mirror of
https://github.com/open-mmlab/mmdeploy.git
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* minor changes * support windows * fix GCC build * fix lint * reformat * fix Windows build * fix GCC build * search backend ops for onnxruntime * fix lint * fix lint * code clean-up * code clean-up * fix clang build * fix trt support * fix cmake for ncnn * fix cmake for openvino * fix SDK Python API * handle ops for other backends (ncnn, trt) * handle SDK Python API library location * robustify linkage * fix cuda * minor fix for openvino & ncnn * use CMAKE_CUDA_ARCHITECTURES if set * fix cuda preprocessor * fix misc * fix pplnn & pplcv, drop support for pplcv<0.6.0 * robustify cmake * update build.md (#2) * build dynamic modules as module library & fix demo (partially) * fix candidate path for mmdeploy_python * move "enable CUDA" to cmake config for demo * refine demo cmake * add comment * fix ubuntu build * revert docs/en/build.md * fix C API * fix lint * Windows build doc (#3) * check in docs related to mmdeploy build on windows * update build guide on windows platform * update build guide on windows platform * make path of thirdparty libraries consistent * make path consistency * correct build command for custom ops * correct build command for sdk * update sdk build instructions * update doc * correct build command * fix lint * correct build command and fix lint Co-authored-by: lvhan <lvhan@pjlab.org> * trailing whitespace (#4) * minor fix * fix sr sdk model * fix type deduction * fix cudaFree after driver shutting down * update ppl.cv installation warning (#5) * fix device allocator threshold & fix lint * update doc (#6) * update ppl.cv installation warning * missing 'git clone' Co-authored-by: chenxin <chenxin2@sensetime.com> Co-authored-by: zhangli <zhangli@sensetime.com> Co-authored-by: lvhan028 <lvhan_028@163.com> Co-authored-by: lvhan <lvhan@pjlab.org>
112 lines
2.4 KiB
C++
112 lines
2.4 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#ifndef MMDEPLOY_SRC_EXPERIMENTAL_PIPELINE_IR_H_
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#define MMDEPLOY_SRC_EXPERIMENTAL_PIPELINE_IR_H_
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#include "core/model.h"
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#include "core/module.h"
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#include "core/registry.h"
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#include "core/status_code.h"
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#include "mpl/span.h"
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#include "utils/formatter.h"
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#if MMDEPLOY_USE_TASKFLOW
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#include "taskflow/taskflow.hpp"
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#endif
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namespace mmdeploy {
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namespace graph {
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using std::pair;
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using std::string;
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using std::unique_ptr;
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using std::vector;
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class TaskGraph;
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class Node;
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class MMDEPLOY_API Context {
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public:
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explicit Context(TaskGraph* graph) : graph_(graph) {}
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Value& current() { return context_.back(); }
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void push(Value&& ctx) { context_.push_back(std::move(ctx)); }
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Value pop() {
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auto ctx = std::move(context_.back());
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context_.pop_back();
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return ctx;
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}
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size_t size() const noexcept { return context_.size(); }
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bool empty() const noexcept { return context_.empty(); }
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std::vector<Result<Value>> Execute(Span<std::function<Result<Value>()>> tasks);
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private:
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vector<Value> context_;
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TaskGraph* graph_;
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};
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class MMDEPLOY_API TaskGraph {
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friend class Context;
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public:
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using TaskFunction = std::function<Result<void>(Context& ctx)>;
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class Handle {
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public:
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const std::string& name() const noexcept { return name_; }
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void set_name(const std::string& name) { name_ = name; }
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private:
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std::string name_;
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};
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~TaskGraph();
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TaskGraph() = default;
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TaskGraph(const TaskGraph&) = delete;
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TaskGraph& operator=(const TaskGraph&) = delete;
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Handle* Add(TaskFunction fn);
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Result<Value> Run(Value inputs);
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private:
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std::vector<Result<Value>> Execute(Span<std::function<Result<Value>()>> tasks);
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vector<TaskFunction> function_;
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vector<unique_ptr<Handle>> handle_;
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#if MMDEPLOY_USE_TASKFLOW
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tf::Executor executor_;
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#endif
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// profiling utils
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std::vector<double> time_;
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int64_t count_{};
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};
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class MMDEPLOY_API Node {
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public:
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virtual ~Node() = default;
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virtual void Build(TaskGraph& graph) = 0;
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const std::vector<std::string>& inputs() const noexcept { return inputs_; }
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const std::vector<std::string>& outputs() const noexcept { return outputs_; }
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const std::string& name() const noexcept { return name_; }
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protected:
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std::string name_;
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std::vector<std::string> inputs_;
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std::vector<std::string> outputs_;
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};
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} // namespace graph
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MMDEPLOY_DECLARE_REGISTRY(graph::Node);
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} // namespace mmdeploy
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#endif // MMDEPLOY_SRC_EXPERIMENTAL_PIPELINE_IR_H_
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