Update files from the datasets library (from 1.0.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bin.* filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zstandard filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

dataset_infos.json

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+{"discofuse-sport": {"description": " DISCOFUSE is a large scale dataset for discourse-based sentence fusion. \n", "citation": "@InProceedings{GevaEtAl2019,\n  title = {{DiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion}},\n  author = {Geva, Mor and Malmi, Eric and Szpektor, Idan and Berant, Jonathan},\n  booktitle = {Proceedings of the 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics},\n  note = {arXiv preprint arXiv:1902.10526},\n  year = {2019}\n}\n\n", "homepage": "https://github.com/google-research-datasets/discofuse", "license": "", "features": {"connective_string": {"dtype": "string", "id": null, "_type": "Value"}, "discourse_type": {"dtype": "string", "id": null, "_type": "Value"}, "coherent_second_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "has_coref_type_pronoun": {"dtype": "float32", "id": null, "_type": "Value"}, "incoherent_first_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "incoherent_second_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "has_coref_type_nominal": {"dtype": "float32", "id": null, "_type": "Value"}, "coherent_first_sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "discofuse", "config_name": "discofuse-sport", "version": {"version_str": "1.0.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 152156582, "num_examples": 445521, "dataset_name": "discofuse"}, "train": {"name": "train", "num_bytes": 14784888867, "num_examples": 43291020, "dataset_name": "discofuse"}, "validation": {"name": "validation", "num_bytes": 150702794, "num_examples": 440902, "dataset_name": "discofuse"}}, "download_checksums": {"https://storage.googleapis.com/discofuse_dataset_v1/discofuse_v1_sports.tar.gz": {"num_bytes": 4326640797, "checksum": "e2716f9ada309d50e5603182e9d1e8ecb9968b5b143dbd6251c4b10b9ae61517"}}, "download_size": 4326640797, "dataset_size": 15087748243, "size_in_bytes": 19414389040}, "discofuse-wikipedia": {"description": " DISCOFUSE is a large scale dataset for discourse-based sentence fusion. \n", "citation": "@InProceedings{GevaEtAl2019,\n  title = {{DiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion}},\n  author = {Geva, Mor and Malmi, Eric and Szpektor, Idan and Berant, Jonathan},\n  booktitle = {Proceedings of the 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics},\n  note = {arXiv preprint arXiv:1902.10526},\n  year = {2019}\n}\n\n", "homepage": "https://github.com/google-research-datasets/discofuse", "license": "", "features": {"connective_string": {"dtype": "string", "id": null, "_type": "Value"}, "discourse_type": {"dtype": "string", "id": null, "_type": "Value"}, "coherent_second_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "has_coref_type_pronoun": {"dtype": "float32", "id": null, "_type": "Value"}, "incoherent_first_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "incoherent_second_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "has_coref_type_nominal": {"dtype": "float32", "id": null, "_type": "Value"}, "coherent_first_sentence": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "discofuse", "config_name": "discofuse-wikipedia", "version": {"version_str": "1.0.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 64191920, "num_examples": 163657, "dataset_name": "discofuse"}, "train": {"name": "train", "num_bytes": 6396238380, "num_examples": 16310585, "dataset_name": "discofuse"}, "validation": {"name": "validation", "num_bytes": 65870774, "num_examples": 168081, "dataset_name": "discofuse"}}, "download_checksums": {"https://storage.googleapis.com/discofuse_dataset_v1/discofuse_v1_wikipedia.tar.gz": {"num_bytes": 1717418045, "checksum": "f351abc85a581142fb9e70a2cbedcc0054bc3568f11ce8255389ef5c007eebde"}}, "download_size": 1717418045, "dataset_size": 6526301074, "size_in_bytes": 8243719119}}

discofuse.py

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+"""TODO(discofuse): Add a description here."""
+
+from __future__ import absolute_import, division, print_function
+
+import csv
+import os
+
+import datasets
+
+
+# TODO(discofuse): BibTeX citation
+
+_URL_ = "https://storage.googleapis.com/discofuse_dataset_v1/"
+_CITATION = """\
+@InProceedings{GevaEtAl2019,
+  title = {DiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion},
+  author = {Geva, Mor and Malmi, Eric and Szpektor, Idan and Berant, Jonathan},
+  booktitle = {Proceedings of the 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics},
+  note = {arXiv preprint arXiv:1902.10526},
+  year = {2019}
+}
+
+"""
+
+# TODO(discofuse):
+_DESCRIPTION = """\
+ DISCOFUSE is a large scale dataset for discourse-based sentence fusion.
+"""
+
+
+class DiscofuseConfig(datasets.BuilderConfig):
+
+    """ BuilderConfig for Discofuse"""
+
+    def __init__(self, data_url, balanced=False, **kwargs):
+        """
+
+        Args:
+            balanced: to specify if we want to load the balanced file or the full file
+            **kwargs: keyword arguments forwarded to super.
+        """
+        super(DiscofuseConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
+        self.balanced = balanced
+        self.data_url = data_url
+
+
+class Discofuse(datasets.GeneratorBasedBuilder):
+    """TODO(discofuse): Short description of my dataset."""
+
+    # TODO(discofuse): Set up version.
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = [
+        DiscofuseConfig(
+            name="discofuse-sport", description="sentence fusion", data_url=_URL_ + "discofuse_v1_sports.tar.gz"
+        ),
+        DiscofuseConfig(
+            name="discofuse-wikipedia", description="sentence fusion", data_url=_URL_ + "discofuse_v1_wikipedia.tar.gz"
+        ),
+    ]
+
+    def _info(self):
+        # TODO(discofuse): Specifies the datasets.DatasetInfo object
+        return datasets.DatasetInfo(
+            # This is the description that will appear on the datasets page.
+            description=_DESCRIPTION,
+            # datasets.features.FeatureConnectors
+            features=datasets.Features(
+                {
+                    "connective_string": datasets.Value("string"),
+                    "discourse_type": datasets.Value("string"),
+                    "coherent_second_sentence": datasets.Value("string"),
+                    "has_coref_type_pronoun": datasets.Value("float32"),
+                    "incoherent_first_sentence": datasets.Value("string"),
+                    "incoherent_second_sentence": datasets.Value("string"),
+                    "has_coref_type_nominal": datasets.Value("float32"),
+                    "coherent_first_sentence": datasets.Value("string"),
+                    # These are the features of your dataset like images, labels ...
+                }
+            ),
+            # If there's a common (input, target) tuple from the features,
+            # specify them here. They'll be used if as_supervised=True in
+            # builder.as_dataset.
+            supervised_keys=None,
+            # Homepage of the dataset for documentation
+            homepage="https://github.com/google-research-datasets/discofuse",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        # TODO(discofuse): Downloads the data and defines the splits
+        # dl_manager is a datasets.download.DownloadManager that can be used to
+        # download and extract URLs
+        if self.config.name == "discofuse-sport":
+            dl_dir = dl_manager.download_and_extract(self.config.data_url)
+            data_dir = os.path.join(dl_dir, "discofuse_v1/sports")
+            if self.config.balanced:
+                return [
+                    datasets.SplitGenerator(
+                        name=datasets.Split.TRAIN,
+                        # These kwargs will be passed to _generate_examples
+                        gen_kwargs={"filepath": os.path.join(data_dir, "train_balanced.tsv")},
+                    ),
+                    datasets.SplitGenerator(
+                        name=datasets.Split.TEST,
+                        # These kwargs will be passed to _generate_examples
+                        gen_kwargs={"filepath": os.path.join(data_dir, "test_balanced.tsv")},
+                    ),
+                    datasets.SplitGenerator(
+                        name=datasets.Split.VALIDATION,
+                        # These kwargs will be passed to _generate_examples
+                        gen_kwargs={"filepath": os.path.join(data_dir, "dev_balanced.tsv")},
+                    ),
+                ]
+            else:
+                return [
+                    datasets.SplitGenerator(
+                        name=datasets.Split.TRAIN,
+                        # These kwargs will be passed to _generate_examples
+                        gen_kwargs={"filepath": os.path.join(data_dir, "train.tsv")},
+                    ),
+                    datasets.SplitGenerator(
+                        name=datasets.Split.TEST,
+                        # These kwargs will be passed to _generate_examples
+                        gen_kwargs={"filepath": os.path.join(data_dir, "test.tsv")},
+                    ),
+                    datasets.SplitGenerator(
+                        name=datasets.Split.VALIDATION,
+                        # These kwargs will be passed to _generate_examples
+                        gen_kwargs={"filepath": os.path.join(data_dir, "dev.tsv")},
+                    ),
+                ]
+        else:
+            if self.config.name == "discofuse-wikipedia":
+                dl_dir = dl_manager.download_and_extract(self.config.data_url)
+                data_dir = os.path.join(dl_dir, "discofuse_v1/wikipedia")
+                if self.config.balanced:
+                    return [
+                        datasets.SplitGenerator(
+                            name=datasets.Split.TRAIN,
+                            # These kwargs will be passed to _generate_examples
+                            gen_kwargs={"filepath": os.path.join(data_dir, "train_balanced.tsv")},
+                        ),
+                        datasets.SplitGenerator(
+                            name=datasets.Split.TEST,
+                            # These kwargs will be passed to _generate_examples
+                            gen_kwargs={"filepath": os.path.join(data_dir, "test_balanced.tsv")},
+                        ),
+                        datasets.SplitGenerator(
+                            name=datasets.Split.VALIDATION,
+                            # These kwargs will be passed to _generate_examples
+                            gen_kwargs={"filepath": os.path.join(data_dir, "dev_balanced.tsv")},
+                        ),
+                    ]
+                else:
+                    return [
+                        datasets.SplitGenerator(
+                            name=datasets.Split.TRAIN,
+                            # These kwargs will be passed to _generate_examples
+                            gen_kwargs={"filepath": os.path.join(data_dir, "train.tsv")},
+                        ),
+                        datasets.SplitGenerator(
+                            name=datasets.Split.TEST,
+                            # These kwargs will be passed to _generate_examples
+                            gen_kwargs={"filepath": os.path.join(data_dir, "test.tsv")},
+                        ),
+                        datasets.SplitGenerator(
+                            name=datasets.Split.VALIDATION,
+                            # These kwargs will be passed to _generate_examples
+                            gen_kwargs={"filepath": os.path.join(data_dir, "dev.tsv")},
+                        ),
+                    ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        # TODO(discofuse): Yields (key, example) tuples from the dataset
+        with open(filepath, encoding="utf-8") as f:
+            data = csv.DictReader(f, delimiter="\t")
+            for id_, row in enumerate(data):
+                co_first_sent = row["coherent_first_sentence"]
+                co_second_sent = row["coherent_second_sentence"]
+                connect_str = row["connective_string"]
+                discourse_type = row["discourse_type"]
+                has_coref_pronoun = row["has_coref_type_pronoun"]
+                has_coref_nominal = row["has_coref_type_nominal"]
+                inco_first_sent = row["incoherent_first_sentence"]
+                inco_second_sent = row["incoherent_second_sentence"]
+                yield id_, {
+                    "connective_string": connect_str,
+                    "discourse_type": discourse_type,
+                    "coherent_second_sentence": co_second_sent,
+                    "has_coref_type_pronoun": has_coref_pronoun,
+                    "incoherent_first_sentence": inco_first_sent,
+                    "incoherent_second_sentence": inco_second_sent,
+                    "has_coref_type_nominal": has_coref_nominal,
+                    "coherent_first_sentence": co_first_sent,
+                }

dummy/discofuse-sport/1.0.0/dummy_data.zip

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+size 3454

dummy/discofuse-wikipedia/1.0.0/dummy_data.zip

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+size 3496