feat(core): added simple optimization example

CMakeLists.txt

@@ -32,6 +32,7 @@ macro(add_example name)
 endmacro()
 
 add_example(hello_world)
+add_example(simple_optimization_example)
 add_example(function_approx)
 add_example(time_serie_prediction)
 add_example(lstm_example)

src/simple_optimization_example.cpp

@@ -0,0 +1,67 @@
+#include <torch/torch.h>
+#include <cstdlib>
+#include <iostream>
+
+constexpr double kLearningRate = 0.001;
+constexpr int kMaxIterations = 100000;
+
+void native_run(double minimal) {
+  // Initial x value
+  auto x = torch::randn({1, 1}, torch::requires_grad(true));
+
+  for (size_t t = 0; t < kMaxIterations; t++) {
+    // Expression/value to be minimized
+    auto y = (x - minimal) * (x - minimal);
+    if (y.item<double>() < 1e-3) {
+      break;
+    }
+    // Calculate gradient
+    y.backward();
+
+    // Step x value without considering gradient
+    torch::NoGradGuard no_grad_guard;
+    x -= kLearningRate * x.grad();
+
+    // Reset the gradient of variable x
+    x.grad().reset();
+  }
+
+  std::cout << "[native] Actual minimal x value: " << minimal
+            << ", calculated optimal x value: " << x.item<double>() << std::endl;
+}
+
+void optimizer_run(double minimal) {
+  // Initial x value
+  std::vector<torch::Tensor> x;
+  x.push_back(torch::randn({1, 1}, torch::requires_grad(true)));
+  auto opt = torch::optim::SGD(x, torch::optim::SGDOptions(kLearningRate));
+
+  for (size_t t = 0; t < kMaxIterations; t++) {
+    // Expression/value to be minimized
+    auto y = (x[0] - minimal) * (x[0] - minimal);
+    if (y.item<double>() < 1e-3) {
+      break;
+    }
+    // Calculate gradient
+    y.backward();
+
+    // Step x value without considering gradient
+    opt.step();
+    // Reset the gradient of variable x
+    opt.zero_grad();
+  }
+
+  std::cout << "[optimizer] Actual minimal x value: " << minimal
+            << ", calculated optimal x value: " << x[0].item<double>() << std::endl;
+}
+
+// optimize y = (x - 10)^2
+int main(int argc, char* argv[]) {
+  if (argc < 2) {
+    std::cout << "Usage: " << argv[0] << " minimal_value\n";
+    return 1;
+  }
+  native_run(atof(argv[1]));
+  optimizer_run(atof(argv[1]));
+  return 0;
+}