some naming fix

python-package/lightgbm/basic.py

@@ -898,9 +898,10 @@ class Booster(object):
         if 'metric' in params:
             self.__need_reload_eval_info = True
         params_str = param_dict_to_str(params)
-        _safe_call(_LIB.LGBM_BoosterResetParameter(
-            self.handle,
-            c_str(params_str)))
+        if params_str:
+            _safe_call(_LIB.LGBM_BoosterResetParameter(
+                self.handle,
+                c_str(params_str)))
 
     def update(self, train_set=None, fobj=None):
         """

python-package/lightgbm/engine.py

@@ -166,7 +166,7 @@ def train(params, train_data, num_boost_round=100,
     """start training"""
     for i in range(num_boost_round):
         for cb in callbacks_before_iter:
-            cb(CallbackEnv(model=booster,
+            cb(callback.CallbackEnv(model=booster,
                            cvfolds=None,
                            iteration=i,
                            begin_iteration=0,
@@ -183,16 +183,16 @@ def train(params, train_data, num_boost_round=100,
             evaluation_result_list.extend(booster.eval_valid(feval))
         try:
             for cb in callbacks_after_iter:
-                cb(CallbackEnv(model=booster,
+                cb(callback.CallbackEnv(model=booster,
                                cvfolds=None,
                                iteration=i,
                                begin_iteration=0,
                                end_iteration=num_boost_round,
                                evaluation_result_list=evaluation_result_list))
-        except EarlyStopException:
+        except callback.EarlyStopException:
             break
     if booster.attr('best_iteration') is not None:
         booster.best_iteration = int(booster.attr('best_iteration'))
     else:
         booster.best_iteration = num_boost_round - 1
-    return num_boost_round
+    return num_boost_round
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