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https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-05 16:48:03 +08:00
[Other] Unify initialize api for lite/trt backend (#1249)
* Unify initialize api for lite/trt backend * Unify initialize api for lite/trt backend
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@@ -56,18 +56,39 @@ void LiteBackend::BuildOption(const LiteBackendOption& option) {
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}
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}
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bool LiteBackend::InitFromPaddle(const std::string& model_file,
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const std::string& params_file,
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const LiteBackendOption& option) {
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bool LiteBackend::Init(const RuntimeOption& runtime_option) {
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if (initialized_) {
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FDERROR << "LiteBackend is already initialized, cannot initialize again."
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<< std::endl;
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return false;
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}
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config_.set_model_file(model_file);
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config_.set_param_file(params_file);
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BuildOption(option);
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if (runtime_option.model_format != ModelFormat::PADDLE) {
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FDERROR
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<< "PaddleLiteBackend only supports model format PADDLE, but now it's "
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<< runtime_option.model_format << "." << std::endl;
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return false;
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}
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if (runtime_option.device != Device::CPU &&
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runtime_option.device != Device::KUNLUNXIN &&
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runtime_option.device != Device::ASCEND &&
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runtime_option.device != Device::TIMVX) {
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FDERROR << "PaddleLiteBackend only supports "
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"Device::CPU/Device::TIMVX/Device::KUNLUNXIN/Device::ASCEND, "
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"but now it's "
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<< runtime_option.device << "." << std::endl;
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return false;
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}
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if (runtime_option.model_from_memory_) {
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FDERROR << "PaddleLiteBackend doesn't support load model from memory, "
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"please load model from disk."
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<< std::endl;
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return false;
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}
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config_.set_model_file(runtime_option.model_file);
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config_.set_param_file(runtime_option.params_file);
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BuildOption(runtime_option.paddle_lite_option);
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predictor_ =
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paddle::lite_api::CreatePaddlePredictor<paddle::lite_api::CxxConfig>(
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config_);
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@@ -22,6 +22,7 @@
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#include "paddle_api.h" // NOLINT
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#include "fastdeploy/runtime/backends/backend.h"
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#include "fastdeploy/runtime/runtime_option.h"
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#include "fastdeploy/runtime/backends/lite/option.h"
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namespace fastdeploy {
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@@ -30,11 +31,8 @@ class LiteBackend : public BaseBackend {
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public:
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LiteBackend() {}
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virtual ~LiteBackend() = default;
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void BuildOption(const LiteBackendOption& option);
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bool InitFromPaddle(const std::string& model_file,
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const std::string& params_file,
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const LiteBackendOption& option = LiteBackendOption());
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bool Init(const RuntimeOption& option);
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bool Infer(std::vector<FDTensor>& inputs,
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std::vector<FDTensor>* outputs,
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@@ -50,6 +48,8 @@ class LiteBackend : public BaseBackend {
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std::vector<TensorInfo> GetOutputInfos() override;
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private:
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void BuildOption(const LiteBackendOption& option);
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void ConfigureCpu(const LiteBackendOption& option);
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void ConfigureTimvx(const LiteBackendOption& option);
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void ConfigureAscend(const LiteBackendOption& option);
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@@ -113,6 +113,50 @@ bool TrtBackend::LoadTrtCache(const std::string& trt_engine_file) {
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return true;
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}
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bool TrtBackend::Init(const RuntimeOption& runtime_option) {
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if (runtime_option.device != Device::GPU) {
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FDERROR << "TrtBackend only supports Device::GPU, but now it's "
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<< runtime_option.device << "." << std::endl;
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return false;
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}
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if (runtime_option.model_format != ModelFormat::PADDLE &&
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runtime_option.model_format != ModelFormat::ONNX) {
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FDERROR
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<< "TrtBackend only supports model format PADDLE/ONNX, but now it's "
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<< runtime_option.model_format << "." << std::endl;
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return false;
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}
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if (runtime_option.model_format == ModelFormat::PADDLE) {
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if (runtime_option.model_from_memory_) {
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return InitFromPaddle(runtime_option.model_file,
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runtime_option.params_file,
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runtime_option.trt_option);
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} else {
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std::string model_buffer;
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std::string params_buffer;
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FDASSERT(ReadBinaryFromFile(runtime_option.model_file, &model_buffer),
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"Failed to read model file %s.",
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runtime_option.model_file.c_str());
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FDASSERT(ReadBinaryFromFile(runtime_option.params_file, ¶ms_buffer),
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"Failed to read parameters file %s.",
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runtime_option.params_file.c_str());
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return InitFromPaddle(model_buffer, params_buffer,
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runtime_option.trt_option);
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}
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} else {
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if (runtime_option.model_from_memory_) {
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return InitFromOnnx(runtime_option.model_file, runtime_option.trt_option);
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} else {
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std::string model_buffer;
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FDASSERT(ReadBinaryFromFile(runtime_option.model_file, &model_buffer),
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"Failed to read model file %s.",
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runtime_option.model_file.c_str());
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return InitFromOnnx(model_buffer, runtime_option.trt_option);
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}
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}
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return true;
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}
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bool TrtBackend::InitFromPaddle(const std::string& model_buffer,
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const std::string& params_buffer,
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const TrtBackendOption& option, bool verbose) {
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@@ -70,14 +70,8 @@ FDDataType GetFDDataType(const nvinfer1::DataType& dtype);
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class TrtBackend : public BaseBackend {
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public:
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TrtBackend() : engine_(nullptr), context_(nullptr) {}
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void BuildOption(const TrtBackendOption& option);
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bool InitFromPaddle(const std::string& model_buffer,
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const std::string& params_buffer,
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const TrtBackendOption& option = TrtBackendOption(),
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bool verbose = false);
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bool InitFromOnnx(const std::string& model_buffer,
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const TrtBackendOption& option = TrtBackendOption());
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bool Init(const RuntimeOption& runtime_option);
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bool Infer(std::vector<FDTensor>& inputs, std::vector<FDTensor>* outputs,
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bool copy_to_fd = true) override;
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@@ -98,6 +92,15 @@ class TrtBackend : public BaseBackend {
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}
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private:
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void BuildOption(const TrtBackendOption& option);
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bool InitFromPaddle(const std::string& model_buffer,
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const std::string& params_buffer,
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const TrtBackendOption& option = TrtBackendOption(),
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bool verbose = false);
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bool InitFromOnnx(const std::string& model_buffer,
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const TrtBackendOption& option = TrtBackendOption());
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TrtBackendOption option_;
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std::shared_ptr<nvinfer1::ICudaEngine> engine_;
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std::shared_ptr<nvinfer1::IExecutionContext> context_;
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@@ -324,12 +324,6 @@ void Runtime::CreateOrtBackend() {
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}
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void Runtime::CreateTrtBackend() {
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FDASSERT(option.device == Device::GPU,
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"Backend::TRT only supports Device::GPU.");
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FDASSERT(option.model_format == ModelFormat::PADDLE ||
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option.model_format == ModelFormat::ONNX,
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"TrtBackend only support model format of ModelFormat::PADDLE / "
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"ModelFormat::ONNX.");
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#ifdef ENABLE_TRT_BACKEND
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option.trt_option.model_file = option.model_file;
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option.trt_option.params_file = option.params_file;
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@@ -338,40 +332,8 @@ void Runtime::CreateTrtBackend() {
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option.trt_option.enable_pinned_memory = option.enable_pinned_memory;
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option.trt_option.external_stream_ = option.external_stream_;
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backend_ = utils::make_unique<TrtBackend>();
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auto casted_backend = dynamic_cast<TrtBackend*>(backend_.get());
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casted_backend->benchmark_option_ = option.benchmark_option;
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if (option.model_format == ModelFormat::ONNX) {
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if (option.model_from_memory_) {
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FDASSERT(
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casted_backend->InitFromOnnx(option.model_file, option.trt_option),
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"Load model from ONNX failed while initliazing TrtBackend.");
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ReleaseModelMemoryBuffer();
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} else {
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std::string model_buffer = "";
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FDASSERT(ReadBinaryFromFile(option.model_file, &model_buffer),
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"Fail to read binary from model file");
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FDASSERT(casted_backend->InitFromOnnx(model_buffer, option.trt_option),
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"Load model from ONNX failed while initliazing TrtBackend.");
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}
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} else {
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if (option.model_from_memory_) {
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FDASSERT(casted_backend->InitFromPaddle(
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option.model_file, option.params_file, option.trt_option),
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"Load model from Paddle failed while initliazing TrtBackend.");
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ReleaseModelMemoryBuffer();
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} else {
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std::string model_buffer = "";
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std::string params_buffer = "";
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FDASSERT(ReadBinaryFromFile(option.model_file, &model_buffer),
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"Fail to read binary from model file");
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FDASSERT(ReadBinaryFromFile(option.params_file, ¶ms_buffer),
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"Fail to read binary from parameter file");
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FDASSERT(casted_backend->InitFromPaddle(model_buffer, params_buffer,
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option.trt_option),
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"Load model from Paddle failed while initliazing TrtBackend.");
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}
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}
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backend_->benchmark_option_ = option.benchmark_option;
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FDASSERT(backend_->Init(option), "Failed to initialize TensorRT backend.");
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#else
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FDASSERT(false,
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"TrtBackend is not available, please compiled with "
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@@ -383,29 +345,18 @@ void Runtime::CreateTrtBackend() {
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void Runtime::CreateLiteBackend() {
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#ifdef ENABLE_LITE_BACKEND
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FDASSERT(option.model_from_memory_ == false,
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"LiteBackend don't support to load model from memory");
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FDASSERT(option.device == Device::CPU || option.device == Device::TIMVX ||
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option.device == Device::KUNLUNXIN ||
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option.device == Device::ASCEND,
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"Backend::LITE only supports "
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"Device::CPU/Device::TIMVX/Device::KUNLUNXIN/Device::ASCEND.");
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FDASSERT(option.model_format == ModelFormat::PADDLE,
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"LiteBackend only support model format of ModelFormat::PADDLE");
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backend_ = utils::make_unique<LiteBackend>();
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auto casted_backend = dynamic_cast<LiteBackend*>(backend_.get());
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casted_backend->benchmark_option_ = option.benchmark_option;
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backend_->benchmark_option_ = option.benchmark_option;
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FDASSERT(casted_backend->InitFromPaddle(option.model_file, option.params_file,
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option.paddle_lite_option),
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FDASSERT(backend_->Init(option),
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"Load model from nb file failed while initializing LiteBackend.");
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#else
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FDASSERT(false,
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"LiteBackend is not available, please compiled with "
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"ENABLE_LITE_BACKEND=ON.");
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#endif
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FDINFO << "Runtime initialized with Backend::LITE in " << option.device << "."
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<< std::endl;
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FDINFO << "Runtime initialized with Backend::PDLITE in " << option.device
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<< "." << std::endl;
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}
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void Runtime::CreateRKNPU2Backend() {
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