| 175 | } |
| 176 | |
| 177 | def get_data(self): |
| 178 | data = Dataset() |
| 179 | with open(self.data_fn, "r") as f: |
| 180 | data_object = json.load(f) |
| 181 | for item in data_object: |
| 182 | answer = item.pop("answer") |
| 183 | gold_answer = set() |
| 184 | for a in answer: |
| 185 | gold_answer.add(a["answer_argument"]) |
| 186 | data.append(DataPiece(item, gold_answer)) # input and target |
| 187 | return data |
| 188 | |
| 189 | def predict_single(self, session, data_item): # return OUTPUT object, need to be json serializable |
| 190 | # todo: return a dictionary including the prediction and metrics per data item |