Create long-summarization-persian.py

long-summarization-persian.py

@@ -0,0 +1,71 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import csv
+import json
+import os
+
+import datasets
+
+
+_DESCRIPTION = """\
+This new dataset is designed to solve persian long summarization tasks.
+"""
+
+_URLS = {
+    "train": "https://huggingface.co/datasets/zedfum/long-summarization-persian/blob/main/train.csv",
+    "validation": "https://huggingface.co/datasets/zedfum/long-summarization-persian/blob/main/validation.csv",
+    "test": "https://huggingface.co/datasets/zedfum/long-summarization-persian/blob/main/test.csv",
+}
+
+class NewDataset(datasets.GeneratorBasedBuilder):
+
+    VERSION = datasets.Version("1.0.0")
+
+
+    def _info(self):
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "article": datasets.Value("string"),
+                    "summary": datasets.Value("string")
+                }
+            ),
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = _URLS
+        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.TEST, gen_kwargs={"filepath": downloaded_files["test"]}
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": downloaded_files["validation"]},
+            ),
+        ]
+    def _generate_examples(self, filepath, split):
+        df = pd.read_csv(filepath)
+        for idx, example in enumerate(df.itertuples(index=False)):
+            yield idx, {"id":example.id,"article": example.article, "summary": example.summary}
+                    }