Function main

tests/engine/AsyncModuleTest.cpp:31–59

};

int main() {
  mllm::initializeContext();
  {
    auto net = FooNet("foo_net");

    // Make some fake weights
    auto params = ParameterFile::create();
    for (int i = 0; i < 4; ++i) {
      auto name = "foo_net.linear_" + std::to_string(i);
      auto w = Tensor::empty({2048, 1024}).setMemType(kParamsNormal).setName(name + ".weight").alloc();
      auto b = Tensor::empty({2048}).setMemType(kParamsNormal).setName(name + ".bias").alloc();
      params->push(w.name(), w);
      params->push(b.name(), b);
    }
    net.load(params);

    // Async run.
    // The net will not run, until mllm::async::wait is called.
    auto future_0 = mllm::async::fork(net, Tensor::empty({1, 12, 1024, 1024}, kFloat32).alloc());
    auto future_1 = mllm::async::fork(net, Tensor::empty({1, 12, 1024, 1024}, kFloat32).alloc());

    // Run future_0 and future_1 async.
    auto [outs_0, outs_1] = mllm::async::wait(future_0, future_1);

    mllm::print(outs_0[0].shape(), outs_0[1].shape(), outs_0[2].shape(), outs_0[3].shape());
    mllm::print(outs_1[0].shape(), outs_1[1].shape(), outs_1[2].shape(), outs_1[3].shape());
  }
  mllm::memoryReport();
}