mmdeploy/csrc/core/operator.h
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

112 lines
3.3 KiB
C++

// Copyright (c) OpenMMLab. All rights reserved.
#ifndef MMDEPLOY_SRC_EXPERIMENTAL_PIPELINE_OPERATOR_H_
#define MMDEPLOY_SRC_EXPERIMENTAL_PIPELINE_OPERATOR_H_
#include "core/value.h"
namespace mmdeploy::graph {
using std::string;
using std::tuple;
using std::vector;
template <class V, std::enable_if_t<is_value_v<std::decay_t<V> >, bool> = true>
Result<void> Idxs2Keys(V&& array, const vector<string>& keys, Value& object) {
if (!std::forward<V>(array).is_array() || std::forward<V>(array).size() < keys.size()) {
return Status(eInvalidArgument);
}
if (!(object.is_null() || object.is_object())) {
return Status(eInvalidArgument);
}
for (int i = 0; i < keys.size(); ++i) {
object[keys[i]] = std::forward<V>(array)[i];
}
return success();
}
template <class V, std::enable_if_t<is_value_v<std::decay_t<V> >, bool> = true>
Result<Value> Idxs2Keys(V&& array, const vector<string>& keys) {
Value object = ValueType::kObject;
OUTCOME_TRY(Idxs2Keys(std::forward<V>(array), keys, object));
return object;
}
template <class V, std::enable_if_t<is_value_v<std::decay_t<V> >, bool> = true>
Result<void> Keys2Idxs(V&& object, const vector<string>& keys, Value& array) {
if (!std::forward<V>(object).is_object()) {
return Status(eInvalidArgument);
}
if (!(array.is_null() || array.is_array())) {
return Status(eInvalidArgument);
}
try {
for (const auto& key : keys) {
array.push_back(std::forward<V>(object)[key]);
}
} catch (...) {
// TODO: forward exception
return Status(eInvalidArgument);
}
return success();
}
template <class V, std::enable_if_t<is_value_v<std::decay_t<V> >, bool> = true>
Result<Value> Keys2Idxs(V&& object, const vector<string>& keys) {
Value array = ValueType::kArray;
OUTCOME_TRY(Keys2Idxs(std::forward<V>(object), keys, array));
return array;
}
template <class V, std::enable_if_t<is_value_v<std::decay_t<V> >, bool> = true>
Result<tuple<Value, vector<int> > > Flatten(V&& input) {
if (!input.is_array()) {
return Status(eInvalidArgument);
}
Value output = ValueType::kArray;
std::vector<int> idxs;
for (int i = 0; i < input.size(); ++i) {
auto inner = std::forward<V>(input)[i];
if (!inner.is_array()) {
return Status(eInvalidArgument);
}
for (auto& item : inner) {
output.push_back(std::move(item));
idxs.push_back(i);
}
}
idxs.push_back(input.size());
return {output, idxs};
}
template <class V, std::enable_if_t<is_value_v<std::decay_t<V> >, bool> = true>
Result<Value> Unflatten(V&& input, const vector<int>& idxs) {
if (!input.is_array()) {
return Status(eInvalidArgument);
}
Value output = ValueType::kArray;
for (int i = 0; i < idxs.back(); ++i) {
output.push_back(ValueType::kArray);
}
for (int i = 0; i < input.size(); ++i) {
if (idxs[i] >= output.size()) {
return Status(eInvalidArgument);
}
output[idxs[i]].push_back(std::forward<V>(input)[i]);
}
return output;
}
// object of arrays -> array of objects, all arrays must be of same length
Result<Value> DistribOA(const Value& oa);
// array of objects -> object of arrays, all objects must be isomorphic
Result<Value> DistribAO(const Value& ao);
// array of arrays -> array of arrays, this is equivalent to transpose
Result<Value> DistribAA(const Value& a);
} // namespace mmdeploy::graph
#endif // MMDEPLOY_SRC_EXPERIMENTAL_PIPELINE_OPERATOR_H_