def load_models(self, skip_local=False):
model_name = list(self.get_models_to_save().keys())[0]
if not skip_local:
load_path = self.local_models_path / model_name
else:
load_path = self.models_path / model_name
self.agent.value_model = GPQLearning.load(load_path)
def load_models(self, skip_local=False):
model_name = list(self.get_models_to_save().keys())[0]
if not skip_local:
load_path = self.local_models_path / model_name
else:
load_path = self.models_path / model_name
self.agent.value_model = GPQLearning.load(load_path,
self.env.staetaction_space,
self.x_seed, self.y_seed)