Update pythin bindings for options (#14)

onnxruntime/python/onnxruntime_pybind_state.cc

@@ -231,21 +231,37 @@ void addObjectMethods(py::module& m) {
   py::add_ostream_redirect(m, "onnxruntime_ostream_redirect");
   py::class_<SessionOptions>(m, "SessionOptions", R"pbdoc(Configuration information for a session.)pbdoc")
       .def(py::init())
+      .def_readwrite("enable_mem_pattern", &SessionOptions::enable_mem_pattern,
+                     R"pbdoc(Enables the memory pattern optimization.
+The idea is if the input shapes are the same, we could trace the internal memory allocation
+and generate a memory pattern for future request. So next time we could just do one allocation
+with a big chunk for all the internal memory allocation. Default is true.)pbdoc")
+      .def_readwrite("enable_cpu_mem_arena", &SessionOptions::enable_cpu_mem_arena,
+                     R"pbdoc(Enables the memory arena on CPU. Arena may pre-allocate memory for future usage.
+Set this option to false if you don't want it. Default is True.)pbdoc")
       .def_readwrite("enable_profiling", &SessionOptions::enable_profiling,
-                     R"pbdoc(Enable profiling for this session.)pbdoc")
-      .def_readwrite("profile_file_prefix", &SessionOptions::profile_file_prefix,
-                     R"pbdoc(The prefix of the profile file. The current time will be appended to the file name.)pbdoc")
+                     R"pbdoc(Enable profiling for this session. Default is false.)pbdoc")
+      .def_readwrite("enable_sequential_execution", &SessionOptions::enable_sequential_execution,
+                     R"pbdoc(Enables sequential execution, disables parallel execution. Default is true.)pbdoc")
+      .def_readwrite("max_num_graph_transformation_steps", &SessionOptions::max_num_graph_transformation_steps,
+                     R"pbdoc(Runs optimization steps on the execution graph. Default is 5.)pbdoc")
       .def_readwrite("session_logid", &SessionOptions::session_logid,
                      R"pbdoc(Logger id to use for session output.)pbdoc")
       .def_readwrite("session_log_verbosity_level", &SessionOptions::session_log_verbosity_level,
-                     R"pbdoc(Applies to session load, initialization, etc.)pbdoc");
+                     R"pbdoc(Applies to session load, initialization, etc. Default is 0.)pbdoc")
+      .def_readwrite("session_thread_pool_size", &SessionOptions::session_thread_pool_size,
+                     R"pbdoc(How many threads in the session thread pool. Default is 0 to let onnxruntime choose.
+This parameter is unused unless *enable_sequential_execution* is false.)pbdoc");
 
   py::class_<RunOptions>(m, "RunOptions", R"pbdoc(Configuration information for a single Run.)pbdoc")
       .def(py::init())
       .def_readwrite("run_log_verbosity_level", &RunOptions::run_log_verbosity_level,
                      "Applies to a particular Run() invocation.")
       .def_readwrite("run_tag", &RunOptions::run_tag,
-                     "To identify logs generated by a particular Run() invocation.");
+                     "To identify logs generated by a particular Run() invocation.")
+      .def_readwrite("terminate", &RunOptions::terminate,
+                     R"pbdoc(Set to True to terminate any currently executing calls that are using this
+RunOptions instance. The individual calls will exit gracefully and return an error status.)pbdoc");
 
   py::class_<ModelMetadata>(m, "ModelMetadata", R"pbdoc(Pre-defined and custom metadata about the model.
 It is usually used to identify the model used to run the prediction and