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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
// 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