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Update files from the datasets library (from 1.0.0)

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

.gitattributes ADDED
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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.joblib filter=lfs diff=lfs merge=lfs -text
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+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
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+ *.model filter=lfs diff=lfs merge=lfs -text
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+ *.pth filter=lfs diff=lfs merge=lfs -text
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+ *.rar filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tflite filter=lfs diff=lfs merge=lfs -text
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+ *.zip filter=lfs diff=lfs merge=lfs -text
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+ *.zstandard filter=lfs diff=lfs merge=lfs -text
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+ *tfevents* filter=lfs diff=lfs merge=lfs -text
dataset_infos.json ADDED
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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 ADDED
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+ """TODO(discofuse): Add a description here."""
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+
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+ from __future__ import absolute_import, division, print_function
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+
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+ import csv
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+ import os
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+
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+ import datasets
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+
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+
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+ # TODO(discofuse): BibTeX citation
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+
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+ _URL_ = "https://storage.googleapis.com/discofuse_dataset_v1/"
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+ _CITATION = """\
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+ @InProceedings{GevaEtAl2019,
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+ title = {DiscoFuse: A Large-Scale Dataset for Discourse-Based Sentence Fusion},
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+ author = {Geva, Mor and Malmi, Eric and Szpektor, Idan and Berant, Jonathan},
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+ booktitle = {Proceedings of the 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics},
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+ note = {arXiv preprint arXiv:1902.10526},
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+ year = {2019}
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+ }
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+
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+ """
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+
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+ # TODO(discofuse):
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+ _DESCRIPTION = """\
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+ DISCOFUSE is a large scale dataset for discourse-based sentence fusion.
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+ """
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+
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+
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+ class DiscofuseConfig(datasets.BuilderConfig):
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+
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+ """ BuilderConfig for Discofuse"""
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+
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+ def __init__(self, data_url, balanced=False, **kwargs):
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+ """
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+
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+ Args:
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+ balanced: to specify if we want to load the balanced file or the full file
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+ **kwargs: keyword arguments forwarded to super.
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+ """
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+ super(DiscofuseConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs)
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+ self.balanced = balanced
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+ self.data_url = data_url
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+
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+
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+ class Discofuse(datasets.GeneratorBasedBuilder):
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+ """TODO(discofuse): Short description of my dataset."""
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+
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+ # TODO(discofuse): Set up version.
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+ VERSION = datasets.Version("1.0.0")
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+ BUILDER_CONFIGS = [
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+ DiscofuseConfig(
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+ name="discofuse-sport", description="sentence fusion", data_url=_URL_ + "discofuse_v1_sports.tar.gz"
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+ ),
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+ DiscofuseConfig(
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+ name="discofuse-wikipedia", description="sentence fusion", data_url=_URL_ + "discofuse_v1_wikipedia.tar.gz"
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+ ),
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+ ]
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+
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+ def _info(self):
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+ # TODO(discofuse): Specifies the datasets.DatasetInfo object
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+ return datasets.DatasetInfo(
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+ # This is the description that will appear on the datasets page.
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+ description=_DESCRIPTION,
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+ # datasets.features.FeatureConnectors
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+ features=datasets.Features(
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+ {
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+ "connective_string": datasets.Value("string"),
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+ "discourse_type": datasets.Value("string"),
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+ "coherent_second_sentence": datasets.Value("string"),
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+ "has_coref_type_pronoun": datasets.Value("float32"),
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+ "incoherent_first_sentence": datasets.Value("string"),
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+ "incoherent_second_sentence": datasets.Value("string"),
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+ "has_coref_type_nominal": datasets.Value("float32"),
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+ "coherent_first_sentence": datasets.Value("string"),
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+ # These are the features of your dataset like images, labels ...
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+ }
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+ ),
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+ # If there's a common (input, target) tuple from the features,
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+ # specify them here. They'll be used if as_supervised=True in
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+ # builder.as_dataset.
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+ supervised_keys=None,
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+ # Homepage of the dataset for documentation
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+ homepage="https://github.com/google-research-datasets/discofuse",
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ """Returns SplitGenerators."""
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+ # TODO(discofuse): Downloads the data and defines the splits
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+ # dl_manager is a datasets.download.DownloadManager that can be used to
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+ # download and extract URLs
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+ if self.config.name == "discofuse-sport":
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+ dl_dir = dl_manager.download_and_extract(self.config.data_url)
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+ data_dir = os.path.join(dl_dir, "discofuse_v1/sports")
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+ if self.config.balanced:
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "train_balanced.tsv")},
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TEST,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "test_balanced.tsv")},
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.VALIDATION,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "dev_balanced.tsv")},
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+ ),
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+ ]
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+ else:
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "train.tsv")},
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TEST,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "test.tsv")},
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.VALIDATION,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "dev.tsv")},
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+ ),
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+ ]
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+ else:
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+ if self.config.name == "discofuse-wikipedia":
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+ dl_dir = dl_manager.download_and_extract(self.config.data_url)
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+ data_dir = os.path.join(dl_dir, "discofuse_v1/wikipedia")
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+ if self.config.balanced:
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "train_balanced.tsv")},
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TEST,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "test_balanced.tsv")},
148
+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.VALIDATION,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "dev_balanced.tsv")},
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+ ),
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+ ]
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+ else:
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "train.tsv")},
161
+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TEST,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "test.tsv")},
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+ ),
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+ datasets.SplitGenerator(
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+ name=datasets.Split.VALIDATION,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={"filepath": os.path.join(data_dir, "dev.tsv")},
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+ ),
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+ ]
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+
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+ def _generate_examples(self, filepath):
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+ """Yields examples."""
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+ # TODO(discofuse): Yields (key, example) tuples from the dataset
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+ with open(filepath, encoding="utf-8") as f:
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+ data = csv.DictReader(f, delimiter="\t")
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+ for id_, row in enumerate(data):
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+ co_first_sent = row["coherent_first_sentence"]
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+ co_second_sent = row["coherent_second_sentence"]
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+ connect_str = row["connective_string"]
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+ discourse_type = row["discourse_type"]
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+ has_coref_pronoun = row["has_coref_type_pronoun"]
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+ has_coref_nominal = row["has_coref_type_nominal"]
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+ inco_first_sent = row["incoherent_first_sentence"]
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+ inco_second_sent = row["incoherent_second_sentence"]
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+ yield id_, {
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+ "connective_string": connect_str,
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+ "discourse_type": discourse_type,
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+ "coherent_second_sentence": co_second_sent,
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+ "has_coref_type_pronoun": has_coref_pronoun,
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+ "incoherent_first_sentence": inco_first_sent,
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+ "incoherent_second_sentence": inco_second_sent,
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+ "has_coref_type_nominal": has_coref_nominal,
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+ "coherent_first_sentence": co_first_sent,
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+ }
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