Upload pv_dataset.py

pv_dataset.py

@@ -0,0 +1,112 @@
+import datasets
+import json
+
+logger = datasets.logging.get_logger(__name__)
+
+
+_HOMEPAGE = "https://www.google.com"
+_TRAINING_FILE = "pv_train.tsv"
+_DEV_FILE = "pv_val.tsv"
+_TEST_FILE = "pv_test.tsv"
+
+
+class PVDatasetConfig(datasets.BuilderConfig):
+    """BuilderConfig for Bc2gmCorpus"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig for Bc2gmCorpus.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(PVDatasetConfig, self).__init__(**kwargs)
+
+class PVDataset(datasets.GeneratorBasedBuilder):
+    """Bc2gmCorpus dataset."""
+
+    BUILDER_CONFIGS = [
+        PVDatasetConfig(name="PVDatasetCorpus", version=datasets.Version("1.0.0"), description="PVDataset"),
+    ]
+
+    def _info(self):
+
+        custom_names = ['O','B-GENE','I-GENE','B-CHEMICAL','I-CHEMICAL','B-DISEASE','I-DISEASE','B-SPECIES', 'I-SPECIES']
+
+        return datasets.DatasetInfo(
+            description='abhi',
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=custom_names
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation='cite me',
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        urls_to_download = {
+            "train": f"{_TRAINING_FILE}",
+            "dev": f"{_DEV_FILE}",
+            "test": f"{_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"]}),
+            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):
+        shift = 0
+        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:
+                    # tokens are tab separated
+                    splits = line.split("\t")
+                    tokens.append(splits[0])
+                    if(splits[1].rstrip()=="B"):
+                        ner_tags.append("B-SPECIES")
+                    elif(splits[1].rstrip()=="I"):
+                        ner_tags.append("I-SPECIES")             
+                    elif(splits[1].rstrip()=="B-Chemical"):
+                        ner_tags.append("B-CHEMICAL")
+                    elif(splits[1].rstrip()=="I-Chemical"):
+                        ner_tags.append("I-CHEMICAL")
+                    elif(splits[1].rstrip()=="B-Disease"):
+                        ner_tags.append("B-DISEASE")
+                    elif(splits[1].rstrip()=="I-Disease"):
+                        ner_tags.append("I-DISEASE")
+                    else:
+                        ner_tags.append(splits[1].rstrip())                
+            # last example
+            yield guid, {
+                "id": str(guid),
+                "tokens": tokens,
+                "ner_tags": ner_tags,
+            }
+
+
+
+