Fixed generate examples

dataset_infos.json

@@ -0,0 +1 @@
+{"robust": {"description": "", "citation": "", "homepage": "", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "du_reader", "config_name": "robust", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 12509537, "num_examples": 14520, "dataset_name": "du_reader"}, "validation": {"name": "validation", "num_bytes": 1228154, "num_examples": 1417, "dataset_name": "du_reader"}, "test": {"name": "test", "num_bytes": 46912731, "num_examples": 50000, "dataset_name": "du_reader"}}, "download_checksums": {"https://dataset-bj.cdn.bcebos.com/qianyan/dureader_robust-data.tar.gz": {"num_bytes": 20518631, "checksum": "99bed9ced8995df1c89b9789f890c27a13b4650a56b4d973907cc28da8bd9f0f"}}, "download_size": 20518631, "post_processing_size": null, "dataset_size": 60650422, "size_in_bytes": 81169053}, "checklist": {"description": "", "citation": "", "homepage": "", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "is_impossible": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}, "type": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "du_reader", "config_name": "checklist", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2459480, "num_examples": 2999, "dataset_name": "du_reader"}, "validation": {"name": "validation", "num_bytes": 879626, "num_examples": 1130, "dataset_name": "du_reader"}, "test": {"name": "test", "num_bytes": 32421655, "num_examples": 49992, "dataset_name": "du_reader"}}, "download_checksums": {"https://dataset-bj.cdn.bcebos.com/qianyan/dureader_checklist-data.tar.gz": {"num_bytes": 18319191, "checksum": "223c370696b9f1e8c89d84b7935c8da88128004788ad80fb9c3830130461e6f3"}}, "download_size": 18319191, "post_processing_size": null, "dataset_size": 35760761, "size_in_bytes": 54079952}}

dureader.py

@@ -56,13 +56,14 @@ class DuReader(datasets.GeneratorBasedBuilder):
                 "title": datasets.Value("string"),
                 "context": datasets.Value("string"),
                 "question": datasets.Value("string"),
-                "is_impossible": datasets.Value("bool"),
+                "is_impossible": datasets.Value("string"),
                 "answers": datasets.Sequence(
                     {
                         "text": datasets.Value("string"),
                         "answer_start": datasets.Value("int32"),
                     }
                 ),
+                "type": datasets.Value("string"),
             }
             return datasets.DatasetInfo(
                 description="",
@@ -123,16 +124,18 @@ class DuReader(datasets.GeneratorBasedBuilder):
     def _generate_examples(self, data_file, split):
         if self.config.name == "robust":
             if split == "train" or split == "dev":
+                print("Processing split: ", split)
                 return self._generate_robust_examples(data_file)
+            print("Processing split: ", split)
             return self._generate_robust_test_examples(data_file)
 
         if self.config.name == "checklist":
             if split == "train" or split == "dev":
+                print("Processing split: ", split)
                 return self._generate_checklist_examples(data_file)
+            print("Processing split: ", split)
             return self._generate_checklist_test_examples(data_file)
 
-        return None, None
-
     def _generate_robust_examples(self, data_file):
         with open(data_file, mode="rt", encoding="utf-8") as fin:
             data = json.load(fin)["data"]
@@ -160,49 +163,71 @@ class DuReader(datasets.GeneratorBasedBuilder):
             for p in d["paragraphs"]:
                 context = p["context"]
                 for qa in p["qas"]:
+                    qid = qa["id"]
                     example = {
-                        "id": qa["id"],
+                        "id": qid,
                         "context": context,
                         "question": qa["question"],
+                        "answers": {
+                            "text": [],
+                            "answer_start": [],
+                        },
                     }
                     yield example["id"], example
 
     def _generate_checklist_examples(self, data_file):
         with open(data_file, mode="rt", encoding="utf-8") as fin:
             data = json.load(fin)["data"]
+        exist_ids = set()
         for d in data:
             for p in d["paragraphs"]:
-                title = p["title"]
-                context = p["context"]
+                title = p["title"].strip()
+                context = p["context"].strip()
                 for qa in p["qas"]:
+                    qid = qa["id"]
+                    # skip dumplicate keys
+                    if qid in exist_ids:
+                        continue
+                    exist_ids.add(qid)
                     starts = [x["answer_start"] for x in qa["answers"]]
-                    answers = [x["text"] for x in qa["answers"]]
+                    answers = [x["text"].strip() for x in qa["answers"]]
                     example = {
-                        "id": qa["id"],
+                        "id": qid,
                         "title": title,
                         "context": context,
-                        "question": qa["question"],
+                        "question": qa["question"].strip(),
                         "is_impossible": qa["is_impossible"],
                         "answers": {
                             "text": answers,
                             "answer_start": starts,
                         },
-                        "type": qa["type"],
+                        "type": qa["type"].strip(),
                     }
                     yield example["id"], example
 
     def _generate_checklist_test_examples(self, data_file):
         with open(data_file, mode="rt", encoding="utf-8") as fin:
             data = json.load(fin)["data"]
+        exist_ids = set()
         for d in data:
             for p in d["paragraphs"]:
                 title = p["title"]
                 context = p["context"]
                 for qa in p["qas"]:
+                    qid = qa["id"]
+                    if qid in exist_ids:
+                        continue
+                    exist_ids.add(qid)
                     example = {
-                        "id": qa["id"],
+                        "id": qid,
                         "title": title,
                         "context": context,
                         "question": qa["question"],
+                        "is_impossible": None,
+                        "answers": {
+                            "text": [],
+                            "answer_start": [],
+                        },
+                        "type": None,
                     }
                     yield example["id"], example