コード例 #1
0
    def predict(self,
                parameter_values_pandas_frame,
                t=None,
                context_values_pandas_frame=None):  # pylint: disable=unused-argument
        # TODO: make this streaming and/or using arrow.
        #
        if context_values_pandas_frame is not None:
            raise NotImplementedError(
                "Context not currently supported on remote optimizers")
        feature_values_dict = parameter_values_pandas_frame.to_dict(
            orient='list')
        prediction_request = OptimizerService_pb2.PredictRequest(
            OptimizerHandle=self.optimizer_handle,
            Features=OptimizerService_pb2.Features(
                FeaturesJsonString=json.dumps(feature_values_dict)))
        prediction_response = self._optimizer_stub.Predict(prediction_request)

        # To be compliant with the OptimizerBase, we need to recover a single Prediction object and return it.
        #
        objective_predictions_pb2 = prediction_response.ObjectivePredictions
        assert len(objective_predictions_pb2) == 1
        only_prediction_pb2 = objective_predictions_pb2[0]
        objective_name = only_prediction_pb2.ObjectiveName
        valid_predictions_df = Prediction.dataframe_from_json(
            only_prediction_pb2.PredictionDataFrameJsonString)
        prediction = Prediction.create_prediction_from_dataframe(
            objective_name=objective_name, dataframe=valid_predictions_df)
        return prediction
コード例 #2
0
    def predict(self, feature_values_pandas_frame, t=None):  # pylint: disable=unused-argument
        # TODO: make this streaming and/or using arrow.
        #
        feature_values_dict = feature_values_pandas_frame.to_dict(
            orient='list')
        prediction_request = OptimizerService_pb2.PredictRequest(
            OptimizerHandle=self.optimizer_handle,
            Features=OptimizerService_pb2.Features(
                FeaturesJsonString=json.dumps(feature_values_dict)))
        prediction_response = self._optimizer_stub.Predict(prediction_request)

        # To be compliant with the OptimizerInterface, we need to recover a single Prediction object and return it.
        #
        objective_predictions_pb2 = prediction_response.ObjectivePredictions
        assert len(objective_predictions_pb2) == 1
        only_prediction_pb2 = objective_predictions_pb2[0]
        objective_name = only_prediction_pb2.ObjectiveName
        valid_predictions_df = Prediction.dataframe_from_json(
            only_prediction_pb2.PredictionDataFrameJsonString)
        prediction = Prediction.create_prediction_from_dataframe(
            objective_name=objective_name, dataframe=valid_predictions_df)
        prediction.add_invalid_rows_at_missing_indices(
            desired_index=feature_values_pandas_frame.index)
        return prediction