Upload c_corpus.py

c_corpus.py

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+import datasets
+
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_CITATION = """ """
+
+_DESCRIPTION = """ """
+
+_HOMEPAGE = ""
+
+_URL = "https://raw.githubusercontent.com/rosi-pc/c_corpus/main/c_corpus/"
+_TRAINING_FILE = "train.txt"
+_DEV_FILE = "valid.txt"
+_TEST_FILE = "test.txt"
+
+
+class CCorpus(datasets.GeneratorBasedBuilder):
+    """c-corpus dataset"""
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="c_corpus", version=VERSION, description="c_corpus dataset"),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                   "O",
+                                   "B-DATA",
+                                   "I-DATA",
+                                   "B-EVENTO",
+                                   "I-EVENTO",
+                                   "B-FUNDAMENTO",
+                                   "I-FUNDAMENTO",
+                                   "B-LOCAL",
+                                   "I-LOCAL",
+                                   "B-ORGANIZACAO",
+                                   "I-ORGANIZACAO",
+                                   "B-PESSOA",
+                                   "I-PESSOA",
+                                   "B-PRODUTODELEI",
+                                   "I-PRODUTODELEI",
+                            ]
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage=" ",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_URL}{_TRAINING_FILE}",
+            "dev": f"{_URL}{_DEV_FILE}",
+            "test": f"{_URL}{_TEST_FILE}",
+        }
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": downloaded_files["train"], "split": "train"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": downloaded_files["dev"], "split": "validation"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": downloaded_files["test"], "split": "test"},
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        """Yields examples."""
+
+        logger.info("⏳ Generating examples from = %s", filepath)
+
+        with open(filepath, encoding="utf-8") as f:
+
+            guid = 0
+            tokens = []
+            ner_tags = []
+
+            for line in f:
+                if line == "" or line == "\n":
+                    if tokens:
+                        yield guid, {
+                            "id": str(guid),
+                            "tokens": tokens,
+                            "ner_tags": ner_tags,
+                        }
+                        guid += 1
+                        tokens = []
+                        ner_tags = []
+                else:
+                    splits = line.split(" ")
+                    tokens.append(splits[0])
+                    ner_tags.append(splits[1].rstrip())
+
+            # last example
+            yield guid, {
+                "id": str(guid),
+                "tokens": tokens,
+                "ner_tags": ner_tags,
+            }