def load(self):
logger.info("Loading AutoML models ...")
try:
params = json.load(open(os.path.join(self._results_path, "params.json")))
self._model_paths = params["saved"]
self._ml_task = params["ml_task"]
self._optimize_metric = params["optimize_metric"]
models_map = {}
for model_path in self._model_paths:
if model_path.endswith("ensemble"):
ens = Ensemble.load(model_path, models_map)
models_map[ens.get_name()] = ens
else:
m = ModelFramework.load(model_path)
self._models += [m]
models_map[m.get_name()] = m
best_model_name = None
with open(os.path.join(self._results_path, "best_model.txt"), "r") as fin:
best_model_name = fin.read()
self._best_model = models_map[best_model_name]
data_info_path = os.path.join(self._results_path, "data_info.json")
self._data_info = json.load(open(data_info_path))
except Exception as e:
raise AutoMLException(f"Cannot load AutoML directory. {str(e)}")
def load(self, path):
logger.info("Loading AutoML models ...")
try:
params = json.load(open(os.path.join(path, "params.json")))
self._model_paths = params["saved"]
self._ml_task = params["ml_task"]
self._eval_metric = params["eval_metric"]
stacked_models = params.get("stacked")
models_map = {}
for model_path in self._model_paths:
if model_path.endswith("Ensemble") or model_path.endswith(
"Ensemble_Stacked"
):
ens = Ensemble.load(model_path, models_map)
self._models += [ens]
models_map[ens.get_name()] = ens
else:
m = ModelFramework.load(model_path)
self._models += [m]
models_map[m.get_name()] = m
if stacked_models is not None:
self._stacked_models = []
for stacked_model_name in stacked_models:
self._stacked_models += [models_map[stacked_model_name]]
best_model_name = None
with open(os.path.join(path, "best_model.txt"), "r") as fin:
best_model_name = fin.read()
self._best_model = models_map[best_model_name]
data_info_path = os.path.join(path, "data_info.json")
self._data_info = json.load(open(data_info_path))
self.n_features_in_ = self._data_info["n_features"]
if "n_classes" in self._data_info:
self.n_classes = self._data_info["n_classes"]
self._fit_level = "finished"
except Exception as e:
raise AutoMLException(f"Cannot load AutoML directory. {str(e)}")
