mmdeploy/csrc/graph/inference.cpp
lvhan028 36124f6205
Merge sdk (#251)
* check in cmake

* move backend_ops to csrc/backend_ops

* check in preprocess, model, some codebase and their c-apis

* check in CMakeLists.txt

* check in parts of test_csrc

* commit everything else

* add readme

* update core's BUILD_INTERFACE directory

* skip codespell on third_party

* update trt_net and ort_net's CMakeLists

* ignore clion's build directory

* check in pybind11

* add onnx.proto. Remove MMDeploy's dependency on ncnn's source code

* export MMDeployTargets only when MMDEPLOY_BUILD_SDK is ON

* remove useless message

* target include directory is wrong

* change target name from mmdeploy_ppl_net to mmdeploy_pplnn_net

* skip install directory

* update project's cmake

* remove useless code

* set CMAKE_BUILD_TYPE to Release by force if it isn't set by user

* update custom ops CMakeLists

* pass object target's source lists

* fix lint end-of-file

* fix lint: trailing whitespace

* fix codespell hook

* remove bicubic_interpolate to csrc/backend_ops/

* set MMDEPLOY_BUILD_SDK OFF

* change custom ops build command

* add spdlog installation command

* update docs on how to checkout pybind11

* move bicubic_interpolate to backend_ops/tensorrt directory

* remove useless code

* correct cmake

* fix typo

* fix typo

* fix install directory

* correct sdk's readme

* set cub dir when cuda version < 11.0

* change directory where clang-format will apply to

* fix build command

* add .clang-format

* change clang-format style from google to file

* reformat csrc/backend_ops

* format sdk's code

* turn off clang-format for some files

* add -Xcompiler=-fno-gnu-unique

* fix trt topk initialize

* check in config for sdk demo

* update cmake script and csrc's readme

* correct config's path

* add cuda include directory, otherwise compile failed in case of tensorrt8.2

* clang-format onnx2ncnn.cpp

Co-authored-by: zhangli <lzhang329@gmail.com>
Co-authored-by: grimoire <yaoqian@sensetime.com>
2021-12-07 10:57:55 +08:00

78 lines
2.2 KiB
C++

// Copyright (c) OpenMMLab. All rights reserved.
#include "graph/inference.h"
#include "archive/json_archive.h"
#include "archive/value_archive.h"
#include "core/operator.h"
#include "graph/common.h"
namespace mmdeploy::graph {
unique_ptr<Inference> Inference::Create(const Value& param) {
try {
auto inst = std::make_unique<Inference>();
auto& model_value = param["params"]["model"];
if (model_value.is_any<Model>()) {
inst->model_ = model_value.get<Model>();
} else if (model_value.is_string()) {
auto model_path = model_value.get<std::string>();
inst->model_ = Model(model_path);
} else {
ERROR("unsupported model specification");
return nullptr;
}
auto pipeline_json = inst->model_.ReadFile("pipeline.json").value();
auto json = nlohmann::json::parse(pipeline_json);
auto context = param.value("context", Value(ValueType::kObject));
context["model"] = inst->model_;
auto value = from_json<Value>(json);
value["context"] = context;
inst->pipeline_ = Pipeline::Create(value);
if (!inst->pipeline_) {
return nullptr;
}
from_value(param["input"], inst->inputs_);
from_value(param["output"], inst->outputs_);
return inst;
} catch (const std::exception& e) {
ERROR("unhandled exception: {}", e.what());
}
return nullptr;
}
void Inference::Build(TaskGraph& graph) {
auto enter = graph.Add([this](Context& ctx) -> Result<void> {
OUTCOME_TRY(auto args, Keys2Idxs(ctx.current(), inputs_));
ctx.push(std::move(args));
return success();
});
enter->set_name("inference/enter");
pipeline_->Build(graph);
auto exit = graph.Add([this](Context& ctx) -> Result<void> {
auto rets = ctx.pop();
OUTCOME_TRY(Idxs2Keys(std::move(rets), outputs_, ctx.current()));
return success();
});
exit->set_name("inference/exit");
}
class InferenceNodeCreator : public Creator<Node> {
public:
const char* GetName() const override { return "Inference"; }
int GetVersion() const override { return 0; }
std::unique_ptr<Node> Create(const Value& value) override { return Inference::Create(value); }
};
REGISTER_MODULE(Node, InferenceNodeCreator);
} // namespace mmdeploy::graph