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* 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>
68 lines
2.1 KiB
C++
68 lines
2.1 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
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#include "graph/pipeline.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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unique_ptr<Pipeline> Pipeline::Create(const Value& config) {
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try {
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auto inst = std::make_unique<Pipeline>();
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from_value(config["pipeline"]["input"], inst->inputs_);
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from_value(config["pipeline"]["output"], inst->outputs_);
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for (auto task_config : config["pipeline"]["tasks"]) {
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auto name = task_config.value("name", std::string{});
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auto type = task_config.value("type", std::string{});
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if (config.contains("context")) {
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// ERROR("passing context: {}", config["context"]);
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task_config["context"].update(config["context"]);
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}
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if (auto node = CreateFromRegistry<Node>(task_config); node) {
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inst->nodes_.push_back(std::move(node).value());
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// } else if (auto task = Task::Create(task_config); task) {
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// inst->nodes_.push_back(std::move(task));
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} else {
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ERROR("could not create {}:{}", name, type);
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return nullptr;
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}
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}
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return inst;
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} catch (...) {
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return nullptr;
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}
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}
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void Pipeline::Build(TaskGraph& graph) {
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auto enter = graph.Add([this](Context& ctx) -> Result<void> {
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auto args = ctx.pop();
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ctx.push(ValueType::kObject);
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OUTCOME_TRY(Idxs2Keys(std::move(args), inputs_, ctx.current()));
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return success();
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});
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enter->set_name("pipeline/enter");
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for (const auto& node : nodes_) {
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node->Build(graph);
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}
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auto exit = graph.Add([this](Context& ctx) -> Result<void> {
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auto rets = ctx.pop();
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ctx.push(ValueType::kArray);
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OUTCOME_TRY(Keys2Idxs(std::move(rets), outputs_, ctx.current()));
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return success();
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});
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exit->set_name("pipeline/exit");
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}
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class PipelineCreator : public Creator<Node> {
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public:
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const char* GetName() const override { return "Pipeline"; }
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int GetVersion() const override { return 0; }
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std::unique_ptr<Node> Create(const Value& value) override { return Pipeline::Create(value); }
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};
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REGISTER_MODULE(Node, PipelineCreator);
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} // namespace mmdeploy::graph
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