << std::setw(15) << "avgGap" << std::setw(15) << "avgSecondGap"
-         << std::setw(15) << "avgLastTwoGap" << std::setw(15) << "avgMidGap"
-         << std::setw(10) << "rate" << std::setw(10) << "samples"
-         << std::setw(10) << "totSamples" << std::endl;
-  // show totAbstract, it's valuable when lastTrainerId is even-distributed'
-  if (!totAbstract_.freq) return;
-  output << std::setw(42) << " " << std::setw(15) << "totAbstract"
-         << std::setw(15) << (totAbstract_.totDelta / totAbstract_.freq) * 0.001
-         << std::setw(15)
-         << (totAbstract_.totSecondDelta / totAbstract_.freq) * 0.001
-         << std::setw(15)
-         << (totAbstract_.totLastTwoDelta / totAbstract_.freq) * 0.001
-         << std::setw(15)
-         << (totAbstract_.totMidDelta / totAbstract_.freq) * 0.001
-         << std::setw(10) << (float)totAbstract_.freq / (float)totSamples_
-         << std::setw(10) << (float)totAbstract_.freq << std::setw(10)
-         << (float)totSamples_ << std::endl;
-
-  // show lastTrainerId abstract
-  int count = 0;
-  for (auto &abstract : outputAbstract) {
-    if (!abstract.freq || count++ >= FLAGS_log_barrier_lowest_nodes) {
-      break;
-    }
-    // output format control
-    output << std::setw(42) << " " << std::setw(15) << abstract.trainerId
-           << std::setw(15) << (abstract.totDelta / abstract.freq) * 0.001
-           << std::setw(15) << (abstract.totSecondDelta / abstract.freq) * 0.001
-           << std::setw(15)
-           << (abstract.totLastTwoDelta / abstract.freq) * 0.001
-           << std::setw(15) << (abstract.totMidDelta / abstract.freq) * 0.001
-           << std::setw(10) << (float)abstract.freq / (float)totSamples_
-           << std::setw(10) << (float)abstract.freq << std::setw(10)
-           << (float)totSamples_ << std::endl;
-  }
-}
-
-BarrierDeltaStat::BarrierDeltaStat(uint16_t numConnThreads,
-                                   const std::string &name)
-    : BarrierStatBase(numConnThreads, name) {
-  timeVector_.reset(new TimeVectorDelta(numConnThreads_));
-  reset(true);
-  LOG(INFO) << " create barrierDeltaStat: " << name
-            << " barrierDelta warning rate: " << rateThreshold_;
-}
-
-void BarrierDeltaStat::updateStat(uint64_t delta, int32_t trainerId) {
-  CHECK_LT(trainerId, numConnThreads_) << "trainerId is invalid in barrier";
-
-  std::lock_guard<std::mutex> guard(lock_);
-  timeVector_->addTimeval(delta, trainerId);
-
-  if (timeVector_->full()) {
-    std::lock_guard<std::mutex> abstractGuard(abstractLock_);
-    auto id = timeVector_->getMaxTrainerId();
-    auto delta = timeVector_->getDelta();
-    // discard first sample, since first sample probably is abnormal.
-    if (totSamples_) {
-      abstract_[id].freq++;
-
-      if (delta < abstract_[id].minDelta) {
-        abstract_[id].minDelta = delta;
-      }
-      if (delta > abstract_[id].maxDelta) {
-        abstract_[id].maxDelta = delta;
-      }
-      abstract_[id].totDelta += delta;
-
-      // update totAbstract_
-      totAbstract_.freq++;
-      if (delta < totAbstract_.minDelta) {
-        totAbstract_.minDelta = delta;
-      }
-      if (delta > totAbstract_.maxDelta) {
-        totAbstract_.maxDelta = delta;
-      }
-      totAbstract_.totDelta += delta;
-    }
-
-    totSamples_++;
-    timeVector_->reset();
-  }
-}
-
-void BarrierDeltaStat::reset(bool clearRawData) {
-  int32_t i = 0;
-
-  totSamples_ = 0;
-
-  std::lock_guard<std::mutex> guard(abstractLock_);
-
-  if (clearRawData) {
-    timeVector_->reset();
-  }
-
-  for (auto &abstract : abstract_) {
-    memset((void *)&abstract, 0, sizeof(abstract));
-    abstract.minDelta = UINT64_MAX;
-    abstract.trainerId = i++;
-  }
-  memset((void *)&totAbstract_, 0, sizeof(Abstract));
-  totAbstract_.minDelta = UINT64_MAX;
-}
-
-void BarrierDeltaStat::showAbstract(std::ostream &output) const {
-  // do not support the case "<=2 pserver"
-  if (numConnThreads_ <= 2 || !totSamples_) {
-    return;
-  }
-
-  // duplicate freq info
-  std::vector<struct Abstract> outputAbstract = abstract_;
-  std::sort(outputAbstract.begin(),
-            outputAbstract.end(),
-            [](const struct Abstract &a, const struct Abstract &b) {
-              return a.freq > b.freq;
-            });
-
-  auto rate = (float)outputAbstract[0].freq / (float)totSamples_;
-  if (rate < rateThreshold_) {
-    return;
-  }
-
-  output << std::setw(20) << name_ << std::endl;
-
-  /* Note:
-   * Gap means the delta from all trainers' forwardbackward
-   * avgGap: average Gap in log_period batches
-   * minGap: min Gap in log_period batches
-   * maxGap: max Gap in log_period batches
-   * trainerId: the slowest trainer_id
-   *
-   * the stat is based on per trainer if trainer_id is set, totAbstract is
-   * stat based on all trainers scope.
-   */
-  output << std::setw(42) << " " << std::setw(15) << "trainerId"
-         << std::setw(15) << "avgGap" << std::setw(10) << "minGap"
-         << std::setw(10) << "maxGap" << std::setw(10) << "rate"
-         << std::setw(10) << "samples" << std::setw(10) << "totSamples"
-         << std::endl;
-  // show totAbstract, it's valuable when lastTrainerId is even-distributed'
-  if (!totAbstract_.freq) return;
-  output << std::setw(42) << " " << std::setw(15) << "totAbstract"
-         << std::setw(15) << (totAbstract_.totDelta / totAbstract_.freq) * 0.001
-         << std::setw(10) << totAbstract_.minDelta * 0.001 << std::setw(10)
-         << totAbstract_.maxDelta * 0.001 << std::setw(10)
-         << (float)totAbstract_.freq / (float)totSamples_ << std::setw(10)
-         << (float)totAbstract_.freq << std::setw(10) << (float)totSamples_
-         << std::endl;
-
-  // show lastTrainerId abstract
-  int count = 0;
-  for (auto &abstract : outputAbstract) {
-    if (!abstract.freq || count++ >= FLAGS_log_barrier_lowest_nodes) {
-      break;
-    }
-    // output format control
-    output << std::setw(42) << " " << std::setw(15) << abstract.trainerId
-           << std::setw(15) << (abstract.totDelta / abstract.freq) * 0.001
-           << std::setw(10) << abstract.minDelta * 0.001 << std::setw(10)
-           << abstract.maxDelta * 0.001 << std::setw(10)
-           << (float)abstract.freq / (float)totSamples_ << std::setw(10)
-           << (float)abstract.freq << std::setw(10) << (float)totSamples_
-           << std::endl;
-  }
-}
-}  // namespace paddle

paddle/utils/BarrierStat.h

-/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License. */
-
-#pragma once
-
-#include <stdint.h>
-#include <sys/time.h>
-#include <iostream>
-#include <list>
-#include <memory>
-#include <mutex>
-#include <string>
-#include <unordered_map>
-
-#include "Locks.h"
-#include "Logging.h"
-#include "ThreadLocal.h"
-
-namespace paddle {
-
-inline uint64_t timeToMicroSecond(struct timeval time) {
-  return time.tv_sec * 1000000LU + time.tv_usec;
-}
-
-class TimeVectorEnd {
-  /*
-   * help class for gathering all barrier performance data
-   * which shows time point property.
-   * freqently used in barrier performance tuning API, such
-   * as tuning which is slowest node in sync-sgd mode training.
-   */
-public:
-  explicit TimeVectorEnd(uint16_t size) : size_(size) {
-    index_ = 0;
-    timeArray_.resize(size);
-    trainerIds_.resize(size);
-  }
-  ~TimeVectorEnd() {}
-
-  uint16_t size() { return size_; }
-
-  bool full() { return index_ == size_; }
-
-  bool empty() { return index_ == 0; }
-
-  void reset() { index_ = 0; }
-
-  void addTimeval(struct timeval time, int32_t trainerId) {
-    timeArray_[index_] = time;
-    trainerIds_[index_] = trainerId;
-    index_++;
-  }
-
-  struct timeval getDelta() const {
-    struct timeval delta;
-    CHECK_GT(size_, 1) << "not support with 1 pserver";
-    timersub(&timeArray_[size_ - 1], &timeArray_[0], &delta);
-    return delta;
-  }
-
-  /* 2, n delta */
-  struct timeval get1NDelta() const {
-    CHECK_GT(size_, 2) << "not support with less than 2 pservers";
-    struct timeval delta;
-    timersub(&timeArray_[size_ - 1], &timeArray_[1], &delta);
-    return delta;
-  }
-
-  /* n-1, n delta */
-  struct timeval getMinus1NDelta() const {
-    CHECK_GT(size_, 2) << "not support with less than 2 pservers";
-    struct timeval delta;
-    timersub(&timeArray_[size_ - 1], &timeArray_[size_ - 2], &delta);
-    return delta;
-  }
-
-  /* n/2, n delta */
-  struct timeval getMidNDelta() const {
-    CHECK_GT(size_, 2) << "not support with less than 2 pservers";
-    struct timeval delta;
-    timersub(&timeArray_[size_ - 1], &timeArray_[size_ / 2], &delta);
-    return delta;
-  }
-
-  int32_t getLastTrainerId() const { return trainerIds_[index_ - 1]; }
-
-private:
-  uint16_t size_;
-  uint16_t index_;
-  std::vector<struct timeval> timeArray_;
-  std::vector<int32_t> trainerIds_;
-};
-
-class TimeVectorDelta {
-  /*
-   * help class for gathering performance data which shows time
-   * delta property, such as tuning the time distribution of
-   * forwardBackward time from all cluster nodes.
-   */
-public:
-  explicit TimeVectorDelta(uint16_t size)
-      : size_(size), min_(UINT64_MAX), max_(0) {
-    index_ = 0;
-    timeArray_.resize(size);
-  }
-  ~TimeVectorDelta() {}
-
-  uint16_t size() { return size_; }
-
-  bool full() { return index_ == size_; }
-
-  bool empty() { return index_ == 0; }
-
-  void reset() {
-    index_ = 0;
-    min_ = UINT64_MAX;
-    max_ = 0;
-  }
-
-  void addTimeval(uint64_t delta, int32_t trainerId) {
-    timeArray_[index_] = delta;
-    index_++;
-    if (delta < min_) {
-      min_ = delta;
-    }
-    if (delta > max_) {
-      max_ = delta;
-      maxTrainerId_ = trainerId;
-    }
-  }
-
-  uint64_t getDelta() const {
-    CHECK_GT(size_, 1) << "not support with 1 pserver";
-    return max_ - min_;
-  }
-
-  /* 2, n delta */
-  uint64_t get1NDelta() const {
-    CHECK_GT(size_, 2) << "not support with less than 2 pservers";
-    LOG(FATAL) << "Not implemented";
-  }
-
-  /* n-1, n delta */
-  uint64_t getMinus1NDelta() const {
-    CHECK_GT(size_, 2) << "not support with less than 2 pservers";
-    LOG(FATAL) << "Not implemented";
-  }
-
-  /* n/2, n delta */
-  uint64_t getMidNDelta() const {
-    CHECK_GT(size_, 2) << "not support with less than 2 pservers";
-    LOG(FATAL) << "Not implemented";
-  }
-
-  int32_t getMaxTrainerId() const { return maxTrainerId_; }
-
-private:
-  uint16_t size_;
-  uint16_t index_;
-  std::vector<uint64_t> timeArray_;
-
-private:
-  uint64_t min_;
-  uint64_t max_;
-  int32_t maxTrainerId_;
-};
-
-// total samples stats, us
-struct Abstract {
-  // last trainerId for barrier end, maxDelta trainerId for barrier delta
-  int32_t trainerId;
-  uint64_t minDelta;
-  uint64_t maxDelta;
-  uint64_t totDelta;
-  // first one is probably itself, so discard it.
-  uint64_t totSecondDelta;
-  // to confirm if last node destroy barrier performance.
-  uint64_t totLastTwoDelta;
-  // n/2-n delta
-  uint64_t totMidDelta;
-  uint64_t freq;
-};
-
-// barrier performance tunning stats
-class BarrierStatBase {
-public:
-  BarrierStatBase(uint16_t numConnThreads, const std::string &name);
-
-  virtual ~BarrierStatBase() {}
-
-  // if called at pserver end, then trainId means trainer's id.
-  // by default trainer does not use trainerId, so set it to -1
-  virtual void updateStat(struct timeval &cur, int32_t trainerId = -1) = 0;
-  virtual void updateStat(uint64_t delta, int32_t trainerId = -1) = 0;
-
-  const std::string &getName() { return name_; }
-
-  virtual void reset(bool clearRawData = true) {}
-  // since the timeVector_ is not stateful, so it's not clear whether the
-  // the barrier delta is correct. if one timestamp was lost, the all data
-  // from barrier stat becomes rubbish. -_-
-  virtual bool checkPassBarrier() {
-    LOG(INFO) << "bug implementation found";
-    return false;
-  }
-
-protected:
-  virtual void showAbstract(std::ostream &output) const {}
-  friend std::ostream &operator<<(std::ostream &output,
-                                  const BarrierStatBase &stat);
-
-protected:
-  mutable std::mutex lock_;
-  std::mutex abstractLock_;  // see note on updaterStat
-  // each freqency for each barrier trainer
-  std::vector<struct Abstract> abstract_;
-  // it is valuable when do perf-tuining, if lastTrainerId acts uniform
-  // distribution
-  struct Abstract totAbstract_;
-  uint64_t totSamples_;
-
-protected:
-  uint16_t numConnThreads_;  // total updates needed
-  float rateThreshold_;
-  std::string name_;
-};
-
-// the end-time of arriving real/forged barrier position
-class BarrierEndStat : public BarrierStatBase {
-public:
-  BarrierEndStat(uint16_t numConnThreads, const std::string &name);
-  ~BarrierEndStat() {}
-
-  virtual void updateStat(struct timeval &cur, int32_t trainerId = -1);
-  virtual void updateStat(uint64_t delta, int32_t trainerId = -1) {
-    LOG(INFO) << "have no delta updateStat in BarrierEndStat";
-  }
-  virtual void reset(bool clearRawData = true);
-  virtual bool checkPassBarrier() { return timeVector_->empty(); }
-
-protected:
-  /*
-   * LOG:
-   * readAllBlocks_denseUpdater
-   * trainerId      avgGap         avgSecondGap   avgLastTwoGap  avgMidGap rate
-   * 44             86.702         81.022         9.984          50.472 0.144737
-   * 46             87.723         82.939         8.737          50.019 0.118421
-   * 35             100.923        96.752         14.305         61.979
-   * 0.0657895
-   * log_barrier_abstract, log_barrier_lowest_nodes, log_barrier_threshold
-   * control details.
-   */
-  virtual void showAbstract(std::ostream &output) const;
-
-private:
-  std::unique_ptr<TimeVectorEnd> timeVector_;
-};
-
-// the delta-time from different trainers,
-// eg, find the degree of imbalance of BP time at pserver end
-// the entry value in timerVector_ is BP delta, do evaluation to BP delta.
-class BarrierDeltaStat : public BarrierStatBase {
-public:
-  BarrierDeltaStat(uint16_t numConnThreads, const std::string &name);
-  ~BarrierDeltaStat() {}
-
-  virtual void updateStat(uint64_t delta, int32_t trainerId = -1);
-  virtual void updateStat(struct timeval &cur, int32_t trainerId = -1) {
-    LOG(INFO) << "have no timeval updateStat in BarrierDeltaStat";
-  }
-
-  virtual void reset(bool clearRawData = true);
-
-  virtual bool checkPassBarrier() { return timeVector_->empty(); }
-
-protected:
-  virtual void showAbstract(std::ostream &outPut) const;
-
-private:
-  // store delta time in uint64_t, eg BP time of all trainers
-  std::unique_ptr<TimeVectorDelta> timeVector_;
-};
-
-// to distinguish different contexts for same parallel threads, and different
-// threads with same code-sgement, just use tagName to tag the run-time
-// position.
-// in Sparse, sendParallel threads can not only run in the stage of push&pull
-// with same thread group, but also run in the stage of pull&push with different
-// thread group, tag will be used to distinguish different run-time barrier
-// position.
-// trainerId in REGISTER_BARRIER_TIMER_SERVER is used to retreive lowest trainer
-// nodes.
-
-// end barrier
-#define __REGISTER_BARRIER_TIMER_SERVER(                            \
-    set, statName, numConnThreads, trainerId, ...)                  \
-  do {                                                              \
-    if (numConnThreads > 2) {                                       \
-      std::string internalName =                                    \
-          std::string(statName) + std::string(__VA_ARGS__);         \
-      BarrierStatPtr __stat =                                       \
-          (set).getStat(numConnThreads, internalName, BARRIER_END); \
-      struct timeval cur;                                           \
-      gettimeofday(&cur, nullptr);                                  \
-      __stat->updateStat(cur, trainerId);                           \
-    }                                                               \
-  } while (0);
-
-// end barrier with user-defined timer
-#define __REGISTER_BARRIER_TIMER_SERVER_SET(                        \
-    set, statName, numConnThreads, trainerId, cur, ...)             \
-  do {                                                              \
-    if (numConnThreads > 2) {                                       \
-      std::string internalName =                                    \
-          std::string(statName) + std::string(__VA_ARGS__);         \
-      BarrierStatPtr __stat =                                       \
-          (set).getStat(numConnThreads, internalName, BARRIER_END); \
-      __stat->updateStat(cur, trainerId);                           \
-    }                                                               \
-  } while (0);
-
-// delta barrier
-#define __REGISTER_BARRIER_DELTA_SERVER_SET(                          \
-    set, statName, numConnThreads, trainerId, delta, ...)             \
-  do {                                                                \
-    if (numConnThreads > 2) {                                         \
-      std::string internalName =                                      \
-          std::string(statName) + std::string(__VA_ARGS__);           \
-      BarrierStatPtr __stat =                                         \
-          (set).getStat(numConnThreads, internalName, BARRIER_DELTA); \
-      __stat->updateStat(delta, trainerId);                           \
-    }                                                                 \
-  } while (0);
-
-// check end barrier
-#define __CHECK_BARRIER_TIMER(set, statName, numConnThreads, ...)   \
-  do {                                                              \
-    std::string internalName =                                      \
-        std::string(statName) + std::string(__VA_ARGS__);           \
-    BarrierStatPtr __stat =                                         \
-        (set).getStat(numConnThreads, internalName, BARRIER_END);   \
-    PCHECK(__stat->checkPassBarrier()) << internalName              \
-                                       << ": invalid barrier data"; \
-  } while (0);
-
-/*
- * Note:
- * with sync-sgd algriothm in cluster mode, lots of synchronize action exsit at
- * pserve end. these synchronizaton actions have impact on the efficiency of
- * parameter exchange. the synchronizaton(barrier) GAP is composed of lots of
- * factors, such as the forwardBackward variance, network fluncation. we try
- * to have a quantitative analysis on these factor, so we design lots of barrier
- * time to capture these performance. these barrier also can be placed at
- * implict barrier position.
- *
- * example:
- * in sync-sgd algorithm, each parameter server waits for all gradients from
- * all trainers, thus, an explict barrier point exsit before doing optimization.
- * the barrier timer located before the point can sense the barrier condition.
- *
- */
-
-// try to capture which trainer is slowest node in sync-sgd at pserver.
-#define REGISTER_SLOW_NODES_PROBE(                 \
-    set, statName, numConnThreads, trainerId, ...) \
-  __REGISTER_BARRIER_TIMER_SERVER(                 \
-      (set), statName, numConnThreads, trainerId, __VA_ARGS__)
-// try to check if all threads or trainers have passed barriers for data
-// accuracy.
-#define CHECK_BARRIER_TIMER(set, statName, numConnThreads, ...) \
-  __CHECK_BARRIER_TIMER((set), statName, numConnThreads, __VA_ARGS__)
-
-#ifdef PADDLE_DISABLE_TIMER
-
-#define REGISTER_BARRIER_TIMER_SERVER( \
-    set, statName, numConnThreads, trainerId, ...)
-#define REGISTER_BARRIER_TIMER_SERVER_SET( \
-    set, statName, numConnThreads, trainerId, cur, ...)
-#define REGISTER_BARRIER_DELTA_SERVER_SET( \
-    set, statName, numConnThreads, trainerId, cur, ...)
-
-#else
-
-/*
- * sensing barrier time distribution for all parallelization threads.
- * it provides low API for slow node check(REGISTER_SLOW_NODES_PROBE)
- */
-#define REGISTER_BARRIER_TIMER_SERVER(             \
-    set, statName, numConnThreads, trainerId, ...) \
-  __REGISTER_BARRIER_TIMER_SERVER(                 \
-      (set), statName, numConnThreads, trainerId, __VA_ARGS__)
-
-/*
- * sensing barrier time distribution for all parallelization threads.
- * but time point for barrier performance is set by user.
- * eg, with this api, you can get implict barrier point such as the beginning
- * time distribution
- * for receiving data.
- */
-#define REGISTER_BARRIER_TIMER_SERVER_SET(              \
-    set, statName, numConnThreads, trainerId, cur, ...) \
-  __REGISTER_BARRIER_TIMER_SERVER_SET(                  \
-      (set), statName, numConnThreads, trainerId, cur, __VA_ARGS__)
-
-// try to capture time delta from all trainers, such as forwardBackward time
-// which implies
-// computation fluctuation
-#define REGISTER_BARRIER_DELTA_SERVER_SET(                \
-    set, statName, numConnThreads, trainerId, delta, ...) \
-  __REGISTER_BARRIER_DELTA_SERVER_SET(                    \
-      (set), statName, numConnThreads, trainerId, delta, __VA_ARGS__)
-
-#endif  // DISABLE_TIMER
-}  // namespace paddle

paddle/utils/Stat.cpp

@@ -97,34 +97,6 @@ std::ostream& operator<<(std::ostream& outPut, const Stat& stat) {
   return outPut;
 }
 
-BarrierStatPtr StatSet::getStat(uint16_t numConnThreads,
-                                const std::string& name,
-                                BarrierStatType bType) {
-  {
-    ReadLockGuard guard(lock_);
-    auto it = barrierStatSet_.find(name);
-    if (it != barrierStatSet_.end()) {
-      return it->second;
-    }
-  }
-
-  std::lock_guard<RWLock> guard(lock_);
-  // test again with lock_guard
-  auto it = barrierStatSet_.find(name);
-  if (it != barrierStatSet_.end()) {
-    return it->second;
-  }
-
-  BarrierStatPtr stat;
-  if (bType == BARRIER_END) {
-    stat = std::make_shared<BarrierEndStat>(numConnThreads, name);
-  } else if (bType == BARRIER_DELTA) {
-    stat = std::make_shared<BarrierDeltaStat>(numConnThreads, name);
-  }
-  auto ret = barrierStatSet_.insert(std::make_pair(name, stat));
-  return ret.first->second;
-}
-
 void StatSet::printSegTimerStatus() {
   ReadLockGuard guard(lock_);
   LOG(INFO) << std::setiosflags(std::ios::left) << std::setfill(' ')
@@ -135,46 +107,20 @@ void StatSet::printSegTimerStatus() {
   }
 }
 
-void StatSet::printBarrierTimerStatus() {
-  ReadLockGuard guard(lock_);
-  if (barrierStatSet_.empty()) {
-    return;
-  }
-  // control barrierAbstact in runtime, so enable compliation
-  LOG(INFO) << std::setiosflags(std::ios::left) << std::setfill(' ')
-            << "======= BarrierStatSet status ======" << std::endl;
-  for (auto& stat : barrierStatSet_) {
-    LOG(INFO) << std::setiosflags(std::ios::left) << std::setfill(' ')
-              << *(stat.second);
-  }
-}
-
 void StatSet::printAllStatus() {
 #ifndef PADDLE_DISABLE_TIMER
   printSegTimerStatus();
 #endif
-  printBarrierTimerStatus();
   LOG(INFO) << std::setiosflags(std::ios::left)
             << "--------------------------------------------------"
             << std::endl;
 }
 
-void StatSet::printStatus(const std::string& name) {
-  ReadLockGuard guard(lock_);
-  auto iter = statSet_.find(name);
-  CHECK(iter != statSet_.end()) << name << " is not registed in " << name_;
-  LOG(INFO) << *(iter->second);
-}
-
 void StatSet::reset(bool clearRawData) {
   ReadLockGuard guard(lock_);
   for (auto& stat : statSet_) {
     stat.second->reset();
   }
-  // reset barrierStat
-  for (auto& stat : barrierStatSet_) {
-    stat.second->reset(clearRawData);
-  }
 }
 
 void StatSet::setThreadInfo(const std::string& name, bool flag) {
@@ -184,13 +130,6 @@ void StatSet::setThreadInfo(const std::string& name, bool flag) {
   iter->second->setThreadInfo(flag);
 }
 
-void StatSet::deleteStat(const std::string& name) {
-  std::lock_guard<RWLock> guard(lock_);
-  auto iter = statSet_.find(name);
-  CHECK(iter != statSet_.end()) << name << " is not registed in " << name_;
-  statSet_.erase(iter);
-}
-
 StatInfo::~StatInfo() {
   if (stat_) {
     std::lock_guard<std::mutex> guard(stat_->lock_);

paddle/utils/Stat.h

@@ -23,7 +23,6 @@ limitations under the License. */
 #include <string>
 #include <unordered_map>
 
-#include "BarrierStat.h"
 #include "Locks.h"
 #include "Logging.h"
 #include "ThreadLocal.h"
@@ -60,12 +59,6 @@ public:
 
 class Stat;
 typedef std::shared_ptr<Stat> StatPtr;
-typedef std::shared_ptr<BarrierStatBase> BarrierStatPtr;
-
-enum BarrierStatType {
-  BARRIER_END = 0,
-  BARRIER_DELTA = 1,
-};
 
 class StatSet {
 public:
@@ -74,11 +67,8 @@ public:
 
   // print to LOG(INFO)
   void printSegTimerStatus();
-  void printBarrierTimerStatus();
   void printAllStatus();
 
-  void printStatus(const std::string& name);
-
   StatPtr getStat(const std::string& name) {
     {
       ReadLockGuard guard(lock_);
@@ -93,12 +83,6 @@ public:
     return ret.first->second;
   }
 
-  BarrierStatPtr getStat(uint16_t numConnThreads,
-                         const std::string& name,
-                         BarrierStatType bType);
-
-  void deleteStat(const std::string& name);
-
   // true for showing stats for each thread
   // false for showing stats aggragated over threads
   void setThreadInfo(const std::string& name, bool flag);
@@ -120,7 +104,6 @@ public:
 
 private:
   std::unordered_map<std::string, StatPtr> statSet_;
-  std::unordered_map<std::string, BarrierStatPtr> barrierStatSet_;
   const std::string name_;
   RWLock lock_;
 };

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

@@ -2511,10 +2511,14 @@ 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)
@@ -2776,11 +2780,15 @@ 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

@@ -1247,10 +1247,19 @@ 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
@@ -1269,6 +1278,8 @@ 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.
@@ -1286,12 +1297,16 @@ 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(
@@ -1553,7 +1568,7 @@ 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.
@@ -1609,7 +1624,7 @@ 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)))