Use std::unique_ptr for DeviceMesh and FusionExecutorCache in direct bindings

python/python_direct/multidevice.cpp

@@ -73,15 +73,15 @@ void bindDeviceMesh(py::module& nvfuser) {
   py::class_<DeviceMesh> device_mesh(nvfuser, "DeviceMesh", py::module_local());
   device_mesh.def(
       py::init([](at::Tensor devices) {
-        return new DeviceMesh(std::move(devices));
+        return std::make_unique<DeviceMesh>(std::move(devices));
       }),
       py::arg("devices"),
       R"(
 Create a new DeviceMesh from torch.Tensor.
 )");
   device_mesh.def(
       py::init([](const std::vector<int64_t>& devices) {
-        return new DeviceMesh(at::tensor(devices));
+        return std::make_unique<DeviceMesh>(at::tensor(devices));
       }),
       py::arg("devices"),
       R"(

python/python_direct/runtime.cpp

@@ -221,7 +221,7 @@ void bindFusionExecutorCache(py::module& nvfuser) {
                       int64_t fusion_id,
                       bool auto_schedule) {
             // Make a copy of the fusion for FusionExecutorCache to own.
-            return new FusionExecutorCache(
+            return std::make_unique<FusionExecutorCache>(
                 std::make_unique<Fusion>(*fusion), fusion_id, auto_schedule);
           }),
           py::arg("fusion"),

python/version.txt

@@ -1 +1 @@
-0.2.34
+0.2.35