Continue training with init_model raise LightGBMError: Number of class for initial score error

[iFe1er]

Continue training with init_model raise LightGBMError: Number of class for initial score error

example code:

#old_model is a trained model loaded from disk.   
old_model = lgb.Booster(model_file="path_of_trained_model")     

continue_model = lgb.train(params, lgb_train, num_round, valid_sets=[lgb_train,lgb_test],verbose_eval=1,
                    fobj = mymse2,feval = self_metric,init_model = old_model)

and it give STDERR:

`~/anaconda3/envs/trader/lib/python3.7/site-packages/lightgbmmt/engine.py in train(params, train_set, num_boost_round, valid_sets, valid_names, fobj, feval, init_model, feature_name, categorical_feature, early_stopping_rounds, evals_result, verbose_eval, learning_rates, keep_training_booster, callbacks)
226 # construct booster
227 try:
--> 228 booster = Booster(params=params, train_set=train_set)
229 if is_valid_contain_train:
230 booster.set_train_data_name(train_data_name)

~/anaconda3/envs/trader/lib/python3.7/site-packages/lightgbmmt/basic.py in init(self, params, train_set, model_file, model_str, silent)
1732 train_set.construct().handle,
1733 c_str(params_str),
-> 1734 ctypes.byref(self.handle)))
1735 # save reference to data
1736 self.train_set = train_set

~/anaconda3/envs/trader/lib/python3.7/site-packages/lightgbmmt/basic.py in _safe_call(ret)
43 """
44 if ret != 0:
---> 45 raise LightGBMError(decode_string(_LIB.LGBM_GetLastError()))
46
47

LightGBMError: Number of class for initial score error`

---

BUG2: If I load model by filename during training (init_mode="path/of/model"), it raise another Error:

~/anaconda3/envs/trader/lib/python3.7/site-packages/lightgbmmt/engine.py in train(params, train_set, num_boost_round, valid_sets, valid_names, fobj, feval, init_model, feature_name, categorical_feature, early_stopping_rounds, evals_result, verbose_eval, learning_rates, keep_training_booster, callbacks)
226 # construct booster
227 try:
--> 228 booster = Booster(params=params, train_set=train_set)
229 if is_valid_contain_train:
230 booster.set_train_data_name(train_data_name)

~/anaconda3/envs/trader/lib/python3.7/site-packages/lightgbmmt/basic.py in init(self, params, train_set, model_file, model_str, silent)
1730 self.handle = ctypes.c_void_p()
1731 _safe_call(_LIB.LGBM_BoosterCreate(
-> 1732 train_set.construct().handle,
1733 c_str(params_str),
1734 ctypes.byref(self.handle)))

~/anaconda3/envs/trader/lib/python3.7/site-packages/lightgbmmt/basic.py in construct(self)
1089 init_score=self.init_score, predictor=self._predictor,
1090 silent=self.silent, feature_name=self.feature_name,
-> 1091 categorical_feature=self.categorical_feature, params=self.params)
1092 if self.free_raw_data:
1093 self.data = None

~/anaconda3/envs/trader/lib/python3.7/site-packages/lightgbmmt/basic.py in _lazy_init(self, data, label, reference, weight, group, init_score, predictor, silent, feature_name, categorical_feature, params)
913 if self._predictor is None and init_score is not None:
914 warnings.warn("The init_score will be overridden by the prediction of init_model.")
--> 915 self._set_init_score_by_predictor(predictor, data)
916 elif init_score is not None:
917 self.set_init_score(init_score)

~/anaconda3/envs/trader/lib/python3.7/site-packages/lightgbmmt/basic.py in _set_init_score_by_predictor(self, predictor, data, used_indices)
819 new_init_score[j * num_data + i] = init_score[i * predictor.num_class + j]
820 init_score = new_init_score
--> 821 self.set_init_score(init_score)
822
823 def _lazy_init(self, data, label=None, reference=None,

~/anaconda3/envs/trader/lib/python3.7/site-packages/lightgbmmt/basic.py in set_init_score(self, init_score)
1433 if self.handle is not None and init_score is not None:
1434 init_score = list_to_1d_numpy(init_score, np.float64, name='init_score')
-> 1435 self.set_field('init_score', init_score)
1436 self.init_score = self.get_field('init_score') # original values can be modified at cpp side
1437 return self

~/anaconda3/envs/trader/lib/python3.7/site-packages/lightgbmmt/basic.py in set_field(self, field_name, data)
1233 ptr_data,
1234 ctypes.c_int(len(data)),
-> 1235 ctypes.c_int(type_data)))
1236 return self
1237

~/anaconda3/envs/trader/lib/python3.7/site-packages/lightgbmmt/basic.py in _safe_call(ret)
43 """
44 if ret != 0:
---> 45 raise LightGBMError(decode_string(_LIB.LGBM_GetLastError()))
46
47

LightGBMError: Initial score size doesn't match data size