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Pnnx generate model ncnn.cpp #5694

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Pnnx generate model ncnn.cpp #5694

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5cfbc30
cpp test
Qi-qi0317 Sep 10, 2024
4b3d8c7
cpp test and CMakeList change
Qi-qi0317 Sep 10, 2024
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80 changes: 79 additions & 1 deletion tools/pnnx/src/save_ncnn.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -462,7 +462,85 @@ int save_ncnn(const Graph& g, const std::string& parampath, const std::string& b

fclose(pyfp);

// Generate C++ test
std::string cpppath = pypath.substr(0, pypath.find_last_of('.')) + ".cpp";
FILE* cppfp = fopen(cpppath.c_str(), "wb");
if (!cppfp)
{
fprint(stderr, "fopen %s failed\n", cpppath.c_str());
return -1;
}

fprintf(cppfp, "#include <iostream>\n");
fprintf(cppfp, "#include <vector>\n");
fprintf(cppfp, "#include <random>\n");
fprintf(cppfp, "#include \"ncnn.hpp\"\n\n");

fprintf(cppfp, "void test_inference(const std::string& parampath, const std::string& binpath)\n");
fprintf(cppfp, "{\n");
fprintf(cppfp, " ncnn:::Net net;\n");
fprintf(cppfp, " net.load_param(parampath.c_str());\n");
fprintf(cppfp, " ner.load_model(binpath.c_str());\n\n");

for (int input_index = 0;; input_index++)
{
std::string input_name = std::string("in") + std::to_string(input_index);
const Operand* r = g.get_operand(input_name);
if (!r)
break;

fprintf(cppfp, " std::vector<float> %s(", input_name.c_str());
for (size_t i = 0; i < r->shape.size(); i++)
{
fprintf(cppfp, "%d", r->shape[i]);
if (i + 1 != r->shape.size())
fprintf(cppfp, " * ");
}
fprint(cppfp, ");\n");

if (type_is_integer(r->type))
{
fprintf(cppfp, " std::default_random_engine engine;\n");
fprintf(cppfp, " std::uniform_int_distribution<int> dist(0, 9);\n");
fprintf(cppfp, " for (float& v : %s) {{ v = dist(engine); }}\n", input_name.c_str());

}
else
{
fprintf(cppfp, " std::default_random_engine engine;\n");
fprintf(cppfp, " std::uniform_real_distribution<float> dist(0.0, 1.0);\n");
fprintf(cppfp, " for (float& v : %s) {{ v = dist(engine); }}\n", input_name.c_str());
}

fprintf(cppfp, " ncnn::Mat %s_mat = ncnn::Mat::from_pixels(%s.data(), ncnn::Mat::PixelType::PIXEL_GRAY, %d, %d);\n",
input_name.c_str(), input_name.c_str(), r->shape[2], r->shape[1]);
// Assuming shape order: batch, height, width
fprintf(cppfp, " net.input(\"net_input\", %s_mat);\n", input_name.c_str());

}
fprintf(cppfp, " std::vector<ncnn::Mat> output;\n");
fprintf(cppfp, " net.extract(\"output\", output);\n\n");

fprintf(cppfp, " for (const auto& m : output) {\n");
fprintf(cppfp, " const float* data = m.channel_data(0);\n");
fprintf(cppfp, " for (int i = 0; i < m.w; i++) {\n");
fprintf(cppfp, " std::cout << data[i] << \" \";\n");
fprintf(cppfp, " }\n");
fprintf(cppfp, " std::cout << std::endl;\n");
fprintf(cppfp, " }\n");

fprintf(cppfp, "}\n\n");

fprintf(cppfp, "int main()\n");
fprintf(cppfp, "{\n");
fprintf(cppfp, " std::string parampath = \"%s\";\n", parampath.c_str());
fprintf(cppfp, " std::string binpath = \"%s\";\n", binpath.c_str());
fprintf(cppfp, " test_inference(parampath, binpath);\n");
fprintf(cppfp, " return 0;\n");
fprintf(cppfp, "}\n");

fclose(cppfp);

return 0;
}

} // namespace pnnx
1 change: 1 addition & 0 deletions tools/pnnx/tests/ncnn/CMakeLists.txt
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Expand Up @@ -3,6 +3,7 @@ find_package(Python3 REQUIRED COMPONENTS Interpreter)

macro(pnnx_ncnn_add_test name)
add_test(NAME test_ncnn_${name} COMMAND ${CMAKE_COMMAND} -DPYTHON_EXECUTABLE=${Python3_EXECUTABLE} -DPYTHON_SCRIPT=${CMAKE_CURRENT_SOURCE_DIR}/test_${name}.py -P ${CMAKE_CURRENT_SOURCE_DIR}/../run_test.cmake)
add_test(NAME test_cpp_${name} COMMAND ${CMAKE_COMMAND} -DCPP_EXECUTABLE=${Cpp_EXECUTABLE} -DCPP_SCRIPT=${CMAKE_CURRENT_SOURCE_DIR}/test_${name}.cpp -P ${CMAKE_CURRENT_SOURCE_DIR}/../run_test.cmake)
endmacro()

pnnx_ncnn_add_test(F_adaptive_avg_pool1d)
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