meta

dataset_infos.json

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+{"github.com": {"description": "Dataset for automatic summarization of Russian news\n", "citation": "\n@InProceedings{10.1007/978-3-030-59082-6_9,\n    author=\"Gusev, Ilya\",\n    editor=\"Filchenkov, Andrey and Kauttonen, Janne and Pivovarova, Lidia\",\n    title=\"Dataset for Automatic Summarization of Russian News\",\n    booktitle=\"Artificial Intelligence and Natural Language\",\n    year=\"2020\",\n    publisher=\"Springer International Publishing\",\n    address=\"Cham\",\n    pages=\"122--134\",\n    isbn=\"978-3-030-59082-6\"\n}\n", "homepage": "https://github.com/IlyaGusev/gazeta", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "summary": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "date": {"dtype": "string", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "gazeta_dataset", "config_name": "github.com", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 468510447, "num_examples": 52400, "dataset_name": "gazeta_dataset"}, "test": {"name": "test", "num_bytes": 51888697, "num_examples": 5770, "dataset_name": "gazeta_dataset"}, "validation": {"name": "validation", "num_bytes": 48394731, "num_examples": 5265, "dataset_name": "gazeta_dataset"}}, "download_checksums": {"https://github.com/IlyaGusev/gazeta/releases/download/0.1/gazeta_jsonl.tar.gz": {"num_bytes": 158907783, "checksum": "43787350a7690803f6a50b99976c1884abf2d3a0246cea2a68e394b2b7d7fa66"}}, "download_size": 158907783, "post_processing_size": null, "dataset_size": 568793875, "size_in_bytes": 727701658}}

gazeta.py

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+# coding=utf-8
+# 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.
+"""Dataset for automatic summarization of Russian news"""
+
+
+import csv
+import json
+import os
+
+import datasets
+
+
+_CITATION = """
+@InProceedings{10.1007/978-3-030-59082-6_9,
+    author="Gusev, Ilya",
+    editor="Filchenkov, Andrey and Kauttonen, Janne and Pivovarova, Lidia",
+    title="Dataset for Automatic Summarization of Russian News",
+    booktitle="Artificial Intelligence and Natural Language",
+    year="2020",
+    publisher="Springer International Publishing",
+    address="Cham",
+    pages="122--134",
+    isbn="978-3-030-59082-6"
+}
+"""
+
+_DESCRIPTION = """\
+Dataset for automatic summarization of Russian news
+"""
+
+_HOMEPAGE = "https://github.com/IlyaGusev/gazeta"
+
+_LICENSE = ""
+
+_URLs = {
+    'github.com': "https://github.com/IlyaGusev/gazeta/releases/download/0.1/gazeta_jsonl.tar.gz",
+}
+
+
+class GazetaDataset(datasets.GeneratorBasedBuilder):
+    """Dataset for automatic summarization of Russian news"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="github.com", version=VERSION, description=""),
+    ]
+
+    DEFAULT_CONFIG_NAME = "github.com"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "text": datasets.Value("string"),
+                "summary": datasets.Value("string"),
+                "title": datasets.Value("string"),
+                "date": datasets.Value("string"),
+                "url": datasets.Value("string")
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
+
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+        my_urls = _URLs[self.config.name]
+        data_dir = dl_manager.download_and_extract(my_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "gazeta_train.jsonl"),
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "gazeta_test.jsonl"),
+                    "split": "test"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, "gazeta_val.jsonl"),
+                    "split": "dev",
+                },
+            ),
+        ]
+
+    def _generate_examples(
+        self, filepath, split
+    ):
+        with open(filepath, encoding="utf-8") as f:
+            for id_, row in enumerate(f):
+                data = json.loads(row)
+                yield id_, data