Add dataset card and python file

dataset-financial-documents-2.py

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+# coding=utf-8
+# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
+#
+# 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.
+
+# Lint as: python3
+"""Multi-News dataset."""
+
+import datasets
+
+_LICENSE = "For non-commercial research and educational purposes only"
+
+_DESCRIPTION = """
+Financial documents
+"""
+
+_REPO = "https://huggingface.co/datasets/searde/dataset-financial-documents-2/blob/main/data"
+_URLs = {
+    "train": [
+        f"{_REPO}/train.src.cleaned",
+        f"{_REPO}/train.tgt",
+    ],
+    "val": [
+        f"{_REPO}/val.src.cleaned",
+        f"{_REPO}/val.tgt",
+    ],
+    "test": [
+        f"{_REPO}/test.src.cleaned",
+        f"{_REPO}/test.tgt",
+    ],
+}
+
+_DOCUMENT = "document"
+_SUMMARY = "summary"
+
+
+class DatasetFinancialDocuments(datasets.GeneratorBasedBuilder):
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features({_DOCUMENT: datasets.Value("string"), _SUMMARY: datasets.Value("string")}),
+            supervised_keys=(_DOCUMENT, _SUMMARY),
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        files = dl_manager.download(_URLs)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"src_file": files["train"][0], "tgt_file": files["train"][1]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"src_file": files["val"][0], "tgt_file": files["val"][1]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"src_file": files["test"][0], "tgt_file": files["test"][1]},
+            ),
+        ]
+
+    def _generate_examples(self, src_file, tgt_file):
+        """Yields examples."""
+        with open(src_file, encoding="utf-8") as src_f, open(tgt_file, encoding="utf-8") as tgt_f:
+            for i, (src_line, tgt_line) in enumerate(zip(src_f, tgt_f)):
+                yield i, {
+                    # In original file, each line has one example and natural newline
+                    # tokens "\n" are being replaced with "NEWLINE_CHAR". Here restore
+                    # the natural newline token to avoid special vocab "NEWLINE_CHAR".
+                    _DOCUMENT: src_line.strip().replace("NEWLINE_CHAR", "\n"),
+                    _SUMMARY: tgt_line.strip(),
+                }

dataset_infos.json

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+{"default": {"description": "\nFinancial documentsF", "license": "For non-commercial research and educational purposes only", "features": {"document": {"dtype": "string", "id": null, "_type": "Value"}, "summary": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "document", "output": "summary"}, "task_templates": null, "builder_name": "dataset-financial-documents-2", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 558392265, "num_examples": 44972, "dataset_name": "dataset-financial-documents-2"}, "validation": {"name": "validation", "num_bytes": 68272432, "num_examples": 5622, "dataset_name": "dataset-financial-documents-2"}, "test": {"name": "test", "num_bytes": 70032124, "num_examples": 5622, "dataset_name": "dataset-financial-documents-2"}}, "download_checksums": {"https://huggingface.co/datasets/searde/dataset-financial-documents-2/blob/main/data/train.src.cleaned": {"num_bytes": 547512283, "checksum": "627781c8ce55d528fcdacd495db45583a915e2d24b7983b0a5a6693ede933bb1"}, "https://huggingface.co/datasets/searde/dataset-financial-documents-2/blob/main/data/train.tgt": {"num_bytes": 58793912, "checksum": "e9e82b8f413b0f1ed4eb7c883f93bb744f829c218c1608b6ba7615d687d07121"}, "https://huggingface.co/datasets/searde/dataset-financial-documents-2/blob/main/data/val.src.cleaned": {"num_bytes": 66875522, "checksum": "f0a43902da366eea2b882e39ddd4c0975ad44aba6b61095a2ea90362e9e2bb65"}, "https://huggingface.co/datasets/searde/dataset-financial-documents-2/blob/main/data/val.tgt": {"num_bytes": 7295302, "checksum": "bb08a078e0cb2b8ca9cc0fe3bfbe9d4098dee706bd00eb97449155e41b880157"}, "https://huggingface.co/datasets/searde/dataset-financial-documents-2/blob/main/data/test.src.cleaned": {"num_bytes": 68999509, "checksum": "138d3ac2dc899cbcd2e3745aaa94d1c1db55fb7058d9df4ba3ef2dac05a3a186"}, "https://huggingface.co/datasets/searde/dataset-financial-documents-2/blob/main/data/test.tgt": {"num_bytes": 7309099, "checksum": "fa97cf91a62ae82a0af6da88f2ddf8e06eb4e3b90f7971d8e0c516436518fae3"}}, "download_size": 756785627, "post_processing_size": null, "dataset_size": 696696821, "size_in_bytes": 1453482448}}