Add XGBModel & RPCRunnerWarpper (apache#15)

* Add XGBModel & RPCRunnerWarpper

* Revert "Add Parallel Granularity Mutation"

python/tvm/ansor/__init__.py

@@ -29,6 +29,7 @@
 from .compute_dag import ComputeDAG
 from .task import SearchTask, MetaTileRewritePolicy, TuneOption
 from .task import auto_schedule
-from .measure import MeasureInput, LocalBuilder, LocalRunner, RPCRunner
+from .measure import MeasureInput, LocalBuilder, LocalRunner, RPCRunner, RPCRunnerWarpper
 from .cost_model import RandomModel
+from .cost_model.xgb_model import XGBModel
 from .serialization import LogToFile, LogReader, best_measure_pair_in_file

python/tvm/ansor/cost_model/cost_model.py

@@ -42,3 +42,32 @@ def random_number(n, return_ptr):
     return_ptr = ctypes.cast(return_ptr, ctypes.POINTER(ctypes.c_float))
     array_wrapper = np.ctypeslib.as_array(return_ptr, shape=(n,))
     array_wrapper[:] = np.random.uniform(0, 1, (n,))
+
+@tvm._ffi.register_object("ansor.PythonBasedModel")
+class PythonBasedModel(CostModel):
+    def __init__(self):
+        def update_func(inputs, results):
+            self.update(inputs, results)
+
+        def predict_func(task, states, return_ptr):
+            return_ptr = ctypes.cast(return_ptr, ctypes.POINTER(ctypes.c_float))
+            array_wrapper = np.ctypeslib.as_array(return_ptr, shape=(len(states),))
+            array_wrapper[:] = self.predict(task, states)
+
+        def predict_stage_func(task, states, return_ptr):
+            ret = self.predict_stages(task, states)
+            return_ptr = ctypes.cast(return_ptr, ctypes.POINTER(ctypes.c_float))
+            array_wrapper = np.ctypeslib.as_array(return_ptr, shape=ret.shape)
+            array_wrapper[:] = ret
+
+        self.__init_handle_by_constructor__(_ffi_api.PythonBasedModel, update_func,
+                                            predict_func, predict_stage_func)
+
+    def update(self, inputs, results):
+        raise NotImplementedError
+
+    def predict(self, task, states):
+        raise NotImplementedError
+
+    def predict_stages(self, task, states):
+        raise NotImplementedError