【Hackathon 6th Fundable Projects 2 No.2】Fix bugprone-branch-clone-final

paddle/fluid/distributed/ps/table/ctr_accessor.cc

@@ -281,7 +281,7 @@ int32_t CtrCommonAccessor::Update(float** update_values,
 bool CtrCommonAccessor::CreateValue(int stage, const float* value) {
   // stage == 0, pull
   // stage == 1, push
-  if (stage == 0) {
+  if (stage == 0) {  // NOLINT
     return true;
   } else if (stage == 1) {
     // operation

paddle/fluid/distributed/ps/table/ctr_double_accessor.cc

@@ -289,7 +289,7 @@ int32_t CtrDoubleAccessor::Update(float** update_values,
 bool CtrDoubleAccessor::CreateValue(int stage, const float* value) {
   // stage == 0, pull
   // stage == 1, push
-  if (stage == 0) {
+  if (stage == 0) {  // NOLINT
     return true;
   } else if (stage == 1) {
     auto show = CtrDoublePushValue::Show(const_cast<float*>(value));

paddle/fluid/distributed/ps/table/ctr_dymf_accessor.cc

@@ -310,7 +310,7 @@ int32_t CtrDymfAccessor::Update(float** update_values,
 bool CtrDymfAccessor::CreateValue(int stage, const float* value) {
   // stage == 0, pull
   // stage == 1, push
-  if (stage == 0) {
+  if (stage == 0) {  // NOLINT
     return true;
   } else if (stage == 1) {
     // operation

paddle/fluid/distributed/ps/table/memory_dense_table.cc

@@ -103,7 +103,7 @@ int32_t MemoryDenseTable::InitializeOptimizer() {
   auto name = common.name();
   auto attrs = common.attributes();
 
-  if (name == "sgd") {
+  if (name == "sgd") {  // NOLINT
     optimizer_ = std::make_shared<DSGD>(common, &values_);
     optimizer_->SetGlobalLR(_global_lr);
   } else if (name == "adam") {

paddle/fluid/distributed/ps/table/sparse_accessor.cc

@@ -244,7 +244,7 @@ int32_t SparseAccessor::Update(float** update_values,
 bool SparseAccessor::CreateValue(int stage, const float* value) {
   // stage == 0, pull
   // stage == 1, push
-  if (stage == 0) {
+  if (stage == 0) {  // NOLINT
     return true;
   } else if (stage == 1) {
     // operation

paddle/fluid/distributed/ps/table/ssd_sparse_table.cc

@@ -882,7 +882,7 @@ int32_t SSDSparseTable::SaveWithStringMultiOutput(const std::string& path,
                            int shard_num,
                            int part_num,
                            int split_num) {
-      if (compress && (save_param == 0 || save_param == 3)) {
+      if (compress && (save_param == 0 || save_param == 3)) {  // NOLINT
         // return
         // ::paddle::string::format_string("%s/part-%03d-%05d-%03d-%03d.gz",
         //     table_path, node_num, shard_num, part_num, split_num);
@@ -1191,7 +1191,7 @@ int32_t SSDSparseTable::SaveWithStringMultiOutput_v2(const std::string& path,
                            int part_num,
                            int split_num,
                            const char* prefix = "") {
-      if (compress && (save_param == 0 || save_param == 3)) {
+      if (compress && (save_param == 0 || save_param == 3)) {  // NOLINT
         return ::paddle::string::format_string("%s/%s/part-%05d-%03d.gz",
                                                table_path,
                                                prefix,
@@ -1624,7 +1624,7 @@ int32_t SSDSparseTable::SaveWithBinary(const std::string& path,
                            int shard_num,
                            int part_num,
                            int split_num) {
-      if (compress && (save_param == 0 || save_param == 3)) {
+      if (compress && (save_param == 0 || save_param == 3)) {  // NOLINT
         return paddle::string::format_string("%s/part-%03d-%05d-%03d-%03d.gz",
                                              table_path,
                                              node_num,
@@ -1945,7 +1945,7 @@ int32_t SSDSparseTable::SaveWithBinary_v2(const std::string& path,
                            int part_num,
                            int split_num,
                            const char* prefix = "") {
-      if (compress && (save_param == 0 || save_param == 3)) {
+      if (compress && (save_param == 0 || save_param == 3)) {  // NOLINT
         return paddle::string::format_string(
             "%s/%s/part-%03d-%05d-%03d-%03d.gz",
             table_path,

paddle/fluid/framework/data_feed.cc

@@ -2132,7 +2132,7 @@ void SlotRecordInMemoryDataFeed::Init(const DataFeedDesc& data_feed_desc) {
   size_t pos = pipe_command_.find(".so");
   if (pos != std::string::npos) {  // NOLINT
     pos = pipe_command_.rfind('|');
-    if (pos == std::string::npos) {
+    if (pos == std::string::npos) {  // NOLINT
       so_parser_name_ = pipe_command_;
       pipe_command_.clear();
     } else {

paddle/fluid/framework/hogwild_worker.cc

@@ -1400,7 +1400,7 @@ void HogwildWorker::TrainFilesWithProfiler() {
     timeline.Pause();
     read_time += timeline.ElapsedSec();
     total_time += timeline.ElapsedSec();
-    if (infer_out_of_ins) {
+    if (infer_out_of_ins) {  // NOLINT
       for (size_t i = 0; i < ops_.size(); ++i) {
         timeline.Start();
         auto &op = ops_[i];
@@ -1620,7 +1620,7 @@ void HogwildWorker::TrainFiles() {
     if (cur_batch <= 0 && !infer_out_of_ins) {
       break;
     }
-    if (infer_out_of_ins) {
+    if (infer_out_of_ins) {  // NOLINT
       for (auto &op : ops_) {
         if (op->Type() == "c_broadcast") {
           op->Run(*thread_scope_, place_);

paddle/fluid/framework/new_executor/pir_interpreter.cc

@@ -779,7 +779,7 @@ void PirInterpreter::BuildInstruction() {
         continue;
       }
     } else if (op.dialect()->name() == "cf") {
-      if (op.isa<pir::TuplePushOp>()) {
+      if (op.isa<pir::TuplePushOp>()) {  // NOLINT
         CREATE_INSTR(TuplePushInstruction);
       } else if (op.isa<pir::TuplePopOp>()) {
         CREATE_INSTR(TuplePopInstruction);
@@ -892,7 +892,7 @@ void PirInterpreter::BuildInstruction() {
                          .AsString();
       VLOG(6) << "process " << op_name;
 
-      if (op.isa<paddle::dialect::OneDNNPhiKernelOp>()) {
+      if (op.isa<paddle::dialect::OneDNNPhiKernelOp>()) {  // NOLINT
         CREATE_INSTR(OneDNNPhiKernelInstruction);
       } else if (op.isa<paddle::dialect::OneDNNMixedPhiKernelOp>()) {
         CREATE_INSTR(OneDNNMixedPhiKernelInstruction);

paddle/fluid/framework/operator.cc

@@ -1857,16 +1857,14 @@ void OperatorWithKernel::RunImpl(const Scope& scope,
 // 2. Whether this op has specific implementation;
 // 3. Whether onednn kernel can be used.
 #ifdef PADDLE_WITH_DNNL
-      if (!this->DnnFallback() &&
-          !paddle::platform::in_mkldnn_white_list(type_) &&
-          this->CanMKLDNNBeUsed(exe_ctx, kernel_type_->data_type_)) {
-        kernel_type_->library_type_ = framework::LibraryType::kMKLDNN;
-        kernel_type_->data_layout_ = framework::DataLayout::ONEDNN;
-      } else if (platform::is_cpu_place(kernel_type_->place_) &&
-                 kernel_type_->data_type_ ==
-                     proto::VarType::Type::VarType_Type_BF16 &&
-                 !this->SupportsCPUBF16() &&
-                 this->SupportsMKLDNN(phi::DataType::BFLOAT16)) {
+      if ((!this->DnnFallback() &&
+           !paddle::platform::in_mkldnn_white_list(type_) &&
+           this->CanMKLDNNBeUsed(exe_ctx, kernel_type_->data_type_)) ||
+          (platform::is_cpu_place(kernel_type_->place_) &&
+           kernel_type_->data_type_ ==
+               proto::VarType::Type::VarType_Type_BF16 &&
+           !this->SupportsCPUBF16() &&
+           this->SupportsMKLDNN(phi::DataType::BFLOAT16))) {
         kernel_type_->library_type_ = framework::LibraryType::kMKLDNN;
         kernel_type_->data_layout_ = framework::DataLayout::ONEDNN;
       }
@@ -2191,15 +2189,13 @@ OpKernelType OperatorWithKernel::InnerGetExpectedKernelType(
 // 2. Whether this op has specific implementation;
 // 3. Whether onednn kernel can be used.
 #ifdef PADDLE_WITH_DNNL
-  if (!this->DnnFallback() && !paddle::platform::in_mkldnn_white_list(type_) &&
-      this->CanMKLDNNBeUsed(ctx, expected_kernel_key.data_type_)) {
-    expected_kernel_key.library_type_ = framework::LibraryType::kMKLDNN;
-    expected_kernel_key.data_layout_ = framework::DataLayout::ONEDNN;
-  } else if (platform::is_cpu_place(expected_kernel_key.place_) &&
-             expected_kernel_key.data_type_ ==
-                 proto::VarType::Type::VarType_Type_BF16 &&
-             !this->SupportsCPUBF16() &&
-             this->SupportsMKLDNN(phi::DataType::BFLOAT16)) {
+  if ((!this->DnnFallback() && !paddle::platform::in_mkldnn_white_list(type_) &&
+       this->CanMKLDNNBeUsed(ctx, expected_kernel_key.data_type_)) ||
+      (platform::is_cpu_place(expected_kernel_key.place_) &&
+       expected_kernel_key.data_type_ ==
+           proto::VarType::Type::VarType_Type_BF16 &&
+       !this->SupportsCPUBF16() &&
+       this->SupportsMKLDNN(phi::DataType::BFLOAT16))) {
     expected_kernel_key.library_type_ = framework::LibraryType::kMKLDNN;
     expected_kernel_key.data_layout_ = framework::DataLayout::ONEDNN;
   }

paddle/fluid/framework/program_converter.cc

@@ -140,8 +140,6 @@ void ConvertAssignValueOp(OpDesc* op) {
       op->SetAttr("bool_values", ExtractPlainVector<int>(values));
       break;
     case phi::DataType::FLOAT32:
-      op->SetAttr("fp32_values", ExtractPlainVector<float>(values));
-      break;
     case phi::DataType::FLOAT64:
       op->SetAttr("fp32_values", ExtractPlainVector<float>(values));
       break;

paddle/fluid/inference/tensorrt/convert/prelu_op.cc

@@ -80,22 +80,17 @@ class PReluOpConverter : public OpConverter {
           hw_tensor = Add1DConstantLayer(
               std::vector<int32_t>(input_dims.nbDims - 2, 1));
         }
-        if (data_format == "NCHW") {
-          if (hw_tensor != nullptr) {
+        if (hw_tensor != nullptr) {
+          if (data_format == "NCHW") {
             shape_tensor = Concat(
                 std::vector<nvinfer1::ITensor*>{n_tensor, c_tensor, hw_tensor});
           } else {
-            shape_tensor =
-                Concat(std::vector<nvinfer1::ITensor*>{n_tensor, c_tensor});
-          }
-        } else {
-          if (hw_tensor != nullptr) {
             shape_tensor = Concat(
                 std::vector<nvinfer1::ITensor*>{n_tensor, hw_tensor, c_tensor});
-          } else {
-            shape_tensor =
-                Concat(std::vector<nvinfer1::ITensor*>{n_tensor, c_tensor});
           }
+        } else {
+          shape_tensor =
+              Concat(std::vector<nvinfer1::ITensor*>{n_tensor, c_tensor});
         }
         reshape_layer->setInput(1, *shape_tensor);
       } else {

paddle/fluid/memory/allocation/allocator_facade.cc

@@ -436,10 +436,11 @@ class AllocatorFacadePrivate {
 
   const std::shared_ptr<Allocator> GetDefaultStreamSafeCUDAAllocator(
       const platform::CUDAPlace& place) const {
-    if (auto iter = default_stream_safe_cuda_allocators_.find(place);
+    if (auto iter = default_stream_safe_cuda_allocators_.find(place);  // NOLINT
         iter != default_stream_safe_cuda_allocators_.end())
       return iter->second;
-    if (auto iter = default_cuda_malloc_async_allocators_.find(place);
+    if (auto iter =
+            default_cuda_malloc_async_allocators_.find(place);  // NOLINT
         iter != default_cuda_malloc_async_allocators_.end())
       return iter->second;
     PADDLE_THROW(platform::errors::NotFound(

paddle/fluid/pir/drr/src/rewrite_pattern.cc

@@ -507,7 +507,7 @@ MatchContextImpl DrrRewritePattern::CreateOperations(
       auto ir_val = res_match_ctx.GetIrValue(input->name());
       if (ir_val) {
         pir::Operation* ir_input_op = ir_val.defining_op();
-        if (op_2_temp_program_index.count(ir_input_op) == 0) {
+        if (op_2_temp_program_index.count(ir_input_op) == 0) {  // NOLINT
           // do nothing
         } else if (max_res_idx < op_2_temp_program_index.at(ir_input_op)) {
           max_res_idx = op_2_temp_program_index.at(ir_input_op);

paddle/fluid/pir/transforms/gpu/transpose_flatten_concat_fuse_pass.cc

@@ -112,7 +112,7 @@ class NTransposeFlattenConcatFusePattern : public paddle::drr::DrrPatternBase {
         res.ComputeAttr([](const paddle::drr::MatchContext &match_ctx) -> int {
           int start_axis = match_ctx.Attr<int>("start_axis_0");
           int stop_axis = match_ctx.Attr<int>("stop_axis_0");
-          if (start_axis == stop_axis) {
+          if (start_axis == stop_axis) {  // NOLINT
             return start_axis;
           } else if (start_axis == 0) {
             return stop_axis + 1;

paddle/fluid/pir/transforms/onednn/reshape_transpose_matmul_fuse_pass.cc

@@ -220,7 +220,7 @@ class ReshapeTransposeFusedMatmulFusePattern
     });
 
     pat.AddConstraint([&](const paddle::drr::MatchContext &match_ctx) {
-      if (as_x_) {
+      if (as_x_) {  // NOLINT
         if (!(match_ctx.Attr<std::vector<int>>("fused_reshape_x").empty()))
           return false;
       } else {

paddle/fluid/platform/profiler.cc

@@ -283,10 +283,12 @@ RecordMemEvent::RecordMemEvent(const void *ptr,
             RecordMemEvent::size_cache["gpu"][place.GetDeviceId()][3];
         RecordMemEvent::has_initialized["gpu"][place.GetDeviceId()] = true;
       } else {
-        current_reserved = DEVICE_MEMORY_STAT_CURRENT_VALUE(
-            Reserved, place.GetDeviceId());  // NOLINT
-        peak_reserved = DEVICE_MEMORY_STAT_PEAK_VALUE(
-            Reserved, place.GetDeviceId());  // NOLINT
+        current_reserved = DEVICE_MEMORY_STAT_CURRENT_VALUE(  // NOLINT
+            Reserved,
+            place.GetDeviceId());
+        peak_reserved = DEVICE_MEMORY_STAT_PEAK_VALUE(  // NOLINT
+            Reserved,
+            place.GetDeviceId());
         RecordMemEvent::size_cache["gpu"][place.GetDeviceId()][1] =
             current_reserved;
         RecordMemEvent::size_cache["gpu"][place.GetDeviceId()][3] =
@@ -449,10 +451,12 @@ RecordMemEvent::RecordMemEvent(const void *ptr,
             RecordMemEvent::size_cache["gpu"][place.GetDeviceId()][3];
         RecordMemEvent::has_initialized["gpu"][place.GetDeviceId()] = true;
       } else {
-        current_reserved = DEVICE_MEMORY_STAT_CURRENT_VALUE(
-            Reserved, place.GetDeviceId());  // NOLINT
-        peak_reserved = DEVICE_MEMORY_STAT_PEAK_VALUE(
-            Reserved, place.GetDeviceId());  // NOLINT
+        current_reserved = DEVICE_MEMORY_STAT_CURRENT_VALUE(  // NOLINT
+            Reserved,
+            place.GetDeviceId());
+        peak_reserved = DEVICE_MEMORY_STAT_PEAK_VALUE(  // NOLINT
+            Reserved,
+            place.GetDeviceId());
         RecordMemEvent::size_cache["gpu"][place.GetDeviceId()][1] =
             current_reserved;
         RecordMemEvent::size_cache["gpu"][place.GetDeviceId()][3] =

paddle/phi/api/lib/kernel_dispatch.cc

@@ -66,16 +66,17 @@ BackendSet GetTensorBackendSet(const phi::TensorBase& t) {
     phi::Backend backend_key = phi::TransToPhiBackend(t.place());
     BackendSet backend_set(backend_key);
     VLOG(10) << "update BackendSet by tensor: add [" << backend_key << "]";
-    if (backend_key == Backend::GPU && phi::DenseTensor::classof(&t) &&
-        static_cast<const phi::DenseTensor&>(t).meta().use_gpudnn) {
-      backend_set = backend_set | BackendSet(Backend::GPUDNN);
-    } else if (backend_key == Backend::GPU &&
-               phi::distributed::DistTensor::classof(&t) &&
-               static_cast<const phi::distributed::DistTensor&>(t)
-                   .value()
-                   .meta()
-                   .use_gpudnn) {
-      backend_set = backend_set | BackendSet(Backend::GPUDNN);
+    if (backend_key == Backend::GPU) {
+      if (phi::DenseTensor::classof(&t) &&
+          static_cast<const phi::DenseTensor&>(t).meta().use_gpudnn) {
+        backend_set = backend_set | BackendSet(Backend::GPUDNN);
+      } else if (phi::distributed::DistTensor::classof(&t) &&
+                 static_cast<const phi::distributed::DistTensor&>(t)
+                     .value()
+                     .meta()
+                     .use_gpudnn) {
+        backend_set = backend_set | BackendSet(Backend::GPUDNN);
+      }
     }
     return backend_set;
   }

paddle/phi/backends/dynload/dynamic_loader.cc

@@ -350,7 +350,7 @@ void* GetCublasDsoHandle() {
 #if defined(__APPLE__) || defined(__OSX__)
   return GetDsoHandleFromSearchPath(FLAGS_cuda_dir, "libcublas.dylib");
 #elif defined(_WIN32) && defined(PADDLE_WITH_CUDA)
-  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {
+  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {  // NOLINT
 #ifdef PADDLE_WITH_PIP_CUDA_LIBRARIES
     return GetDsoHandleFromSearchPath(FLAGS_cuda_dir, "cublas64_11.dll");
 #else
@@ -371,7 +371,7 @@ void* GetCublasDsoHandle() {
     return nullptr;
   }
 #elif defined(__linux__) && defined(PADDLE_WITH_CUDA)
-  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {
+  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {  // NOLINT
 #ifdef PADDLE_WITH_PIP_CUDA_LIBRARIES
     return GetDsoHandleFromSearchPath(FLAGS_cublas_dir, "libcublas.so.11");
 #else
@@ -399,7 +399,7 @@ void* GetCublasDsoHandle() {
 void* GetCublasLtDsoHandle() {
 // APIs available after CUDA 10.1
 #if defined(__linux__) && defined(PADDLE_WITH_CUDA)
-  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {
+  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {  // NOLINT
 #ifdef PADDLE_WITH_PIP_CUDA_LIBRARIES
     return GetDsoHandleFromSearchPath(FLAGS_cublas_dir, "libcublasLt.so.11");
 #else
@@ -487,7 +487,7 @@ void* GetCUPTIDsoHandle() {
   return GetDsoHandleFromSearchPath(
       FLAGS_cupti_dir, "libcupti.dylib", false, {cupti_lib_path});
 #elif defined(__linux__) && defined(PADDLE_WITH_CUDA)
-  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {
+  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {  // NOLINT
 #ifdef PADDLE_WITH_PIP_CUDA_LIBRARIES
     return GetDsoHandleFromSearchPath(
         FLAGS_cupti_dir, "libcupti.so.11.8", false, {cupti_lib_path});
@@ -584,7 +584,7 @@ void* GetCusparseDsoHandle() {
 #if defined(__APPLE__) || defined(__OSX__)
   return GetDsoHandleFromSearchPath(FLAGS_cuda_dir, "libcusparse.dylib");
 #elif defined(_WIN32) && defined(PADDLE_WITH_CUDA)
-  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {
+  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {  // NOLINT
 #ifdef PADDLE_WITH_PIP_CUDA_LIBRARIES
     return GetDsoHandleFromSearchPath(FLAGS_cuda_dir, "cusparse64_11.dll");
 #else
@@ -605,7 +605,7 @@ void* GetCusparseDsoHandle() {
     return nullptr;
   }
 #elif defined(__linux__) && defined(PADDLE_WITH_CUDA)
-  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {
+  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {  // NOLINT
 #ifdef PADDLE_WITH_PIP_CUDA_LIBRARIES
     return GetDsoHandleFromSearchPath(FLAGS_cusparse_dir, "libcusparse.so.11");
 #else
@@ -781,7 +781,7 @@ void* GetCUFFTDsoHandle() {
 #if defined(__APPLE__) || defined(__OSX__)
   return GetDsoHandleFromSearchPath(FLAGS_cuda_dir, "libcufft.dylib");
 #elif defined(__linux__) && defined(PADDLE_WITH_CUDA)
-  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {
+  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {  // NOLINT
 #ifdef PADDLE_WITH_PIP_CUDA_LIBRARIES
     return GetDsoHandleFromSearchPath(FLAGS_cuda_dir, "libcufft.so.10");
 #else
@@ -796,7 +796,7 @@ void* GetCUFFTDsoHandle() {
     return nullptr;
   }
 #elif defined(_WIN32) && defined(PADDLE_WITH_CUDA)
-  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {
+  if (CUDA_VERSION >= 11000 && CUDA_VERSION < 12000) {  // NOLINT
 #ifdef PADDLE_WITH_PIP_CUDA_LIBRARIES
     return GetDsoHandleFromSearchPath(FLAGS_cuda_dir, "cufft64_10.dll");
 #else

paddle/phi/infermeta/spmd_rules/cross_entropy_with_softmax.cc

@@ -320,11 +320,7 @@ SpmdInfo CrossEntropyWithSoftmaxInferSpmdReverse(
     if (!use_softmax) {
       x_dims_mapping[axis] = -1;
     } else {
-      if (axis != x_ndim - 1) {
-        x_dims_mapping[axis] = -1;
-        s_out_dims_mapping_dst[axis] = -1;
-        label_dims_mapping[axis] = -1;
-      } else if (soft_label) {
+      if (axis != x_ndim - 1 || soft_label) {
         x_dims_mapping[axis] = -1;
         s_out_dims_mapping_dst[axis] = -1;
         label_dims_mapping[axis] = -1;