mirror of
https://github.com/open-mmlab/mmdeploy.git
synced 2025-01-14 08:09:43 +08:00
36124f6205
* 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>
100 lines
2.4 KiB
C++
100 lines
2.4 KiB
C++
// Copyright (c) OpenMMLab. All rights reserved.
|
|
|
|
#include <fstream>
|
|
#include <iostream>
|
|
#include <sstream>
|
|
|
|
#include "catch.hpp"
|
|
#include "core/model.h"
|
|
#include "core/net.h"
|
|
|
|
using namespace mmdeploy;
|
|
|
|
static Value ReadFileContent(const char* path) {
|
|
std::ifstream ifs(path, std::ios::binary);
|
|
ifs.seekg(0, std::ios::end);
|
|
auto size = ifs.tellg();
|
|
ifs.seekg(0, std::ios::beg);
|
|
Value::Binary bin(size);
|
|
ifs.read((char*)bin.data(), size);
|
|
return bin;
|
|
}
|
|
|
|
template <typename T, typename V = typename mmdeploy::uncvref_t<T>::value_type,
|
|
std::enable_if_t<!std::is_same_v<V, bool> && std::is_integral_v<V>, int> = 0>
|
|
std::string shape_string(const T& v) {
|
|
std::stringstream ss;
|
|
ss << "(";
|
|
auto first = true;
|
|
for (const auto& x : v) {
|
|
if (!first) {
|
|
ss << ", ";
|
|
} else {
|
|
first = false;
|
|
}
|
|
ss << x;
|
|
}
|
|
ss << ")";
|
|
return ss.str();
|
|
}
|
|
|
|
TEST_CASE("test pplnn", "[net]") {
|
|
auto backend = "pplnn";
|
|
Model model("../../resnet50");
|
|
REQUIRE(model);
|
|
auto img_path = "../../sea_lion.txt";
|
|
|
|
auto creator = Registry<Net>::Get().GetCreator(backend);
|
|
REQUIRE(creator);
|
|
Device device{"cpu"};
|
|
auto stream = Stream::GetDefault(device);
|
|
// clang-format off
|
|
Value net_config{
|
|
{"context", {
|
|
{"device", device},
|
|
{"model", model},
|
|
{"stream", stream}
|
|
}
|
|
},
|
|
{"name", "resnet50"}
|
|
};
|
|
// clang-format on
|
|
auto net = creator->Create(net_config);
|
|
|
|
std::vector<float> img(3 * 224 * 224);
|
|
{
|
|
std::ifstream ifs(img_path);
|
|
REQUIRE(ifs.is_open());
|
|
for (auto& x : img) {
|
|
ifs >> x;
|
|
}
|
|
}
|
|
|
|
std::vector<TensorShape> input_shape{{1, 3, 224, 224}};
|
|
REQUIRE(net->Reshape(input_shape));
|
|
|
|
auto inputs = net->GetInputTensors().value();
|
|
|
|
for (auto& tensor : inputs) {
|
|
std::cout << "input: " << tensor.name() << " " << shape_string(tensor.shape()) << "\n";
|
|
}
|
|
|
|
REQUIRE(inputs.front().CopyFrom(img.data(), stream));
|
|
REQUIRE(stream.Wait());
|
|
|
|
REQUIRE(net->Forward());
|
|
|
|
auto outputs = net->GetOutputTensors().value();
|
|
|
|
for (auto& tensor : outputs) {
|
|
std::cout << "output: " << tensor.name() << " " << shape_string(tensor.shape()) << "\n";
|
|
}
|
|
|
|
std::vector<float> logits(1000);
|
|
REQUIRE(outputs.front().CopyTo(logits.data(), stream));
|
|
REQUIRE(stream.Wait());
|
|
|
|
auto cls_id = std::max_element(logits.begin(), logits.end()) - logits.begin();
|
|
std::cout << "class id = " << cls_id << "\n";
|
|
}
|