Create PEYMA.py

PEYMA.py

@@ -0,0 +1,79 @@
+import json
+import pandas as pd
+import datasets
+import requests
+import os
+
+_CITATION = """\\
+@article{shahshahani2018peyma,
+    title={PEYMA: A Tagged Corpus for Persian Named Entities},
+    author={Mahsa Sadat Shahshahani and Mahdi Mohseni and Azadeh Shakery and Heshaam Faili},
+    year=2018,
+    journal={ArXiv},
+    volume={abs/1801.09936}
+}
+"""
+_DESCRIPTION = """\\\\\\\\
+PEYMA dataset includes 7,145 sentences with a total of 302,530 tokens from which 41,148 tokens are tagged with seven different classes.
+"""
+
+_DRIVE_URL = "https://drive.google.com/uc?export=download&id=1WZxpFRtEs5HZWyWQ2Pyg9CCuIBs1Kmvx"
+
+class PEYMAConfig(datasets.BuilderConfig):
+    """BuilderConfig for PEYMA."""
+    def __init__(self, **kwargs):
+        super(PEYMAConfig, self).__init__(**kwargs)
+        
+class PEYMA(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        PEYMAConfig(name="PEYMA", version=datasets.Version("1.0.0"), description="persian ner dataset"),
+    ]
+    def _info(self):
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                    "token": datasets.Value("string"),
+                    "label": datasets.Value("string")
+                }
+            ),
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage="https://hooshvare.github.io/docs/datasets/ner#peyma",
+            citation=_CITATION,
+        )
+
+    def custom_dataset(self, src_url, dest_path):
+        response = requests.get(src_url)
+        response.raise_for_status()
+
+        with open(dest_path, 'wb') as f:
+            f.write(response.content)
+
+        
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # dl_manager is a datasets.download.DownloadManager that can be used to
+        # download and extract URLs
+    
+        downloaded_file = dl_manager.download_custom(_DRIVE_URL, self.custom_dataset)
+        extracted_file = dl_manager.extract(downloaded_file)
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(extracted_file, 'peyma/train.txt')}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(extracted_file, 'peyma/test.txt')}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": os.path.join(extracted_file, 'peyma/dev.txt')}),
+        ]
+
+    def _generate_examples(self, filepath):
+        try:
+            df = pd.read_csv(filepath, error_bad_lines=False, engine='python', 
+            sep='|', names=["token", "label"])
+            for idx, row in enumerate(reader):
+                yield idx, {
+                    "token": row["token"],
+                    "label": row["label"]
+                }
+        except Exception as e:
+            print(e)