Add movable example (#225)

Summary:
Pull Request resolved: #225

Creates a basic movable example and adds it to CI.

Test Plan: Imported from OSS

Reviewed By: d4l3k

Differential Revision: D40646969

Pulled By: PaliC

fbshipit-source-id: 18bde29f0e2f89def05033f95b246da2513487f1

Author: PaliC

.github/workflows/runtime_tests.yaml

@@ -40,6 +40,7 @@ jobs:
         run: |
           docker run --rm multipy bash -c "if [[ ${{ matrix.python-minor-version }} -lt 8 ]]; then source ~/venvs/multipy/bin/activate; fi && examples/build/hello_world_example"
           docker run --rm multipy bash -c "if [[ ${{ matrix.python-minor-version }} -lt 8 ]]; then source ~/venvs/multipy/bin/activate; fi && python3 examples/quickstart/gen_package.py && ./examples/build/quickstart my_package.pt"
+          docker run --rm multipy bash -c "if [[ ${{ matrix.python-minor-version }} -lt 8 ]]; then source ~/venvs/multipy/bin/activate; fi && ./examples/build/movable_example"
 
       - name: Compat Tests
         run: |

examples/CMakeLists.txt

@@ -23,3 +23,7 @@ target_link_libraries(hello_world_example PUBLIC "-Wl,--no-as-needed -rdynamic"
 
 add_executable(quickstart quickstart/quickstart.cpp)
 target_link_libraries(quickstart PUBLIC "-Wl,--no-as-needed -rdynamic" dl pthread util multipy c10 torch_cpu)
+
+add_executable(movable_example movable_example/movable_example.cpp)
+target_link_libraries(movable_example PUBLIC "-Wl,--no-as-needed -rdynamic" dl pthread util multipy c10 torch_cpu)
+

examples/movable_example/movable_example.cpp

@@ -0,0 +1,38 @@
+// Basic example of using `ReplicatedObject` in `torch::deploy`.
+#include <multipy/runtime/deploy.h>
+#include <multipy/runtime/path_environment.h>
+#include <torch/script.h>
+#include <torch/torch.h>
+
+#include <iostream>
+#include <memory>
+
+int main(int argc, const char* argv[]) {
+  torch::deploy::InterpreterManager m(4);
+
+  try {
+    // Load the model from the torch.package.
+    auto I = m.acquireOne();
+    std::vector<torch::jit::IValue> constructor_inputs;
+    auto model_obj = I.global("torch.nn", "Conv2d")({6, 2, 2, 1});
+    auto rObj = m.createMovable(model_obj, &I);
+    auto I2 = m.acquireOne();
+    auto model_obj2 = I2.fromMovable(rObj);
+    rObj.unload(); // free the replicated object
+
+    // Create a vector of inputs.
+    std::vector<torch::jit::IValue> inputs;
+    inputs.push_back(torch::ones({1, 6, 6, 6}));
+
+    // Execute the model and turn its output into a tensor.
+    at::Tensor output = model_obj2(inputs).toIValue().toTensor();
+    std::cout << output.slice(/*dim=*/1, /*start=*/0, /*end=*/5) << '\n';
+
+  } catch (const c10::Error& e) {
+    std::cerr << "error creating movable\n";
+    std::cerr << e.msg();
+    return -1;
+  }
+
+  std::cout << "ok\n";
+}