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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+{"plain_text": {"description": "Composed by 30 students from one of the author's undergraduate classes. These\nsentence pairs cover topics ranging from real events (e.g., Iran's plan to\nattack the Saudi ambassador to the U.S.) to events/characters in movies (e.g.,\nBatman) and purely imaginary situations, largely reflecting the pop culture as\nperceived by the American kids born in the early 90s. Each annotated example\nspans four lines: the first line contains the sentence, the second line contains\nthe target pronoun, the third line contains the two candidate antecedents, and\nthe fourth line contains the correct antecedent. If the target pronoun appears\nmore than once in the sentence, its first occurrence is the one to be resolved.\n", "citation": "@inproceedings{rahman2012resolving,\n  title={Resolving complex cases of definite pronouns: the winograd schema challenge},\n  author={Rahman, Altaf and Ng, Vincent},\n  booktitle={Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning},\n  pages={777--789},\n  year={2012},\n  organization={Association for Computational Linguistics}\n}", "homepage": "http://www.hlt.utdallas.edu/~vince/data/emnlp12/", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "pronoun": {"dtype": "string", "id": null, "_type": "Value"}, "candidates": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": 2, "id": null, "_type": "Sequence"}, "label": {"num_classes": 2, "names": ["0", "1"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "supervised_keys": {"input": "sentence", "output": "label"}, "builder_name": "definite_pronoun_resolution", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 72187, "num_examples": 564, "dataset_name": "definite_pronoun_resolution"}, "train": {"name": "train", "num_bytes": 172672, "num_examples": 1322, "dataset_name": "definite_pronoun_resolution"}}, "download_checksums": {"http://www.hlt.utdallas.edu/~vince/data/emnlp12/train.c.txt": {"num_bytes": 160409, "checksum": "bc0a54b3ca1009d8d5b2ca5a221086aee2b0fc5cd03b22b9dfa9cdf44c629cec"}, "http://www.hlt.utdallas.edu/~vince/data/emnlp12/test.c.txt": {"num_bytes": 67044, "checksum": "cf1cf025e1d59a5b363e6dcfbd5a13aae8a9830831ac16fd7f865aca7a1559d8"}}, "download_size": 227453, "dataset_size": 244859, "size_in_bytes": 472312}}

definite_pronoun_resolution.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
+"""The Definite Pronoun Resolution Dataset."""
+
+from __future__ import absolute_import, division, print_function
+
+import datasets
+
+
+_CITATION = """\
+@inproceedings{rahman2012resolving,
+  title={Resolving complex cases of definite pronouns: the winograd schema challenge},
+  author={Rahman, Altaf and Ng, Vincent},
+  booktitle={Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning},
+  pages={777--789},
+  year={2012},
+  organization={Association for Computational Linguistics}
+}"""
+
+_DESCRIPTION = """\
+Composed by 30 students from one of the author's undergraduate classes. These
+sentence pairs cover topics ranging from real events (e.g., Iran's plan to
+attack the Saudi ambassador to the U.S.) to events/characters in movies (e.g.,
+Batman) and purely imaginary situations, largely reflecting the pop culture as
+perceived by the American kids born in the early 90s. Each annotated example
+spans four lines: the first line contains the sentence, the second line contains
+the target pronoun, the third line contains the two candidate antecedents, and
+the fourth line contains the correct antecedent. If the target pronoun appears
+more than once in the sentence, its first occurrence is the one to be resolved.
+"""
+
+_DATA_URL_PATTERN = "http://www.hlt.utdallas.edu/~vince/data/emnlp12/{}.c.txt"
+
+
+class DefinitePronounResolution(datasets.GeneratorBasedBuilder):
+    """The Definite Pronoun Resolution Dataset."""
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="plain_text",
+            version=datasets.Version("1.0.0", ""),
+            description="Plain text import of the Definite Pronoun Resolution Dataset.",  # pylint: disable=line-too-long
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "sentence": datasets.Value("string"),
+                    "pronoun": datasets.Value("string"),
+                    "candidates": datasets.features.Sequence(datasets.Value("string"), length=2),
+                    "label": datasets.features.ClassLabel(num_classes=2),
+                }
+            ),
+            supervised_keys=("sentence", "label"),
+            homepage="http://www.hlt.utdallas.edu/~vince/data/emnlp12/",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        files = dl_manager.download_and_extract(
+            {
+                "train": _DATA_URL_PATTERN.format("train"),
+                "test": _DATA_URL_PATTERN.format("test"),
+            }
+        )
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": files["test"]}),
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": files["train"]}),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            line_num = -1
+            while True:
+                line_num += 1
+                sentence = f.readline().strip()
+                pronoun = f.readline().strip()
+                candidates = [c.strip() for c in f.readline().strip().split(",")]
+                correct = f.readline().strip()
+                f.readline()
+                if not sentence:
+                    break
+                yield line_num, {
+                    "sentence": sentence,
+                    "pronoun": pronoun,
+                    "candidates": candidates,
+                    "label": candidates.index(correct),
+                }

dummy/plain_text/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e7fac313481f024c2f5f7d4ae3c4993c197786264bf783e0b65be7c9ccb17a74
+size 850