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[Other]Fastdeploy supports set_model_buffer function for encrypted model (#930)

Browse Source 
* Update keypointdetection result docs

* Update im.copy() to im in examples

* Update new Api, fastdeploy::vision::Visualize to fastdeploy::vision

* Update SwapBackgroundSegmentation && SwapBackgroundMatting to SwapBackground

* Update README_CN.md

* Update README_CN.md

* Support set_model_buffer function
This commit is contained in:
huangjianhui
2022-12-21 14:21:28 +08:00
committed by GitHub
parent b42ec302e6
commit 291db315c8
6 changed files with 110 additions and 12 deletions
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30
fastdeploy/backends/paddle/paddle_backend.cc
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@@ -99,17 +99,22 @@ bool PaddleBackend::InitFromPaddle(const std::string& model_file,
<< std::endl;
return false;
}
config_.SetModel(model_file, params_file);
config_.EnableMemoryOptim();
BuildOption(option);
// The input/output information get from predictor is not right, use PaddleReader instead now
std::string contents;
if (!ReadBinaryFromFile(model_file, &contents)) {
return false;
}
auto reader = paddle2onnx::PaddleReader(contents.c_str(), contents.size());
if (option.model_from_memory_) {
config_.SetModelBuffer(model_file.c_str(), option.model_buffer_size_, params_file.c_str(), option.params_buffer_size_);
contents = model_file;
} else {
config_.SetModel(model_file, params_file);
if (!ReadBinaryFromFile(model_file, &contents)) {
return false;
}
}
config_.EnableMemoryOptim();
BuildOption(option);
auto reader = paddle2onnx::PaddleReader(contents.c_str(), contents.size());
// If it's a quantized model, and use cpu with mkldnn, automaticaly switch to int8 mode
if (reader.is_quantize_model) {
if (option.use_gpu) {
@@ -167,13 +172,20 @@ bool PaddleBackend::InitFromPaddle(const std::string& model_file,
#ifdef ENABLE_TRT_BACKEND
if (option.collect_shape) {
// Set the shape info file.
auto curr_model_dir = GetDirFromPath(model_file);
std::string curr_model_dir = "./";
if (!option.model_from_memory_) {
curr_model_dir = GetDirFromPath(model_file);
}
std::string shape_range_info =
PathJoin(curr_model_dir, "shape_range_info.pbtxt");
if (!CheckFileExists(shape_range_info)) {
FDINFO << "Start generating shape range info file." << std::endl;
paddle_infer::Config analysis_config;
analysis_config.SetModel(model_file, params_file);
if (option.model_from_memory_) {
analysis_config.SetModelBuffer(model_file.c_str(), option.model_buffer_size_, params_file.c_str(), option.params_buffer_size_);
} else {
analysis_config.SetModel(model_file, params_file);
}
analysis_config.CollectShapeRangeInfo(shape_range_info);
auto predictor_tmp = paddle_infer::CreatePredictor(analysis_config);
std::map<std::string, std::vector<int>> max_shape;