[MS][LITE] Add build function for model_path

include/api/model.h

@@ -38,7 +38,6 @@ namespace dataset {
 class Dataset;
 }  // namespace dataset
 
-
 class MS_API Model {
  public:
   Model();
@@ -73,6 +72,9 @@ class MS_API Model {
   Status Build(const void *model_data, size_t data_size, ModelType model_type,
                const std::shared_ptr<Context> &model_context = nullptr, const Key &dec_key = {},
                const std::string &dec_mode = kDecModeAesGcm);
+  Status Build(const std::string &model_path, ModelType model_type,
+               const std::shared_ptr<Context> &model_context = nullptr, const Key &dec_key = {},
+               const std::string &dec_mode = kDecModeAesGcm);
 
  private:
   friend class Serialization;

mindspore/ccsrc/cxx_api/model/model.cc

@@ -72,6 +72,12 @@ Status Model::Build(const void *model_data, size_t data_size, ModelType model_ty
   return kMCFailed;
 }
 
+Status Model::Build(const std::string &model_path, ModelType model_type, const std::shared_ptr<Context> &model_context,
+                    const Key &dec_key, const std::string &dec_mode) {
+  MS_LOG(ERROR) << "Unsupported Feature.";
+  return kMCFailed;
+}
+
 Status Model::Resize(const std::vector<MSTensor> &inputs, const std::vector<std::vector<int64_t>> &dims) {
   if (impl_ == nullptr) {
     MS_LOG(ERROR) << "Failed because this model has not been built.";

mindspore/lite/src/cxx_api/model/model.cc

@@ -40,6 +40,20 @@ Status Model::Build(const void *model_data, size_t data_size, ModelType model_ty
   return kSuccess;
 }
 
+Status Model::Build(const std::string &model_path, ModelType model_type, const std::shared_ptr<Context> &model_context,
+                    const Key &dec_key, const std::string &dec_mode) {
+  impl_ = std::shared_ptr<ModelImpl>(new (std::nothrow) ModelImpl());
+  if (impl_ == nullptr) {
+    MS_LOG(ERROR) << "Model implement is null.";
+    return kLiteNullptr;
+  }
+  Status ret = impl_->Build(model_path, model_type, model_context);
+  if (ret != kSuccess) {
+    return ret;
+  }
+  return kSuccess;
+}
+
 Status Model::Build(GraphCell graph, const std::shared_ptr<Context> &model_context,
                     const std::shared_ptr<TrainCfg> &train_cfg) {
   std::stringstream err_msg;

mindspore/lite/src/cxx_api/model/model_impl.cc

@@ -28,6 +28,7 @@
 #include "src/cxx_api/tensor_utils.h"
 #include "src/common/log_adapter.h"
 #include "src/train/train_session.h"
+#include "src/common/file_utils.h"
 
 namespace mindspore {
 using mindspore::lite::RET_ERROR;
@@ -62,6 +63,33 @@ Status ModelImpl::Build(const void *model_data, size_t data_size, ModelType mode
   return kSuccess;
 }
 
+Status ModelImpl::Build(const std::string &model_path, ModelType model_type,
+                        const std::shared_ptr<Context> &ms_context) {
+  lite::Context lite_context;
+  auto status = A2L_ConvertContext(ms_context.get(), &lite_context);
+  if (status != kSuccess) {
+    return status;
+  }
+
+  size_t data_size = 0;
+  char *model_data = lite::ReadFile(model_path.c_str(), &data_size);
+  if (model_data == nullptr) {
+    MS_LOG(ERROR) << "Read model path failed.";
+    return kMDFileNotExist;
+  }
+
+  auto session = std::shared_ptr<session::LiteSession>(
+    session::LiteSession::CreateSession(const_cast<const char *>(model_data), data_size, &lite_context));
+  if (session == nullptr) {
+    MS_LOG(ERROR) << "Allocate session failed.";
+    return kLiteNullptr;
+  }
+
+  session_.swap(session);
+  MS_LOG(DEBUG) << "Build model success.";
+  return kSuccess;
+}
+
 Status ModelImpl::Build() {
   MS_LOG(DEBUG) << "Start build model.";
   if (graph_ == nullptr || graph_->graph_data_ == nullptr) {

mindspore/lite/src/cxx_api/model/model_impl.h

@@ -60,6 +60,7 @@ class ModelImpl {
   Status Build();
   Status Build(const void *model_data, size_t data_size, ModelType model_type,
                const std::shared_ptr<Context> &model_context);
+  Status Build(const std::string &model_path, ModelType model_type, const std::shared_ptr<Context> &model_context);
   Status Resize(const std::vector<MSTensor> &inputs, const std::vector<std::vector<int64_t>> &dims);
 
   Status Predict(const std::vector<MSTensor> &inputs, std::vector<MSTensor> *outputs, const MSKernelCallBack &before,