diff --git a/cmake/external/paddle2onnx.cmake b/cmake/external/paddle2onnx.cmake index cbb622f5cb952987331ce1da75571ed419c6e638..b8a1b4548b8224745a1c3d7c33781b72a9a9ad08 100644 --- a/cmake/external/paddle2onnx.cmake +++ b/cmake/external/paddle2onnx.cmake @@ -24,7 +24,7 @@ endif() include(ExternalProject) set(PADDLE2ONNX_PROJECT "extern_paddle2onnx") -set(PADDLE2ONNX_VERSION "0.9.9") +set(PADDLE2ONNX_VERSION "1.0.0rc") set(PADDLE2ONNX_PREFIX_DIR ${THIRD_PARTY_PATH}/paddle2onnx) set(PADDLE2ONNX_SOURCE_DIR ${THIRD_PARTY_PATH}/paddle2onnx/src/${PADDLE2ONNX_PROJECT}) diff --git a/paddle/fluid/inference/api/details/zero_copy_tensor.cc b/paddle/fluid/inference/api/details/zero_copy_tensor.cc index 4040d09c4519ed13a82f36241f3a92cd5e5bcad3..7bb384b27381db9bad8148a92f5b29fa4dc4ba4c 100644 --- a/paddle/fluid/inference/api/details/zero_copy_tensor.cc +++ b/paddle/fluid/inference/api/details/zero_copy_tensor.cc @@ -179,13 +179,6 @@ PlaceType Tensor::place() const { return place_; } template void Tensor::CopyFromCpu(const T *data) { -#ifdef PADDLE_WITH_ONNXRUNTIME - if (is_ort_tensor_) { - ORTCopyFromCpu(data); - return; - } -#endif - EAGER_GET_TENSOR(paddle::framework::LoDTensor); PADDLE_ENFORCE_GE(tensor->numel(), 0, @@ -731,112 +724,6 @@ void Tensor::SetOrtBuffer(const std::shared_ptr> buffer) { buffer_ = buffer; } -Ort::Value GetOrtVaule(const Ort::MemoryInfo &memory_info, - float *data, - size_t size, - const int64_t *shape, - size_t shape_len) { - return Ort::Value::CreateTensor( - memory_info, data, size, shape, shape_len); -} - -Ort::Value GetOrtVaule(const Ort::MemoryInfo &memory_info, - int64_t *data, - size_t size, - const int64_t *shape, - size_t shape_len) { - return Ort::Value::CreateTensor( - memory_info, data, size, shape, shape_len); -} - -Ort::Value GetOrtVaule(const Ort::MemoryInfo &memory_info, - int32_t *data, - size_t size, - const int64_t *shape, - size_t shape_len) { - return Ort::Value::CreateTensor( - memory_info, data, size, shape, shape_len); -} - -Ort::Value GetOrtVaule(const Ort::MemoryInfo &memory_info, - uint8_t *data, - size_t size, - const int64_t *shape, - size_t shape_len) { - return Ort::Value::CreateTensor( - memory_info, data, size, shape, shape_len); -} - -Ort::Value GetOrtVaule(const Ort::MemoryInfo &memory_info, - int8_t *data, - size_t size, - const int64_t *shape, - size_t shape_len) { - return Ort::Value::CreateTensor( - memory_info, data, size, shape, shape_len); -} - -Ort::Value GetOrtVaule(const Ort::MemoryInfo &memory_info, - float16 *data, - size_t size, - const int64_t *shape, - size_t shape_len) { - return Ort::Value::CreateTensor(memory_info, - static_cast(data), - size * sizeof(float16), - shape, - shape_len, - ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16); -} - -template -void Tensor::ORTCopyFromCpu(const T *data) { - auto binding = binding_.lock(); - PADDLE_ENFORCE_NOT_NULL(binding, - paddle::platform::errors::PreconditionNotMet( - "input tensor [%s] no binding ptr", name_)); - const char *device_name = place_ == PlaceType::kCPU ? "Cpu" : "Cuda"; - Ort::MemoryInfo memory_info( - device_name, OrtDeviceAllocator, device_, OrtMemTypeDefault); - size_t size = std::accumulate( - begin(shape_), end(shape_), 1UL, std::multiplies()); - auto buffer = buffer_.lock(); - size_t buffer_size = size * sizeof(T); - if (buffer_size > buffer->size()) { - buffer->resize(buffer_size); - } - std::memcpy(static_cast(buffer->data()), data, buffer_size); - - auto onnx_dtype = ONNX_TENSOR_ELEMENT_DATA_TYPE_UNDEFINED; - if (std::is_same::value) { - onnx_dtype = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT; - } else if (std::is_same::value) { - onnx_dtype = ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE; - } else if (std::is_same::value) { - onnx_dtype = ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64; - } else if (std::is_same::value) { - onnx_dtype = ONNX_TENSOR_ELEMENT_DATA_TYPE_INT32; - } else if (std::is_same::value) { - onnx_dtype = ONNX_TENSOR_ELEMENT_DATA_TYPE_UINT8; - } else if (std::is_same::value) { - onnx_dtype = ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8; - } else if (std::is_same::value) { - onnx_dtype = ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16; - } else { - PADDLE_THROW(paddle::platform::errors::InvalidArgument( - "Found undefined data type for onnxruntime, only supports " - "float16/float32/float64/int8/uint8/int32/int64.")); - } - - auto ort_value = Ort::Value::CreateTensor(memory_info, - buffer->data(), - buffer_size, - shape_.data(), - shape_.size(), - onnx_dtype); - binding->BindInput(name_.c_str(), ort_value); -} - template void Tensor::ORTCopyToCpu(T *data) const { auto binding = binding_.lock(); @@ -857,13 +744,6 @@ void Tensor::ORTCopyToCpu(T *data) const { } } -template void Tensor::ORTCopyFromCpu(const float *data); -template void Tensor::ORTCopyFromCpu(const int64_t *data); -template void Tensor::ORTCopyFromCpu(const int32_t *data); -template void Tensor::ORTCopyFromCpu(const uint8_t *data); -template void Tensor::ORTCopyFromCpu(const int8_t *data); -template void Tensor::ORTCopyFromCpu(const float16 *data); - template void Tensor::ORTCopyToCpu(float *data) const; template void Tensor::ORTCopyToCpu(int32_t *data) const; template void Tensor::ORTCopyToCpu(uint8_t *data) const; diff --git a/paddle/fluid/inference/api/onnxruntime_predictor.cc b/paddle/fluid/inference/api/onnxruntime_predictor.cc index 83919ad13967db514d2f631688b2fc995e008e1e..5313db644298695f38e24906d70b70e04951cb5d 100644 --- a/paddle/fluid/inference/api/onnxruntime_predictor.cc +++ b/paddle/fluid/inference/api/onnxruntime_predictor.cc @@ -24,11 +24,10 @@ #include #include -#include "paddle/fluid//platform/device/gpu/gpu_types.h" #include "paddle/fluid/framework/scope.h" -#include "paddle/fluid/framework/version.h" +#include "paddle/fluid/framework/var_type_traits.h" +#include "paddle/fluid/framework/variable_helper.h" #include "paddle/fluid/inference/analysis/helper.h" -#include "paddle/fluid/inference/analysis/passes/memory_optimize_pass.h" #include "paddle/fluid/inference/api/helper.h" #include "paddle/fluid/inference/api/paddle_inference_api.h" #include "paddle/fluid/inference/api/paddle_inference_pass.h" @@ -97,6 +96,7 @@ bool ONNXRuntimePredictor::Init() { } else { place_ = paddle::platform::CPUPlace(); } + scope_.reset(new paddle::framework::Scope()); char *onnx_proto = nullptr; int out_size; @@ -147,6 +147,8 @@ bool ONNXRuntimePredictor::Init() { Ort::Allocator allocator(session_, memory_info); size_t n_inputs = session_.GetInputCount(); + framework::proto::VarType::Type proto_type = + framework::proto::VarType::LOD_TENSOR; for (size_t i = 0; i < n_inputs; ++i) { auto input_name = session_.GetInputName(i, allocator); auto type_info = session_.GetInputTypeInfo(i); @@ -155,6 +157,10 @@ bool ONNXRuntimePredictor::Init() { ONNXTensorElementDataType data_type = type_info.GetTensorTypeAndShapeInfo().GetElementType(); input_desc_.emplace_back(ONNXDesc{input_name, shape, data_type}); + + auto *ptr = scope_->Var(input_name); + framework::InitializeVariable(ptr, proto_type); + allocator.Free(input_name); } @@ -249,13 +255,13 @@ bool ONNXRuntimePredictor::FindONNXDesc(const std::string &name, std::unique_ptr ONNXRuntimePredictor::GetInputTensor( const std::string &name) { - PADDLE_ENFORCE_EQ(FindONNXDesc(name, true), - true, - platform::errors::PreconditionNotMet( - "The in variable named %s is not found in the " - "ONNXPredictor.", - name)); - std::unique_ptr res(new ZeroCopyTensor(nullptr, this)); + PADDLE_ENFORCE_NOT_NULL(scope_->FindVar(name), + platform::errors::PreconditionNotMet( + "The in variable named %s is not found in the " + "ONNXPredictor.", + name)); + std::unique_ptr res( + new ZeroCopyTensor(static_cast(scope_.get()), this)); res->input_or_output_ = true; res->SetName(name); if (platform::is_cpu_place(place_)) { @@ -264,16 +270,6 @@ std::unique_ptr ONNXRuntimePredictor::GetInputTensor( auto gpu_place = place_; res->SetPlace(PaddlePlace::kGPU, gpu_place.GetDeviceId()); } - res->SetOrtMark(true); - res->SetOrtBinding(binding_); - auto iter = input_buffers_.find(name); - if (iter == input_buffers_.end()) { - std::vector i_vector; - input_buffers_[name] = std::make_shared>(i_vector); - res->SetOrtBuffer(input_buffers_[name]); - } else { - res->SetOrtBuffer(iter->second); - } return res; } @@ -306,6 +302,24 @@ std::unique_ptr ONNXRuntimePredictor::GetOutputTensor( return res; } +Ort::Value ONNXRuntimePredictor::GetOrtValue(const ONNXDesc &desc, + const char *device_name) { + Ort::MemoryInfo memory_info( + device_name, OrtDeviceAllocator, place_.GetDeviceId(), OrtMemTypeDefault); + auto *var = scope_->FindVar(desc.name); + auto *tensor = var->GetMutable(); + size_t size = + tensor->numel() * + framework::SizeOfType(framework::TransToProtoVarType(tensor->dtype())); + std::vector shape = phi::vectorize(tensor->dims()); + return Ort::Value::CreateTensor(memory_info, + static_cast(tensor->data()), + size, + shape.data(), + shape.size(), + desc.dtype); +} + bool ONNXRuntimePredictor::Run(const std::vector &inputs, std::vector *output_data, int batch_size) { @@ -315,7 +329,13 @@ bool ONNXRuntimePredictor::Run(const std::vector &inputs, bool ONNXRuntimePredictor::ZeroCopyRun() { try { - const char *device_name = place_ == PlaceType::kCPU ? "Cpu" : "Cuda"; + const char *device_name = platform::is_cpu_place(place_) ? "Cpu" : "Cuda"; + std::vector inputs; + inputs.reserve(input_desc_.size()); + for (auto desc : input_desc_) { + inputs.push_back(GetOrtValue(desc, device_name)); + binding_->BindInput(desc.name.c_str(), inputs.back()); + } for (auto output : output_desc_) { Ort::MemoryInfo out_memory_info(device_name, OrtDeviceAllocator, @@ -333,8 +353,10 @@ bool ONNXRuntimePredictor::ZeroCopyRun() { } std::unique_ptr ONNXRuntimePredictor::Clone(void *stream) { - LOG(ERROR) << "Not support Clone(), Please create new Predictor"; - return nullptr; + std::lock_guard lk(clone_mutex_); + auto *x = new ONNXRuntimePredictor(config_); + x->Init(); + return std::unique_ptr(x); } uint64_t ONNXRuntimePredictor::TryShrinkMemory() { diff --git a/paddle/fluid/inference/api/onnxruntime_predictor.h b/paddle/fluid/inference/api/onnxruntime_predictor.h index 27ce4529a8fe86b0b91a811b3d724271ca76c84a..b8f0ad0a5294132c56806746b7351da7907351b9 100644 --- a/paddle/fluid/inference/api/onnxruntime_predictor.h +++ b/paddle/fluid/inference/api/onnxruntime_predictor.h @@ -21,8 +21,6 @@ #include "onnxruntime_c_api.h" // NOLINT #include "onnxruntime_cxx_api.h" // NOLINT -#include "paddle/fluid/framework/naive_executor.h" -#include "paddle/fluid/framework/op_compatible_info.h" #include "paddle/fluid/inference/analysis/analyzer.h" #include "paddle/fluid/inference/api/api_impl.h" #include "paddle/fluid/inference/api/details/reset_tensor_array.h" @@ -94,7 +92,7 @@ class ONNXRuntimePredictor : public PaddlePredictor { /// \param[in] AnalysisConfig config /// explicit ONNXRuntimePredictor(const AnalysisConfig &config) - : config_(config), env_(ORT_LOGGING_LEVEL_WARNING, "onnx") { + : env_(ORT_LOGGING_LEVEL_WARNING, "onnx"), config_(config) { predictor_id_ = inference::GetUniqueId(); } /// @@ -176,6 +174,8 @@ class ONNXRuntimePredictor : public PaddlePredictor { /// std::unique_ptr Clone(void *stream = nullptr) override; + std::shared_ptr scope_; + protected: const void *GetDeviceContexts() const override; @@ -191,14 +191,24 @@ class ONNXRuntimePredictor : public PaddlePredictor { /// bool FindONNXDesc(const std::string &name, bool is_input); - private: - AnalysisConfig config_; + /// \brief get the Ort Value(input Tensor). + /// + /// \param[in] desc ONNXDesce(name、shape、dtype) + /// + /// \param[in] device_name "cpu" or "gpu" of device + /// + /// \return get a Ort::Value + /// + Ort::Value GetOrtValue(const ONNXDesc &desc, const char *device_name); + private: // ONNXRuntime Ort::Env env_; Ort::Session session_{nullptr}; std::shared_ptr binding_; + AnalysisConfig config_; + std::mutex clone_mutex_; platform::Place place_; std::vector input_desc_; std::vector output_desc_;