mirror of
https://github.com/open-mmlab/mmdeploy.git
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a494a6f6ff
* sync SDK changes according to performance benchmarks * fix end-of-file lint * fix clang-format issue * fix clang-format by adding 'clang-format off' * remove useless casts * remove 'data' argument of 'operator()' * change 'Tensor2Img' to 'TensorToImg' according to spec * correct tensor's name according spec Co-authored-by: lvhan028 <lvhan_028@163.com>
53 lines
1.5 KiB
C++
53 lines
1.5 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "graph/inference.h"
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#include "archive/json_archive.h"
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#include "archive/value_archive.h"
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#include "core/operator.h"
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#include "graph/common.h"
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namespace mmdeploy::graph {
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Inference::Inference(const Value& cfg) : BaseNode(cfg) {
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auto& model_value = cfg["params"]["model"];
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if (model_value.is_any<Model>()) {
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model_ = model_value.get<Model>();
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} else if (model_value.is_string()) {
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auto model_path = model_value.get<std::string>();
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model_ = Model(model_path);
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} else {
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ERROR("unsupported model specification");
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throw_exception(eInvalidArgument);
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}
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auto pipeline_json = model_.ReadFile("pipeline.json").value();
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auto json = nlohmann::json::parse(pipeline_json);
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auto context = cfg.value("context", Value(ValueType::kObject));
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context["model"] = model_;
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auto value = from_json<Value>(json);
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value["context"] = context;
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pipeline_ = std::make_unique<Pipeline>(value);
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if (!pipeline_) {
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ERROR("failed to create pipeline");
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throw_exception(eFail);
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}
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}
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void Inference::Build(TaskGraph& graph) { pipeline_->Build(graph); }
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class InferenceNodeCreator : public Creator<Node> {
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public:
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const char* GetName() const override { return "Inference"; }
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int GetVersion() const override { return 0; }
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std::unique_ptr<Node> Create(const Value& value) override {
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return std::make_unique<Inference>(value);
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}
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};
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REGISTER_MODULE(Node, InferenceNodeCreator);
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} // namespace mmdeploy::graph
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