adding script and sample data

persian_blog_V2.py

@@ -0,0 +1,58 @@
+import datasets
+import csv
+import os
+import sys
+csv.field_size_limit(sys.maxsize)
+
+_DESCRIPTION = """persian_blog is a dataset consist of 400K blog posts from various websites and has types of tones.
+this dataset can be used in different NLG tasks and as a show-case it's is used in training reformer-persian."""
+_PROJECT_URL = """"""
+
+
+_CITATION = """
+https://saied71.github.io/RohanAiLab/,
+  author={Saied Alimoradi},
+  year={2021}
+}
+"""
+
+train = "sample_train.zip"
+test = "sample_test.zip"
+
+class persian_blog_V2(datasets.GeneratorBasedBuilder):
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "text": datasets.Value("string")
+                }
+            ),
+            homepage=_PROJECT_URL,
+            citation=_CITATION,
+        )
+
+
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        dl_train = dl_manager.download_and_extract(train)
+        dl_test = dl_manager.download_and_extract(valid)
+        train_dir = os.path.join(dl_train, "sample_train.zip")
+        test_dir = os.path.join(dl_train, "sample_test.zip")
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_dir}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_dir}),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        with open(filepath, encoding="utf-8") as f:
+            reader = csv.reader(f)
+            for id_, row in enumerate(reader):
+                if id_ == 0:
+                    continue
+                yield id_, {
+                    "text": row[0]
+                }