def _make_cloud_mlengine_request(examples): """Builds and sends requests to Cloud ML Engine.""" api = discovery.build("ml", "v1", credentials=credentials) parent = "projects/%s/models/%s/versions/%s" % (cloud.default_project(), model_name, version) input_data = { "instances": [{ "input": { "b64": base64.b64encode(ex.SerializeToString()) } } for ex in examples] } prediction = api.projects().predict(body=input_data, name=parent).execute() return prediction["predictions"]
def _make_cloud_mlengine_request(examples): """Builds and sends requests to Cloud ML Engine.""" api = discovery.build("ml", "v1", credentials=credentials) parent = "projects/%s/models/%s/versions/%s" % (cloud.default_project(), model_name, version) input_data = { "instances": [{ # pylint: disable=g-complex-comprehension "input": { "b64": base64.b64encode(ex.SerializeToString()) } } for ex in examples] } response = api.projects().predict(body=input_data, name=parent).execute() predictions = response["predictions"] for prediction in predictions: prediction["outputs"] = np.array([prediction["outputs"]]) prediction["scores"] = np.array(prediction["scores"]) return predictions