PyTorch 源码阅读笔记（5）：TorchScript

class MyCell(torch.nn.Module):
    def __init__(self):
        super(MyCell, self).__init__()
        self.linear = torch.nn.Linear(4, 4)

    def forward(self, x, h):
        new_h = torch.tanh(self.linear(x) + h)
        return new_h, new_h
    
scripted_module = torch.jit.script(MyCell().eval())

#include <torch/script.h> // One-stop header.
#include <iostream>
#include <memory>

int main(int argc, const char* argv[]) {
  if (argc != 2) {
    std::cerr << "usage: example-app <path-to-exported-script-module>\n";
    return -1;
  }
  torch::jit::script::Module module;
  try {
    // Deserialize the ScriptModule from a file using torch::jit::load().
    module = torch::jit::load(argv[1]);
  }
  catch (const c10::Error& e) {
    std::cerr << "error loading the model\n";
    return -1;
  }
  std::cout << "ok\n";

  // Create a vector of inputs.
  std::vector<torch::jit::IValue> inputs;
  inputs.push_back(torch::ones({1, 3, 224, 224}));

  // Execute the model and turn its output into a tensor.
  at::Tensor output = module.forward(inputs).toTensor();
  std::cout << output.slice(/*dim=*/1, /*start=*/0, /*end=*/5) << '\n';

}