Files
FastDeploy/fastdeploy/fastdeploy_model.cc
Jason 4b681581b1 Add custom operator for onnxruntime and fix paddle backend (#35)
Add custom operator for onnxruntime ans fix paddle backend
2022-07-23 22:21:36 +08:00

145 lines
4.3 KiB
C++

// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "fastdeploy/fastdeploy_model.h"
#include "fastdeploy/utils/utils.h"
namespace fastdeploy {
bool FastDeployModel::InitRuntime() {
FDASSERT(
CheckModelFormat(runtime_option.model_file, runtime_option.model_format),
"ModelFormatCheck Failed.");
if (runtime_initialized_) {
FDERROR << "The model is already initialized, cannot be initliazed again."
<< std::endl;
return false;
}
if (runtime_option.backend != Backend::UNKNOWN) {
if (runtime_option.backend == Backend::ORT) {
if (!IsBackendAvailable(Backend::ORT)) {
FDERROR
<< "Backend::ORT is not complied with current FastDeploy library."
<< std::endl;
return false;
}
} else if (runtime_option.backend == Backend::TRT) {
if (!IsBackendAvailable(Backend::TRT)) {
FDERROR
<< "Backend::TRT is not complied with current FastDeploy library."
<< std::endl;
return false;
}
} else if (runtime_option.backend == Backend::PDINFER) {
if (!IsBackendAvailable(Backend::PDINFER)) {
FDERROR << "Backend::PDINFER is not compiled with current FastDeploy "
"library."
<< std::endl;
return false;
}
} else {
FDERROR
<< "Only support Backend::ORT / Backend::TRT / Backend::PDINFER now."
<< std::endl;
return false;
}
runtime_ = new Runtime();
if (!runtime_->Init(runtime_option)) {
return false;
}
runtime_initialized_ = true;
return true;
}
if (runtime_option.device == Device::CPU) {
return CreateCpuBackend();
} else if (runtime_option.device == Device::GPU) {
#ifdef WITH_GPU
return CreateGpuBackend();
#else
FDERROR << "The compiled FastDeploy library doesn't support GPU now."
<< std::endl;
return false;
#endif
}
FDERROR << "Only support CPU/GPU now." << std::endl;
return false;
}
bool FastDeployModel::CreateCpuBackend() {
if (valid_cpu_backends.size() == 0) {
FDERROR << "There's no valid cpu backends for model: " << ModelName()
<< std::endl;
return false;
}
for (size_t i = 0; i < valid_cpu_backends.size(); ++i) {
if (!IsBackendAvailable(valid_cpu_backends[i])) {
continue;
}
runtime_option.backend = valid_cpu_backends[i];
runtime_ = new Runtime();
if (!runtime_->Init(runtime_option)) {
return false;
}
runtime_initialized_ = true;
return true;
}
FDERROR << "Found no valid backend for model: " << ModelName() << std::endl;
return false;
}
bool FastDeployModel::CreateGpuBackend() {
if (valid_gpu_backends.size() == 0) {
FDERROR << "There's no valid gpu backends for model: " << ModelName()
<< std::endl;
return false;
}
for (size_t i = 0; i < valid_gpu_backends.size(); ++i) {
if (!IsBackendAvailable(valid_gpu_backends[i])) {
continue;
}
runtime_option.backend = valid_gpu_backends[i];
runtime_ = new Runtime();
if (!runtime_->Init(runtime_option)) {
return false;
}
runtime_initialized_ = true;
return true;
}
FDERROR << "Cannot find an available gpu backend to load this model."
<< std::endl;
return false;
}
bool FastDeployModel::Infer(std::vector<FDTensor>& input_tensors,
std::vector<FDTensor>* output_tensors) {
return runtime_->Infer(input_tensors, output_tensors);
}
void FastDeployModel::EnableDebug() {
#ifdef FASTDEPLOY_DEBUG
debug_ = true;
#else
FDLogger() << "The compile FastDeploy is not with -DENABLE_DEBUG=ON, so "
"cannot enable debug mode."
<< std::endl;
debug_ = false;
#endif
}
bool FastDeployModel::DebugEnabled() { return debug_; }
} // namespace fastdeploy