def on_get()

in tensorflow/inference/docker/build_artifacts/sagemaker/python_service.py [0:0]

• 37 lines of code
• 6 McCabe index (conditional complexity)

    def on_get(self, req, res, model_name=None):  # pylint: disable=W0613
        with lock():
            self._sync_local_mme_instance_status()
            if model_name is None:
                models_info = {}
                uri = "http://localhost:{}/v1/models/{}"
                for model, tfs_instance_status in self._mme_tfs_instances_status.items():
                    try:
                        info = json.loads(
                            requests.get(
                                uri.format(tfs_instance_status[0].rest_port, model)
                            ).content
                        )
                        models_info[model] = info
                    except ValueError as e:
                        log.exception("exception handling request: {}".format(e))
                        res.status = falcon.HTTP_500
                        res.body = json.dumps({"error": str(e)}).encode("utf-8")
                res.status = falcon.HTTP_200
                res.body = json.dumps(models_info)
            else:
                if model_name not in self._mme_tfs_instances_status:
                    res.status = falcon.HTTP_404
                    res.body = json.dumps(
                        {"error": "Model {} is loaded yet.".format(model_name)}
                    ).encode("utf-8")
                else:
                    port = self._mme_tfs_instances_status[model_name].rest_port
                    uri = "http://localhost:{}/v1/models/{}".format(port, model_name)
                    try:
                        info = requests.get(uri)
                        res.status = falcon.HTTP_200
                        res.body = json.dumps({"model": info}).encode("utf-8")
                    except ValueError as e:
                        log.exception("exception handling GET models request.")
                        res.status = falcon.HTTP_500
                        res.body = json.dumps({"error": str(e)}).encode("utf-8")