fix train_lenet demo

fix code-style

mindspore/lite/examples/train_lenet/Makefile

@@ -1,6 +1,6 @@
 BASE_DIR=$(realpath ../../../../)
 APP:=bin/net_runner
-LMSLIB:=-lmindspore-lite
+LMSLIB:=-lmindspore-lite-train
 LMDLIB:=-lminddata-lite
 MSDIR:=$(realpath package-$(TARGET)/lib)
 ifneq ("$(wildcard $(MSDIR)/libhiai.so)","")

mindspore/lite/examples/train_lenet/src/net_runner.cc

@@ -99,11 +99,8 @@ void NetRunner::InitAndFigureInputs() {
   context.device_list_[0].device_type_ = mindspore::lite::DT_CPU;
   context.thread_num_ = 2;
 
-  model_ = mindspore::lite::Model::Import(ms_file_);
-  if (model_ == nullptr) {
-    MS_LOG(ERROR) << "import model failed";
-    return nullptr;
-  }
+  model_ = mindspore::lite::Model::Import(ms_file_.c_str());
+  MS_ASSERT(nullptr != model_);
   session_ = mindspore::session::TrainSession::CreateSession(model_, &context, true);
 
   MS_ASSERT(nullptr != session_);
@@ -169,7 +166,7 @@ int NetRunner::TrainLoop() {
 
   mindspore::lite::LossMonitor lm(100);
   mindspore::lite::ClassificationTrainAccuracyMonitor am(1);
-  mindspore::lite::CkptSaver cs(1000, std::string("lenet"));
+  mindspore::lite::CkptSaver cs(1000, std::string("lenet"), model_);
   Rescaler rescale(255.0);
 
   loop_->Train(epochs_, train_ds_.get(), std::vector<TrainLoopCallBack *>{&rescale, &lm, &cs, &am, &step_lr_sched});
@@ -187,7 +184,7 @@ int NetRunner::Main() {
 
   if (epochs_ > 0) {
     auto trained_fn = ms_file_.substr(0, ms_file_.find_last_of('.')) + "_trained.ms";
-    Model::Export(model_, trained_fn);
+    mindspore::lite::Model::Export(model_, trained_fn.c_str());
   }
   return 0;
 }

mindspore/lite/include/train/ckpt_saver.h

@@ -29,14 +29,14 @@ namespace lite {
 
 class CkptSaver : public session::TrainLoopCallBack {
  public:
-  CkptSaver(int save_every_n, const std::string &filename_prefix)
-      : save_every_n_(save_every_n), filename_prefix_(filename_prefix) {}
+  CkptSaver(int save_every_n, const std::string &filename_prefix, mindspore::lite::Model *model)
+      : save_every_n_(save_every_n), filename_prefix_(filename_prefix), model_(model) {}
 
   int EpochEnd(const session::TrainLoopCallBackData &cb_data) override {
     if ((cb_data.epoch_ + 1) % save_every_n_ == 0) {
       auto cpkt_fn = filename_prefix_ + "_trained_" + std::to_string(cb_data.epoch_ + 1) + ".ms";
       remove(cpkt_fn.c_str());
-      cb_data.session_->SaveToFile(cpkt_fn);
+      Model::Export(model_, cpkt_fn.c_str());
     }
     return session::RET_CONTINUE;
   }
@@ -44,6 +44,7 @@ class CkptSaver : public session::TrainLoopCallBack {
  private:
   int save_every_n_;
   std::string filename_prefix_;
+  mindspore::lite::Model *model_ = nullptr;
 };
 
 }  // namespace lite