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// This is a simple predictor binary that loads a TorchScript CV model and runs
// a forward pass with fixed input `torch::ones({1, 3, 224, 224})`.
// It's used for end-to-end integration test for custom mobile build.
#include <iostream>
#include <string>
#include <c10/util/irange.h>
#include <torch/script.h>
using namespace std;
namespace {
struct MobileCallGuard {
// Set InferenceMode for inference only use case.
c10::InferenceMode guard;
// Disable graph optimizer to ensure list of unused ops are not changed for
// custom mobile build.
torch::jit::GraphOptimizerEnabledGuard no_optimizer_guard{false};
};
torch::jit::Module loadModel(const std::string& path) {
MobileCallGuard guard;
auto module = torch::jit::load(path);
module.eval();
return module;
}
} // namespace
int main(int argc, const char* argv[]) {
if (argc < 2) {
std::cerr << "Usage: " << argv[0] << " <model_path>\n";
return 1;
}
auto module = loadModel(argv[1]);
auto input = torch::ones({1, 3, 224, 224});
auto output = [&]() {
MobileCallGuard guard;
return module.forward({input}).toTensor();
}();
std::cout << std::setprecision(3) << std::fixed;
for (const auto i : c10::irange(5)) {
std::cout << output.data_ptr<float>()[i] << std::endl;
}
return 0;
}
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