Update nemo_corpus.py

nemo_corpus.py

@@ -118,7 +118,7 @@ def tokens_with_tags_to_spans(tags: Iterable[str], tokens: Iterable[str]) -> Lis
 class NemoCorpusConfig(datasets.BuilderConfig):
     """BuilderConfig for NemoCorpus"""
 
-    def __init__(self):
+    def __init__(self, name):
         """BuilderConfig for flat Nemo corpus.
         Args:
           **kwargs: keyword arguments forwarded to super.
@@ -150,25 +150,65 @@ class NemoCorpusConfig(datasets.BuilderConfig):
                                'B-WOA', 'E-WOA', 'I-WOA', 'S-WOA']
                     )
                 ),
-                "spans": datasets.Sequence({
-                    "span": datasets.Value("string"),
-                    "start": datasets.Value("int32"),
-                    "end": datasets.Value("int32"),
-                    "entity": datasets.Value("string"),
-                    "start_char": datasets.Value("int32"),
-                    "end_char": datasets.Value("int32"),
-                })
+                # "spans": datasets.Sequence({
+                #     "span": datasets.Value("string"),
+                #     "start": datasets.Value("int32"),
+                #     "end": datasets.Value("int32"),
+                #     "entity": datasets.Value("string"),
+                #     "start_char": datasets.Value("int32"),
+                #     "end_char": datasets.Value("int32"),
+                # })
             }
         )
 
     def get_datafiles(self, folder):
         data_prefix = "morph" if self.dataset_type == "morph" else "token-single"
-        return  {
-            "train": dl_manager.download(folder / f"{data_prefix}_gold_train.bmes"),
-            "validation": dl_manager.download(folder / f"{data_prefix}_gold_dev.bmes"),
-            "test": dl_manager.download(folder / f"{data_prefix}_gold_test.bmes"),
+        return {
+            "train": folder / f"{data_prefix}_gold_train.bmes",
+            "validation": folder / f"{data_prefix}_gold_dev.bmes",
+            "test": folder / f"{data_prefix}_gold_test.bmes",
         }
 
+    def _generate_examples(self, filepath, sep=" "):
+        logger.info("⏳ Generating examples from = %s", filepath)
+        with open(filepath, encoding="utf-8") as f:
+            guid = 0
+            tokens = []
+            ner_tags = []
+            raw_tags = []
+            for line in f:
+                line = line.strip()
+                if line.startswith("-DOCSTART-") or line == "" or line == "\n":
+                    if tokens:
+                        yield guid, {
+                            "id": str(guid),
+                            "sentence": " ".join(tokens),
+                            "tokens": tokens,
+                            "raw_tags": raw_tags,
+                            "ner_tags": ner_tags,
+                            # "spans": tokens_with_tags_to_spans(ner_tags, tokens)
+                        }
+                        guid += 1
+                        tokens = []
+                        ner_tags = []
+                        raw_tags = []
+                else:
+                    splits = line.split(sep)
+                    # token-single contains errors in the data, so need to split it a bit differently rather than just space
+                    tag = splits[-1].rstrip()
+                    token = line[:-len(tag)].strip()
+                    tokens.append(token)
+                    raw_tags.append(tag)
+                    ner_tags.append(tag)
+            # last example
+            yield guid, {
+                "id": str(guid),
+                "sentence": " ".join(tokens),
+                "tokens": tokens,
+                "raw_tags": raw_tags,
+                "ner_tags": ner_tags,
+                # "spans": tokens_with_tags_to_spans(ner_tags, tokens)
+            }
 
 
 class NemoCorpusNestedConfig(datasets.BuilderConfig):
@@ -215,95 +255,13 @@ class NemoCorpusNestedConfig(datasets.BuilderConfig):
     def get_datafiles(self, folder):
         data_prefix = "morph" if self.dataset_type == "morph" else "token-single"
         folder = folder / "nested"
-        return  {
-            "train": dl_manager.download(folder / f"{data_prefix}_gold_train.bmes"),
-            "validation": dl_manager.download(folder / f"{data_prefix}_gold_dev.bmes"),
-            "test": dl_manager.download(folder / f"{data_prefix}_gold_test.bmes"),
+        return {
+            "train": folder / f"{data_prefix}_gold_train.bmes",
+            "validation": folder / f"{data_prefix}_gold_dev.bmes",
+            "test": folder / f"{data_prefix}_gold_test.bmes"
         }
 
-
-
-class NemoCorpus(datasets.GeneratorBasedBuilder):
-    """NemoCorpus dataset."""
-
-    DEFAULT_CONFIG_NAME = "flat_token"
-
-    BUILDER_CONFIGS = [
-        NemoCorpusConfig("flat_token"),
-        NemoCorpusNestedConfig("nested_token"),
-        NemoCorpusConfig("flat_morph"),
-        NemoCorpusNestedConfig("nested_morph")
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=self.config.features,
-            supervised_keys=None,
-            homepage="https://www.cs.bgu.ac.il/~elhadad/nlpproj/naama/",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        dirname = tempfile.TemporaryDirectory().name
-        os.makedirs(dirname, exist_ok=True)
-        os.system(f"cd {dirname} && git clone --depth=1 {URL}")
-        folder = Path(dirname) / "NEMO-Corpus" / "data" / "spmrl" / "gold"
-        data_files = self.config.get_datafiles(folder)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN,
-                                    gen_kwargs={"filepath": data_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION,
-                                    gen_kwargs={"filepath": data_files["validation"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST,
-                                    gen_kwargs={"filepath": data_files["test"]}),
-        ]
-
     def _generate_examples(self, filepath, sep=" "):
-        if self.config.name == "nested":
-            yield from self._generate_examples_nested(filepath, sep)
-        else:
-            yield from self._generate_examples_flat(filepath, sep)
-
-    def _generate_examples_flat(self, filepath, sep=" "):
-        logger.info("⏳ Generating examples from = %s", filepath)
-        with open(filepath, encoding="utf-8") as f:
-            guid = 0
-            tokens = []
-            ner_tags = []
-            raw_tags = []
-            for line in f:
-                if line.startswith("-DOCSTART-") or line == "" or line == "\n":
-                    if tokens:
-                        yield guid, {
-                            "id": str(guid),
-                            "sentence": " ".join(tokens),
-                            "tokens": tokens,
-                            "raw_tags": raw_tags,
-                            "ner_tags": ner_tags,
-                            "spans": tokens_with_tags_to_spans(ner_tags, tokens)
-                        }
-                        guid += 1
-                        tokens = []
-                        ner_tags = []
-                        raw_tags = []
-                else:
-                    splits = line.split(sep)
-                    tokens.append(splits[0])
-                    raw_tags.append(splits[1].rstrip())
-                    ner_tags.append(splits[1].rstrip())
-            # last example
-            yield guid, {
-                "id": str(guid),
-                "sentence": " ".join(tokens),
-                "tokens": tokens,
-                "raw_tags": raw_tags,
-                "ner_tags": ner_tags,
-                "spans": tokens_with_tags_to_spans(ner_tags, tokens)
-            }
-
-    def _generate_examples_nested(self, filepath, sep=" "):
         logger.info("⏳ Generating examples from = %s", filepath)
         with open(filepath, encoding="utf-8") as f:
             guid = 0
@@ -345,3 +303,50 @@ class NemoCorpus(datasets.GeneratorBasedBuilder):
                 "ner_tags_3": ner_tags_3,
                 "ner_tags_4": ner_tags_4,
             }
+
+
+class NemoCorpus(datasets.GeneratorBasedBuilder):
+    """NemoCorpus dataset."""
+
+    DEFAULT_CONFIG_NAME = "flat_token"
+
+    BUILDER_CONFIGS = [
+        NemoCorpusConfig("flat_token"),
+        NemoCorpusNestedConfig("nested_token"),
+        NemoCorpusConfig("flat_morph"),
+        NemoCorpusNestedConfig("nested_morph")
+    ]
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        dirname = tempfile.TemporaryDirectory().name
+        os.makedirs(dirname, exist_ok=True)
+        os.system(f"cd {dirname} && git clone --depth=1 {URL}")
+        self.repo_folder = Path(dirname) / "NEMO-Corpus" / "data" / "spmrl" / "gold"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=self.config.features,
+            supervised_keys=None,
+            homepage="https://www.cs.bgu.ac.il/~elhadad/nlpproj/naama/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        data_files = self.config.get_datafiles(self.repo_folder)
+        data_files = dl_manager.download_and_extract(data_files)
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN,
+                                    gen_kwargs={"filepath": data_files["train"]}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION,
+                                    gen_kwargs={"filepath": data_files["validation"]}),
+            datasets.SplitGenerator(name=datasets.Split.TEST,
+                                    gen_kwargs={"filepath": data_files["test"]}),
+        ]
+
+    def _generate_examples(self, filepath, sep=" "):
+        yield from self.config._generate_examples(filepath, sep)
+
+