def main(args):
parameters = parse_parameters(json.loads(args.parameters))
model_uri = parameters["model_uri"]
# TODO: Cache downloaded model for MLFlowServer.py
log.info(f"Downloading model from {model_uri}")
model_folder = Storage.download(model_uri)
setup_env(model_folder)
def load(self):
logger.info(f"Downloading model from {self.model_uri}")
model_folder = Storage.download(self.model_uri)
self._model = pyfunc.load_model(model_folder)
self.ready = True
def load(self):
model_file = os.path.join(Storage.download(self.model_uri),
MODEL_FILE_NAME)
self._model = torch.load(model_file)
self.ready = True