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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
// Copyright (c) OpenMMLab. All rights reserved.
#include "operator.h"
namespace mmdeploy::graph {
Result<void> Gather(const Value::Array& array, const vector<int>& idxs, Value::Array& output) {
if (idxs.empty()) {
return success();
}
auto max_idx = *max_element(begin(idxs), end(idxs));
if (array.size() <= max_idx) {
return Status(eOutOfRange);
}
output.reserve(output.size() + idxs.size());
for (const auto& idx : idxs) {
output.push_back(array[idx]);
}
return success();
}
Result<void> Gather(Value::Array&& array, const vector<int>& idxs, Value::Array& output) {
if (idxs.empty()) {
return success();
}
auto max_idx = *max_element(begin(idxs), end(idxs));
if (array.size() <= max_idx) {
return Status(eOutOfRange);
}
output.reserve(output.size() + idxs.size());
for (const auto& idx : idxs) {
output.push_back(std::move(array[idx]));
}
return success();
}
Result<void> Gather(const Value::Object& object, const vector<std::string>& keys,
Value::Array& output) {
output.reserve(output.size() + keys.size());
try {
for (const auto& key : keys) {
output.push_back(object.at(key));
}
} catch (const std::out_of_range& e) {
return Status(eOutOfRange);
}
return success();
}
Result<void> Gather(Value::Object&& object, const vector<std::string>& keys, Value::Array& output) {
output.reserve(output.size() + keys.size());
try {
for (const auto& key : keys) {
output.push_back(std::move(object.at(key)));
}
} catch (const std::out_of_range& e) {
return Status(eOutOfRange);
}
return success();
}
Result<void> Scatter(Value::Array array, const vector<int>& idxs, Value::Array& output) {
if (array.size() < idxs.size()) {
return Status(eOutOfRange);
}
for (int i = 0; i < idxs.size(); ++i) {
output[idxs[i]] = std::move(array[i]);
}
return success();
}
Result<void> Scatter(Value::Array array, const vector<std::string>& keys, Value::Object& output) {
if (array.size() < keys.size()) {
return Status(eOutOfRange);
}
for (int i = 0; i < keys.size(); ++i) {
output.emplace(keys[i], std::move(array[i]));
}
return success();
}
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
Result<Value> DistribOA(const Value& oa) {
if (!oa.is_object()) {
return Status(eInvalidArgument);
}
Value ao = ValueType::kArray;
for (auto inner = oa.begin(); inner != oa.end(); ++inner) {
if (!inner->is_array()) {
return Status(eInvalidArgument);
}
if (ao.empty()) {
for (int i = 0; i < inner->size(); ++i) ao.push_back(ValueType::kObject);
}
if (inner->size() != oa.size()) {
return Status(eInvalidArgument);
}
for (int i = 0; i < inner->size(); ++i) {
ao[i][inner.key()] = (*inner)[i];
}
}
return ao;
}
Result<Value> DistribAO(const Value& ao) {
if (!ao.is_array()) {
return Status(eInvalidArgument);
}
Value oa = ValueType::kObject;
for (const auto& inner : ao) {
if (inner.is_object()) {
return Status(eInvalidArgument);
}
if (oa.empty()) {
for (auto item = inner.begin(); item != inner.end(); ++item) {
oa[item.key()] = ValueType::kObject;
}
}
if (inner.size() != oa.size()) {
return Status(eInvalidArgument);
}
for (auto item = inner.begin(); item != inner.end(); ++item) {
if (!oa.contains(item.key())) {
return Status(eInvalidArgument);
}
oa[item.key()].push_back(*item);
}
}
return oa;
}
Result<Value> DistribAA(const Value& a) {
if (!a.is_array()) {
return Status(eInvalidArgument);
}
auto ta = Value::Array{};
for (const auto& inner : a.get_ref<const Value::Array&>()) {
if (!inner.is_array()) {
return Status(eInvalidArgument);
}
if (ta.empty()) {
ta.reserve(inner.size());
for (int i = 0; i < inner.size(); ++i) {
ta.emplace_back(Value::kArray);
}
}
if (inner.size() != ta.size()) {
return Status(eInvalidArgument);
}
for (int i = 0; i < inner.size(); ++i) {
ta[i].push_back(inner[i]);
}
}
return ta;
}
} // namespace mmdeploy::graph