Function init_graph_rt

imperative/python/src/graph_rt.cpp:120–735

const std::unique_ptr<mgb::OprFootprint> _imperative_sm_opr_footprint_ptr{
        std::make_unique<mgb::OprFootprint>()};
void init_graph_rt(py::module m) {
    def_rendezvous<DeviceTensorND>(m, "DeviceTensorNDRendezvous");

    def_rendezvous<HostNDWithEvent>(m, "HostTensorNDRendezvous");

    def_rendezvous<TensorAttr>(m, "TensorAttrRendezvous");

    Py_Varnode =
            py::class_<cg::VarNode, GraphNodePtr<cg::VarNode>>(m, "VarNode")
                    .def_property_readonly(
                            "owner", [](cg::VarNode* v) { return v->owner_opr(); })
                    .def_property_readonly(
                            "graph", [](cg::VarNode* v) { return v->owner_graph(); })
                    .def_property(
                            "name", py::overload_cast<>(&VarNode::name, py::const_),
                            py::overload_cast<std::string>(&VarNode::name))
                    .def_property_readonly(
                            "dtype", [](cg::VarNode* v) { return v->dtype(); })
                    .def_property_readonly(
                            "comp_node", [](cg::VarNode* v) { return v->comp_node(); })
                    .def_property_readonly(
                            "shape",
                            [](cg::VarNode* v) -> const TensorShape* {
                                auto&& mgr = v->owner_graph()->static_infer_manager();
                                return mgr.infer_shape_fallible(v);
                            })
                    .def_property_readonly(
                            "value",
                            [](cg::VarNode* v) -> py::object {
                                auto&& mgr = v->owner_graph()->static_infer_manager();
                                auto&& type = mgr.get_infer_type(v);
                                using InferType = cg::static_infer::InferType;
                                if (!(type.value &
                                      (InferType::CONST | InferType::RT_STATIC))) {
                                    return py::none();
                                }
                                auto* val = mgr.infer_value_fallible(v);
                                if (!val) {
                                    return py::none();
                                }
                                return py::cast(*val).attr("numpy")();
                            })
                    .def_property_readonly(
                            "id", [](cg::VarNode* v) { return (v->id()); })
                    .def("__repr__", [](cg::VarNode* v) { return "Var:" + v->name(); });

    py::class_<cg::OperatorNodeBase, GraphNodePtr<cg::OperatorNodeBase>>(
            m, "OperatorNode")
            .def_property_readonly(
                    "graph",
                    [](cg::OperatorNodeBase* opr) { return opr->owner_graph(); })
            .def_property(
                    "name",
                    py::overload_cast<>(&cg::OperatorNodeBase::name, py::const_),
                    py::overload_cast<std::string>(&cg::OperatorNodeBase::name))
            .def_property_readonly(
                    "inputs",
                    [](cg::OperatorNodeBase* opr) { return to_tuple(opr->input()); })