Merge pull request #10165 from JiayiFeng/fix_Clang_compile_error

fix Clang compile errors

paddle/gserver/dataproviders/PyDataProvider2.cpp

@@ -390,9 +390,7 @@ private:
 
       if (this->loadThread_) {  // wait poolActualSize < poolSize;
         std::unique_lock<std::mutex> l(mtx_);
-        pushCV_.wait(l, [this, additionalBatchSize] {
-          return this->poolActualSize_ < poolSize_;
-        });
+        pushCV_.wait(l, [this] { return this->poolActualSize_ < poolSize_; });
       }
 
       {

paddle/gserver/gradientmachines/MultiGradientMachine.cpp

@@ -52,7 +52,7 @@ MultiGradientMachine::MultiGradientMachine(const ModelConfig& config,
   } else {
     numDevices_ = 0;
   }
-  ParamInitCallback mainParamInitCb = [this](int paramId, Parameter* para) {
+  ParamInitCallback mainParamInitCb = [](int paramId, Parameter* para) {
     // only create buf for CPU parameters
     // GPU parameters will be created in each thread
     if (para->useGpu()) return;

paddle/gserver/layers/RecurrentLayerGroup.cpp

@@ -72,7 +72,7 @@ void RecurrentLayerGroup::initSubNetwork(
   setNeedGradient(true);
 
   network_.reset(new RecurrentGradientMachine(config_.name(), rootNetwork));
-  ParamInitCallback cb = [this, rootNetwork](int paramId, Parameter* para) {
+  ParamInitCallback cb = [rootNetwork](int paramId, Parameter* para) {
     para->enableSharedType(
         PARAMETER_VALUE,
         rootNetwork->getParameters()[paramId]->getBuf(PARAMETER_VALUE),

paddle/parameter/Argument.cpp

@@ -325,7 +325,7 @@ void Argument::concat(const std::vector<Argument>& args,
         ->copyFrom(*src->subVec(srcStartRow, size), stream);
   };
 
-  auto copyStrs = [batchSize, stream](SVectorPtr& dst,
+  auto copyStrs = [batchSize](SVectorPtr& dst,
                               const SVectorPtr& src,
                               int desStartRow,
                               int srcStartRow,
@@ -413,7 +413,7 @@ void Argument::concat(const std::vector<Argument>& args,
     dst->subVec(startRow, src->getSize())->copyFrom(*src, stream);
   };
 
-  auto copyStrs = [batchSize, stream](
+  auto copyStrs = [batchSize](
       SVectorPtr& dst, const SVectorPtr& src, int startRow, bool useGpu) {
     if (!src) {
       dst.reset();

paddle/parameter/AverageOptimizer.cpp

@@ -81,7 +81,7 @@ ParameterOptimizer::TraverseCallback AverageOptimizer::needSpecialTraversal(
   if (numUpdates_ % kMaxNumAccumulates == 0) {
     // Move the sum to a different buffer to avoid loss of precision
     // due to too many sums.
-    callbacks.emplace_back([this](const VectorPtr vecs[],
+    callbacks.emplace_back([](const VectorPtr vecs[],
                               const ParameterConfig& config,
                               size_t sparseId) {
       vecs[PARAMETER_SUM2]->add(*vecs[PARAMETER_SUM1]);
@@ -94,7 +94,7 @@ ParameterOptimizer::TraverseCallback AverageOptimizer::needSpecialTraversal(
     if (auto callback = this->startCatchUpWith()) {
       callbacks.emplace_back(callback);
     }
-    callbacks.emplace_back([this](const VectorPtr vecs[],
+    callbacks.emplace_back([](const VectorPtr vecs[],
                               const ParameterConfig& config,
                               size_t sparseId) {
       vecs[PARAMETER_SUM3]->add(*vecs[PARAMETER_SUM1], *vecs[PARAMETER_SUM2]);

paddle/parameter/FirstOrderOptimizer.cpp

@@ -145,7 +145,7 @@ AdagradParameterOptimizer::needSpecialTraversal(
   if (numUpdates_ % kMaxNumAccumulates == 0) {
     // Move the sum to a different buffer to avoid loss of precision
     // due to too many sums.
-    return [this](const VectorPtr vecs[],
+    return [](const VectorPtr vecs[],
               const ParameterConfig& config,
               size_t sparseId) {
       vecs[PARAMETER_GRADIENT_SQURESUM]->add(