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Commit b546836e authored by Nikita Titov's avatar Nikita Titov Committed by Tsukasa OMOTO
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[python] simplified code with np.zeros (#1551)

parent 225eb5ed
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Showing with 2 additions and 3 deletions
python-package/lightgbm/basic.py
View file @ b546836e
...@@ -1961,7 +1961,7 @@ class Booster(object): ...@@ -1961,7 +1961,7 @@ class Booster(object):
self.__get_eval_info() self.__get_eval_info()
ret = [] ret = []
if self.__num_inner_eval > 0: if self.__num_inner_eval > 0:
result = np.array([0.0 for _ in range_(self.__num_inner_eval)], dtype=np.float64) result = np.zeros(self.__num_inner_eval, dtype=np.float64)
tmp_out_len = ctypes.c_int(0) tmp_out_len = ctypes.c_int(0)
_safe_call(_LIB.LGBM_BoosterGetEval( _safe_call(_LIB.LGBM_BoosterGetEval(
self.handle, self.handle,
...@@ -1997,8 +1997,7 @@ class Booster(object): ...@@ -1997,8 +1997,7 @@ class Booster(object):
n_preds = self.train_set.num_data() * self.__num_class n_preds = self.train_set.num_data() * self.__num_class
else: else:
n_preds = self.valid_sets[data_idx - 1].num_data() * self.__num_class n_preds = self.valid_sets[data_idx - 1].num_data() * self.__num_class
self.__inner_predict_buffer[data_idx] = \ self.__inner_predict_buffer[data_idx] = np.zeros(n_preds, dtype=np.float64)
np.array([0.0 for _ in range_(n_preds)], dtype=np.float64, copy=False)
# avoid to predict many time in one iteration # avoid to predict many time in one iteration
if not self.__is_predicted_cur_iter[data_idx]: if not self.__is_predicted_cur_iter[data_idx]:
tmp_out_len = ctypes.c_int64(0) tmp_out_len = ctypes.c_int64(0)
......
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