def __init__(self, model_dir, model_name=None, num_classes=None):
self.time_dir = model_dir
self.num_classes = num_classes
self.__model_dir = mkdir_time(PATH_MODEL_DIR, model_dir)
self.__update_model_dir = mkdir_time(PATH_MODEL_DIR, NEW_TIME_DIR)
self.__monitor_bigger_best = self.params['monitor_mode'] == 'max'
# initialize some variables that would be used by func "model.fit";
# the child class can change this params when customizing the build func
self.__class_weight = None
self.__initial_epoch = 0 if 'initial_epoch' not in self.params else self.params[
'initial_epoch']
# get the tensorboard dir path
self.__get_tf_board_path(model_dir)
# get the model path
self.__get_model_path(model_name)
self.init_gpu_config()
# build model
self.build()
# initialize some callback funcs
self.__init_callback()
def __init__(self, model_dir, model_name=None):
# get the time from model name and create a directory for this time
dir_path = mkdir_time(PATH_MODEL_DIR, model_dir)
self.__model_path = os.path.join(
dir_path, model_name + '.model' if model_name else 'lgb.model')
if model_name and os.path.isfile(self.__model_path):
self.__has_train = True
self.__model = lgb.Booster(model_file=self.__model_path)
else:
self.__has_train = False
self.__model = lgb.LGBMClassifier(**self.params)
def __get_tf_board_path(self, model_dir):
""" Get the tensorboard dir path and run it on cmd """
self.tf_board_dir = mkdir_time(PATH_BOARD_DIR, model_dir)