mmdeploy/csrc/core/graph.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

79 lines
2.0 KiB
C++

// Copyright (c) OpenMMLab. All rights reserved.
#include "core/graph.h"
#include "archive/value_archive.h"
namespace mmdeploy::graph {
TaskGraph::Handle* TaskGraph::Add(TaskFunction fn) {
function_.push_back(std::move(fn));
handle_.push_back(std::make_unique<Handle>());
return handle_.back().get();
}
TaskGraph::~TaskGraph() {
for (int i = 0; i < time_.size(); ++i) {
INFO("node {} ({}): {} ms", i, handle_[i]->name(), static_cast<float>(time_[i]) / count_);
}
}
Result<Value> TaskGraph::Run(Value inputs) {
Context ctx(this);
ctx.push(std::move(inputs));
time_.resize(function_.size());
for (int i = 0; i < function_.size(); ++i) {
auto t0 = std::chrono::high_resolution_clock::now();
OUTCOME_TRY(function_[i](ctx));
auto t1 = std::chrono::high_resolution_clock::now();
auto dt = std::chrono::duration<double, std::milli>(t1 - t0).count();
time_[i] += dt;
}
count_ += 1;
return ctx.pop();
}
std::vector<Result<Value>> TaskGraph::Execute(Span<std::function<Result<Value>()>> tasks) {
#if MMDEPLOY_USE_TASKFLOW
std::vector<tf::Future<std::optional<Result<Value>>>> futures;
futures.reserve(tasks.size());
for (auto& task : tasks) {
futures.push_back(executor_.async(task));
}
executor_.wait_for_all();
std::vector<Result<Value>> rets;
rets.reserve(tasks.size());
for (auto& future : futures) {
Result<Value> ret = Status(eUnknown);
try {
ret = *future.get();
} catch (...) {
ret = Status(eFail);
}
rets.push_back(std::move(ret));
}
return rets;
#else
std::vector<Result<Value>> rets;
rets.reserve(tasks.size());
for (auto& task : tasks) {
Result<Value> ret = Status(eUnknown);
try {
ret = task();
} catch (const Exception& e) {
ret = failure(e.code());
} catch (...) {
ret = Status(eFail);
}
rets.push_back(std::move(ret));
}
return rets;
#endif
}
std::vector<Result<Value>> Context::Execute(Span<std::function<Result<Value>()>> tasks) {
return graph_->Execute(tasks);
}
} // namespace mmdeploy::graph