Support gnustl, replace string funcs with ours, test=develop (#3263)

lite/api/cxx_api_bin.cc

@@ -67,7 +67,7 @@ void Run(const char* model_dir, int repeat) {
 
 int main(int argc, char** argv) {
   CHECK_EQ(argc, 3) << "usage: ./cmd <model_dir> <repeat>";
-  paddle::lite::Run(argv[1], std::stoi(argv[2]));
+  paddle::lite::Run(argv[1], atoi(argv[2]));
 
   return 0;
 }

lite/api/model_test.cc

@@ -138,7 +138,7 @@ void Run(const std::vector<std::vector<int64_t>>& input_shapes,
     std::ofstream out(FLAGS_arg_name + ".txt");
     for (size_t i = 0; i < arg_num; ++i) {
       sum += arg_tensor->data<float>()[i];
-      out << std::to_string(arg_tensor->data<float>()[i]) << "\n";
+      out << paddle::lite::to_string(arg_tensor->data<float>()[i]) << "\n";
     }
     LOG(INFO) << FLAGS_arg_name << " shape is " << os.str()
               << ", mean value is " << sum * 1. / arg_num;

lite/api/model_test_classify.cc

@@ -250,7 +250,7 @@ void Run(const std::vector<std::vector<int64_t>>& input_shapes,
     std::ofstream out(FLAGS_arg_name + ".txt");
     for (size_t i = 0; i < arg_num; ++i) {
       sum += arg_tensor->data<float>()[i];
-      out << std::to_string(arg_tensor->data<float>()[i]) << "\n";
+      out << paddle::lite::to_string(arg_tensor->data<float>()[i]) << "\n";
     }
     LOG(INFO) << FLAGS_arg_name << " shape is " << os.str()
               << ", mean value is " << sum * 1. / arg_num;

lite/api/model_test_detection.cc

@@ -264,7 +264,7 @@ void Run(const std::vector<std::vector<int64_t>>& input_shapes,
     std::ofstream out(FLAGS_arg_name + ".txt");
     for (size_t i = 0; i < arg_num; ++i) {
       sum += arg_tensor->data<float>()[i];
-      out << std::to_string(arg_tensor->data<float>()[i]) << "\n";
+      out << paddle::lite::to_string(arg_tensor->data<float>()[i]) << "\n";
     }
     LOG(INFO) << FLAGS_arg_name << " shape is " << os.str()
               << ", mean value is " << sum * 1. / arg_num;

lite/backends/fpga/KD/debugger.hpp

@@ -106,7 +106,7 @@ inline void read_from_file(lite::Tensor* t, const std::string& path) {
 
 inline void save_float(float* data, const std::string& name, int len) {
   static int counter = 0;
-  std::string old_string = std::to_string(counter);
+  std::string old_string = paddle::lite::to_string(counter);
   std::string new_string =
       std::string(3 - old_string.length(), '0') + old_string;
 

lite/backends/fpga/KD/tensor.hpp

@@ -351,10 +351,10 @@ class Tensor {
   void printScale(std::string type) { printScale(); }
 
   std::string dimsFileName() {
-    return std::to_string(shape_->num()) + "_" +
-           std::to_string(shape_->channel()) + "_" +
-           std::to_string(shape_->height()) + "_" +
-           std::to_string(shape_->width()) + ".txt";
+    return paddle::lite::to_string(shape_->num()) + "_" +
+           paddle::lite::to_string(shape_->channel()) + "_" +
+           paddle::lite::to_string(shape_->height()) + "_" +
+           paddle::lite::to_string(shape_->width()) + ".txt";
   }
 
   void saveToFile() { std::string path = dimsFileName(); }
@@ -374,7 +374,7 @@ class Tensor {
     invalidate();
     std::ofstream ofs;
     static int counter = 0;
-    std::string npath = std::to_string(counter) + "_" + path;
+    std::string npath = paddle::lite::to_string(counter) + "_" + path;
     counter++;
     save_file_with_name(npath);
   }

lite/backends/x86/jit/gen/blas.h

@@ -17,6 +17,7 @@
 #include <string>
 #include "glog/logging.h"
 #include "lite/backends/x86/jit/gen/jitcode.h"
+#include "lite/utils/string.h"
 
 namespace paddle {
 namespace lite {
@@ -64,7 +65,7 @@ class VXXJitCode : public JitCode {
       base += "_Vec";
     }
     base += (with_relu_ ? "_Relu" : "");
-    base += "_D" + std::to_string(num_);
+    base += "_D" + paddle::lite::to_string(num_);
     return base;
   }
   void genCode() override;

lite/backends/x86/jit/gen/embseqpool.h

@@ -47,7 +47,7 @@ class EmbSeqPoolJitCode : public JitCode {
     } else if (type_ == SeqPoolType::kSqrt) {
       base += "_Sqrt";
     }
-    base += ("_W" + std::to_string(tbl_w_));
+    base += ("_W" + paddle::lite::to_string(tbl_w_));
     return base;
   }
   void genCode() override;

lite/backends/x86/jit/gen/matmul.h

@@ -38,8 +38,8 @@ class MatMulJitCode : public JitCode {
 
   std::string name() const override {
     std::string base = "MatMulJitCode";
-    base = base + "_M" + std::to_string(m_) + "_N" + std::to_string(n_) + "_K" +
-           std::to_string(k_);
+    base = base + "_M" + paddle::lite::to_string(m_) + "_N" +
+           paddle::lite::to_string(n_) + "_K" + paddle::lite::to_string(k_);
     return base;
   }
   void genCode() override;

lite/backends/x86/jit/gen/seqpool.h

@@ -47,7 +47,7 @@ class SeqPoolJitCode : public JitCode {
     } else if (type_ == SeqPoolType::kSqrt) {
       base += "_Sqrt";
     }
-    base += ("_W" + std::to_string(w_));
+    base += ("_W" + paddle::lite::to_string(w_));
     return base;
   }
   void genCode() override;

lite/core/mir/graph_visualize_pass.cc

@@ -48,13 +48,16 @@ std::string Visualize(mir::SSAGraph* graph) {
     auto attr_type = op_info->GetAttrType(attr_name);
     switch (attr_type) {
       case AttrType::INT:
-        os << ":int:" << std::to_string(op_info->GetAttr<int>(attr_name));
+        os << ":int:"
+           << paddle::lite::to_string(op_info->GetAttr<int>(attr_name));
         break;
       case AttrType::FLOAT:
-        os << ":float:" << std::to_string(op_info->GetAttr<float>(attr_name));
+        os << ":float:"
+           << paddle::lite::to_string(op_info->GetAttr<float>(attr_name));
         break;
       case AttrType::BOOLEAN:
-        os << ":int:" << std::to_string(op_info->GetAttr<bool>(attr_name));
+        os << ":int:"
+           << paddle::lite::to_string(op_info->GetAttr<bool>(attr_name));
         break;
       case AttrType::STRING:
         os << ":string: \""

lite/core/mir/memory_optimize_pass.cc

@@ -238,7 +238,7 @@ void MemoryOptimizePass::PerformReusePlan(
       if (reuse_table.count(name) && reuse_table.at(name) != name) {
         auto replace_name = reuse_table.at(name);
         input_node->AsArg().name =
-            replace_name + "(" + std::to_string(node_append_idx) + ")";
+            replace_name + "(" + paddle::lite::to_string(node_append_idx) + ")";
         node_append_idx++;
       }
     }
@@ -262,7 +262,7 @@ void MemoryOptimizePass::PerformReusePlan(
       if (reuse_table.count(name) && reuse_table.at(name) != name) {
         auto replace_name = reuse_table.at(name);
         out_node->AsArg().name =
-            replace_name + "(" + std::to_string(node_append_idx) + ")";
+            replace_name + "(" + paddle::lite::to_string(node_append_idx) + ")";
         node_append_idx++;
       }
     }

lite/core/mir/subgraph/subgraph_detector.cc

@@ -66,11 +66,11 @@ std::string SubgraphVisualizer::operator()() {
     } else {
       exists_ops[op_type]++;
     }
-    auto op_name = op_type + std::to_string(exists_ops[op_type]);
+    auto op_name = op_type + paddle::lite::to_string(exists_ops[op_type]);
     std::string op_color = "white";
     if (subgraph_indices.count(node)) {
       auto subgraph_idx = subgraph_indices[node];
-      op_name += "_subgraph_" + std::to_string(subgraph_idx);
+      op_name += "_subgraph_" + paddle::lite::to_string(subgraph_idx);
       op_color = subgraph_colors[subgraph_idx % subgraph_colors.size()];
     }
     dot.AddNode(op_name,

lite/core/mir/subgraph/subgraph_detector_test.cc

@@ -39,7 +39,7 @@ std::vector<std::string> AddFCDesc(
   CHECK_EQ(input_var_names.size(), 1);
   CHECK_EQ(wshape.size(), 2);
   static int id = 0;
-  std::string prefix = "fc_" + std::to_string(id);
+  std::string prefix = "fc_" + paddle::lite::to_string(id);
   auto* op_desc = block_desc->AddOp<cpp::OpDesc>();
 
   auto* wgt = block_desc->AddVar<cpp::VarDesc>();
@@ -76,7 +76,7 @@ std::vector<std::string> AddElementwiseAddDesc(
     const std::vector<std::string>& input_Y_names) {
   // CHECK_EQ(input_var_names.size(), 2);
   static int id = 0;
-  std::string prefix = "elementwise_add_" + std::to_string(id);
+  std::string prefix = "elementwise_add_" + paddle::lite::to_string(id);
   auto* op_desc = block_desc->AddOp<cpp::OpDesc>();
   auto* out = block_desc->AddVar<cpp::VarDesc>();
 
@@ -100,7 +100,7 @@ std::vector<std::string> AddFeedDesc(
     const std::vector<std::string>& input_X_names) {
   // CHECK_EQ(input_var_names.size(), 1);
   static int id = 0;
-  std::string prefix = "feed_" + std::to_string(id);
+  std::string prefix = "feed_" + paddle::lite::to_string(id);
   auto* op_desc = block_desc->AddOp<cpp::OpDesc>();
   auto* out = block_desc->AddVar<cpp::VarDesc>();
 
@@ -123,7 +123,7 @@ std::vector<std::string> AddFetchDesc(
     const std::vector<std::string>& input_X_names) {
   // CHECK_EQ(input_var_names.size(), 1);
   static int id = 0;
-  std::string prefix = "fetch_" + std::to_string(id);
+  std::string prefix = "fetch_" + paddle::lite::to_string(id);
   auto* op_desc = block_desc->AddOp<cpp::OpDesc>();
   auto* out = block_desc->AddVar<cpp::VarDesc>();
 

lite/core/mir/type_precision_cast_pass.cc

@@ -201,7 +201,8 @@ void PrecisionCastPass::AddCastInst(const Type& from,
   CHECK(in->IsArg());
   // auto node_id = [&] { return graph->nodes().size(); };
   auto cast_op_output_name = in->AsArg().name + "/precision_trans";
-  // in->AsArg().name + "/precision_trans/" + std::to_string(node_id());
+  // in->AsArg().name + "/precision_trans/" +
+  // paddle::lite::to_string(node_id());
   auto* cast_op_output_arg = graph->NewArgumentNode(cast_op_output_name);
   cast_op_output_arg->AsArg().type =
       LiteType::GetTensorTy(from.target(), to.precision(), from.layout());

lite/core/profile/precision_profiler.h

@@ -263,8 +263,8 @@ class PrecisionProfiler {
                                           &mean,
                                           &std_dev,
                                           out_name);
-            mean_str = std::to_string(mean);
-            std_dev_str = std::to_string(std_dev);
+            mean_str = paddle::lite::to_string(mean);
+            std_dev_str = paddle::lite::to_string(std_dev);
           }
           std::string kernel_info = op_name + ":" + kernel_place;
           std::string output_arg_info = out_name + ":" +
@@ -294,8 +294,8 @@ class PrecisionProfiler {
                                             &mean,
                                             &std_dev,
                                             out_name);
-              mean_str = std::to_string(mean);
-              std_dev_str = std::to_string(std_dev);
+              mean_str = paddle::lite::to_string(mean);
+              std_dev_str = paddle::lite::to_string(std_dev);
             }
             std::string kernel_info = op_name + ":" + kernel_place;
             std::string output_arg_info = out_name + ":" +

lite/core/program_fake_utils.h

@@ -30,9 +30,9 @@ Program FakeProgram() {
 
   auto add_fc = [&](int id, std::string x) {
     // create variables
-    std::string w1 = "w" + std::to_string(id);
-    std::string b1 = "b" + std::to_string(id);
-    std::string out1 = "out" + std::to_string(id);
+    std::string w1 = "w" + paddle::lite::to_string(id);
+    std::string b1 = "b" + paddle::lite::to_string(id);
+    std::string out1 = "out" + paddle::lite::to_string(id);
     auto w1v = program.scope()->Var(w1)->GetMutable<lite::Tensor>();
     auto b1v = program.scope()->Var(b1)->GetMutable<lite::Tensor>();
     auto out1v = program.scope()->Var(out1)->GetMutable<lite::Tensor>();

lite/core/version.h.in

@@ -53,9 +53,9 @@ static std::string version() {
 static int64_t int_version(const std::string& version) {
   const std::vector<std::string> vec = Split(version, ".");
   if (vec.size() == 3) {
-    return std::stoi(vec[0]) * MAJOR_COEFF +
-           std::stoi(vec[1]) * MINOR_COEFF +
-           std::stoi(vec[2]) * PATCH_COEFF;
+    return atoi(vec[0].c_str()) * MAJOR_COEFF +
+           atoi(vec[1].c_str()) * MINOR_COEFF +
+           atoi(vec[2].c_str()) * PATCH_COEFF;
   }
   return -1;
 }

lite/demo/cxx/mask_detection/mask_detection.cc

@@ -207,7 +207,8 @@ void RunModel(std::string det_model_file,
     cv::Mat roi = crop_img(img, rec_clip, classify_w, classify_h);
 
     // uncomment two lines below, save roi img to disk
-    // std::string roi_name = "roi_" + std::to_string(i) + ".jpg";
+    // std::string roi_name = "roi_" + paddle::lite::to_string(i)
+    // + ".jpg";
     // imwrite(roi_name, roi);
 
     // Do PreProcess
@@ -240,7 +241,7 @@ void RunModel(std::string det_model_file,
       roi_color = cv::Scalar(0, 0, 255);
       prob = 1 - prob;
     }
-    std::string prob_str = std::to_string(prob * 100);
+    std::string prob_str = paddle::lite::to_string(prob * 100);
     int point_idx = prob_str.find_last_of(".");
 
     text += prob_str.substr(0, point_idx + 3) + "%";

lite/demo/cxx/mobile_light/mobilenetv1_light_api.cc

@@ -32,7 +32,7 @@ int64_t ShapeProduction(const shape_t& shape) {
 std::string ShapePrint(const shape_t& shape) {
   std::string shape_str{""};
   for (auto i : shape) {
-    shape_str += std::to_string(i) + " ";
+    shape_str += paddle::lite::to_string(i) + " ";
   }
   return shape_str;
 }

lite/demo/cxx/ssd_detection/ssd_detection.cc

@@ -126,7 +126,7 @@ std::vector<Object> detect_object(const float* data,
       if (w > 0 && h > 0 && obj.prob <= 1) {
         rect_out.push_back(obj);
         cv::rectangle(image, rec_clip, cv::Scalar(0, 0, 255), 2, cv::LINE_AA);
-        std::string str_prob = std::to_string(obj.prob);
+        std::string str_prob = paddle::lite::to_string(obj.prob);
         std::string text = std::string(class_names[obj.class_id]) + ": " +
                            str_prob.substr(0, str_prob.find(".") + 4);
         int font_face = cv::FONT_HERSHEY_COMPLEX_SMALL;

lite/demo/cxx/yolov3_detection/yolov3_detection.cc

@@ -146,7 +146,7 @@ std::vector<Object> detect_object(const float* data,
       if (w > 0 && h > 0 && obj.prob <= 1) {
         rect_out.push_back(obj);
         cv::rectangle(image, rec_clip, cv::Scalar(0, 0, 255), 1, cv::LINE_AA);
-        std::string str_prob = std::to_string(obj.prob);
+        std::string str_prob = paddle::lite::to_string(obj.prob);
         std::string text = std::string(class_names[obj.class_id]) + ": " +
                            str_prob.substr(0, str_prob.find(".") + 4);
         int font_face = cv::FONT_HERSHEY_COMPLEX_SMALL;

lite/gen_code/gen_code.cc

@@ -111,11 +111,11 @@ void Module::AddOpDescHelper(const std::string &op_id,
 
     switch (type) {
       case AttrType::INT:
-        return std::to_string(desc.GetAttr<int>(name));
+        return paddle::lite::to_string(desc.GetAttr<int>(name));
       case AttrType::FLOAT:
-        return std::to_string(desc.GetAttr<float>(name));
+        return paddle::lite::to_string(desc.GetAttr<float>(name));
       case AttrType::BOOLEAN:
-        return std::to_string(desc.GetAttr<bool>(name));
+        return paddle::lite::to_string(desc.GetAttr<bool>(name));
       case AttrType::STRING:
         return "\"" + desc.GetAttr<std::string>(name) + "\"";
       case AttrType::FLOATS: {

lite/gen_code/gen_code.h

@@ -153,16 +153,16 @@ class Module {
 
  private:
   std::string WeightUniqueName() const {
-    return "w_" + std::to_string(weight_counter_++);
+    return "w_" + paddle::lite::to_string(weight_counter_++);
   }
   std::string TmpVarUniqueName() const {
-    return "tmp_" + std::to_string(tmp_var_counter_++);
+    return "tmp_" + paddle::lite::to_string(tmp_var_counter_++);
   }
   std::string OpUniqueName() const {
-    return "op_" + std::to_string(op_counter_++);
+    return "op_" + paddle::lite::to_string(op_counter_++);
   }
   std::string KernelUniqueName() const {
-    return "kernel_" + std::to_string(kernel_counter_++);
+    return "kernel_" + paddle::lite::to_string(kernel_counter_++);
   }
 
   std::string DataRepr(const std::string &raw_data, PrecisionType dtype);

lite/kernels/bm/bridges/utility.cc

@@ -33,7 +33,7 @@ std::string UniqueName(const std::string& prefix) {
     counter = ++(it->second);
   }
 
-  return prefix + "_" + std::to_string(counter);
+  return prefix + "_" + paddle::lite::to_string(counter);
 }
 
 bool HasInputArg(const OpInfo* op_info,

lite/kernels/npu/bridges/graph.h

@@ -87,7 +87,8 @@ class Graph {
     auto idx = Add(name, node);
     CHECK_GE(idx, 1);
     // Generate a unique name for the created HiAI IR
-    node->set_data(std::make_shared<T>(name + "__" + std::to_string(idx)));
+    node->set_data(
+        std::make_shared<T>(name + "__" + paddle::lite::to_string(idx)));
     return node;
   }
 

lite/kernels/npu/bridges/split_op.cc

@@ -64,10 +64,12 @@ int SplitConverter(void* ctx, OpLite* op, KernelBase* kernel) {
   split_op->create_dynamic_output_y(out_names.size());
   int idx = 1;
   for (auto& out_name : out_names) {
-    auto zero_node = graph->Add(out_name + "/zero" + std::to_string(idx), 0);
+    auto zero_node =
+        graph->Add(out_name + "/zero" + paddle::lite::to_string(idx), 0);
     auto add_node = graph->Add<ge::op::Add>(out_name);
     auto add_op = add_node->data<ge::op::Add>();
-    add_op->set_input_x1(*split_node->data(), "y" + std::to_string(idx));
+    add_op->set_input_x1(*split_node->data(),
+                         "y" + paddle::lite::to_string(idx));
     add_op->set_input_x2(*zero_node->data());
     idx++;
   }

lite/kernels/xpu/bridges/graph.cc

@@ -49,7 +49,7 @@ std::shared_ptr<Node> Graph::Add(const std::string& name,
   CHECK_GE(idx, 1);
   node->set_data(std::make_shared<xtcl::xExpr>(layer));
   // Generate a unique name for the current XTCL layer
-  builder_.SetLayer(name + "__" + std::to_string(idx));
+  builder_.SetLayer(name + "__" + paddle::lite::to_string(idx));
   return node;
 }
 

lite/model_parser/naive_buffer/naive_buffer_test.cc

@@ -155,7 +155,7 @@ TEST(ListBuilder, basic) {
 
   for (int i = 0; i < num_elems; i++) {
     auto* elem = li.New();
-    elem->set("elem-" + std::to_string(i));
+    elem->set("elem-" + paddle::lite::to_string(i));
   }
   li.Save();
   table.SaveToFile("2.bf");
@@ -169,7 +169,7 @@ TEST(ListBuilder, basic) {
   li1.Load();
 
   for (int i = 0; i < num_elems; i++) {
-    ASSERT_EQ(li1.Get(i).data(), "elem-" + std::to_string(i));
+    ASSERT_EQ(li1.Get(i).data(), "elem-" + paddle::lite::to_string(i));
   }
 }
 

lite/tests/kernels/concat_compute_test.cc

@@ -128,7 +128,7 @@ class ConcateComputeTester : public arena::TestCase {
       for (int i = 0; i < x_dims_.production(); i++) {
         x_data[i] = static_cast<float>(i + n);
       }
-      const std::string x_name = "x_tensor_" + std::to_string(n);
+      const std::string x_name = "x_tensor_" + paddle::lite::to_string(n);
       x_vct_.push_back(x_name);
       SetCommonTensor(x_name, x_dims_, x_data.data());
     }

lite/tests/kernels/fill_constant_compute_test.cc

@@ -52,7 +52,8 @@ class FillConstantComputeTester : public arena::TestCase {
         is_use_shape_tensor_list_(is_use_shape_tensor_list) {
     if (is_use_shape_tensor_list) {
       for (int i = 0; i < shape.size(); i++) {
-        shape_tensor_list_.push_back(shape_tensor_ + std::to_string(i));
+        shape_tensor_list_.push_back(shape_tensor_ +
+                                     paddle::lite::to_string(i));
       }
     }
   }

lite/tests/kernels/reshape_compute_test.cc

@@ -45,7 +45,8 @@ class ReshapeComputeTester : public arena::TestCase {
       : TestCase(place, alias), dims_(dims) {
     if (is_shape_tensor_vct) {
       for (size_t i = 0; i < shape.size(); i++) {
-        shape_tensor_vct_.emplace_back(op_type_ + "/shape" + std::to_string(i));
+        shape_tensor_vct_.emplace_back(op_type_ + "/shape" +
+                                       paddle::lite::to_string(i));
       }
     } else if (is_shape_tensor) {
       shape_tensor_ = op_type_ + "/shape";

lite/tests/kernels/slice_compute_test.cc

@@ -168,8 +168,9 @@ class SliceComputeTester : public arena::TestCase {
       std::vector<std::string> ends_tensor_list_;
       for (int i = 0; i < starts_.size(); ++i) {
         starts_tensor_list_.push_back("starts_tensor_list_" +
-                                      std::to_string(i));
-        ends_tensor_list_.push_back("ends_tensor_list_" + std::to_string(i));
+                                      paddle::lite::to_string(i));
+        ends_tensor_list_.push_back("ends_tensor_list_" +
+                                    paddle::lite::to_string(i));
       }
       op_desc->SetInput("StartsTensorList", {starts_tensor_list_});
       op_desc->SetInput("EndsTensorList", {ends_tensor_list_});
@@ -203,15 +204,15 @@ class SliceComputeTester : public arena::TestCase {
     } else if (use_tensor_list_) {
       Scope& scope_ = this->scope();
       for (int i = 0; i < starts_.size(); ++i) {
-        auto* tensor =
-            scope_.NewTensor("starts_tensor_list_" + std::to_string(i));
+        auto* tensor = scope_.NewTensor("starts_tensor_list_" +
+                                        paddle::lite::to_string(i));
         tensor->Resize(DDim({1}));
         auto* d = tensor->mutable_data<int>();
         d[0] = starts_[i];
       }
       for (int i = 0; i < ends_.size(); ++i) {
         auto* tensor =
-            scope_.NewTensor("ends_tensor_list_" + std::to_string(i));
+            scope_.NewTensor("ends_tensor_list_" + paddle::lite::to_string(i));
         tensor->Resize(DDim({1}));
         auto* d = tensor->mutable_data<int>();
         d[0] = ends_[i];

lite/tests/kernels/unsqueeze_compute_test.cc

@@ -123,7 +123,7 @@ class UnsqueezeComputeTester : public arena::TestCase {
     } else if (input_axes_flag_ == 3) {
       std::string name = "axes_tensor_";
       for (size_t i = 0; i < axes_.size(); i++) {
-        name = name + std::to_string(i);
+        name = name + paddle::lite::to_string(i);
         axes_tensor_list_.push_back(name);
         SetCommonTensor(name, DDim({1}), &axes_[i]);
       }

lite/utils/logging.h

@@ -29,6 +29,7 @@
 #include <cstring>
 #include <string>
 #include "lite/utils/replace_stl/stream.h"
+#include "lite/utils/string.h"
 
 #ifdef LITE_WITH_ANDROID
 #include <android/log.h>
@@ -171,7 +172,7 @@ class VLogMessage {
     if (GLOG_v_int < level_int) {
       return;
     }
-    const char* level = std::to_string(level_int).c_str();
+    const char* level = paddle::lite::to_string(level_int).c_str();
     paddle::lite::gen_log(log_stream_, file, func, lineno, level);
   }
 

lite/utils/replace_stl/stream.cc

@@ -15,6 +15,7 @@
 #include "lite/utils/replace_stl/stream.h"
 #include <assert.h>
 #include <stdio.h>
+#include "lite/utils/string.h"
 
 #ifdef LITE_ON_TINY_PUBLISH
 
@@ -40,7 +41,7 @@ void ostream::pad(const std::string& text) {
 #define ADD_DATA_AS_STRING(data_, obj_)
 #else
 #define ADD_DATA_AS_STRING(data_, obj_)             \
-  std::string text = std::to_string(obj_); \
+  std::string text = paddle::lite::to_string(obj_); \
   pad(text);                                        \
   data_ = data_ + text;
 

lite/utils/string.h

@@ -48,7 +48,14 @@ template <typename T>
 static std::string to_string_with_precision(const T& v, const int n = 6) {
   STL::stringstream ss;
   ss.precision(n);
-  // ss << std::fixed << v;
+  ss << v;
+  return ss.str();
+}
+
+template <typename T>
+static std::string to_string(const T& v) {
+  STL::stringstream ss;
+  ss << v;
   return ss.str();
 }