Rename PLOD-CW_old.py to PLOD-CW.py

PLOD-CW_old.py → PLOD-CW.py

@@ -81,83 +81,4 @@ class PLODfilteredConfig(datasets.GeneratorBasedBuilder):
             homepage="https://github.com/surrey-nlp/PLOD-AbbreviationDetection",
             citation=_CITATION,
         )
-    _URL = "https://huggingface.co/datasets/surrey-nlp/PLOD-CW/resolve/main/data/"
-    _URLS = {
-        "train": _URL + "PLOS-train70-filtered-pos_bio.json",
-        "dev": _URL + "PLOS-val15-filtered-pos_bio.json",
-        "test": _URL + "PLOS-test15-filtered-pos_bio.json"
-    }
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-        urls_to_download = self._URLS
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]})
-        ]
-
-    def _generate_examples(self, filepath):
-        """This function returns the examples in the raw (text) form."""
-        logger.info("generating examples from = %s", filepath)
-        with open(filepath) as f:
-            plod = json.load(f)
-            for object in plod:
-                id_ = int(object['id'])
-                yield id_, {
-                    "id": str(id_),
-                    "tokens": object['tokens'],
-                    "pos_tags": object['pos_tags'],
-                    "ner_tags": object['ner_tags'],
-                }
-    _URL = "https://huggingface.co/datasets/surrey-nlp/PLOD-CW/resolve/main/data/"
-    _URLS = {
-        "train": _URL + "train.conll",
-        "dev": _URL + "dev.conll",
-        "test": _URL + "test.conll"
-    }
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
-        urls_to_download = self._URLS
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]})
-        ]
-
-    def _generate_examples(self, filepath):
-        logger.info("⏳ Generating examples from = %s", filepath)
-        with open(filepath, encoding="utf-8") as f:
-            guid = 0
-            tokens = []
-            pos_tags = []
-            ner_tags = []
-            for line in f:
-                if line.startswith("-DOCSTART-") or line == "" or line == "\n":
-                    if tokens:
-                        yield guid, {
-                            "id": str(guid),
-                            "tokens": tokens,
-                            "pos_tags": pos_tags,
-                            "ner_tags": ner_tags,
-                        }
-                        guid += 1
-                        tokens = []
-                        pos_tags = []
-                        ner_tags = []
-                else:
-                    splits = line.split(" ")
-                    tokens.append(splits[0])
-                    pos_tags.append(splits[1])
-                    ner_tags.append(splits[2].rstrip())
-            # last example
-            if tokens:
-                yield guid, {
-                    "id": str(guid),
-                    "tokens": tokens,
-                    "pos_tags": pos_tags,
-                    "ner_tags": ner_tags,
-                }
+