Delete gap_raw.py with huggingface_hub

gap_raw.py

@@ -1,118 +0,0 @@
-# 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
-"""GAP is a gender-balanced text data set."""
-
-
-import csv
-
-import datasets
-
-
-_CITATION = """
-@article{DBLP:journals/corr/abs-1810-05201,
-  author    = {Kellie Webster and
-               Marta Recasens and
-               Vera Axelrod and
-               Jason Baldridge},
-  title     = {Mind the {GAP:} {A} Balanced Corpus of Gendered Ambiguous Pronouns},
-  journal   = {CoRR},
-  volume    = {abs/1810.05201},
-  year      = {2018},
-  url       = {http://arxiv.org/abs/1810.05201},
-  archivePrefix = {arXiv},
-  eprint    = {1810.05201},
-  timestamp = {Tue, 30 Oct 2018 20:39:56 +0100},
-  biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1810-05201},
-  bibsource = {dblp computer science bibliography, https://dblp.org}
-}
-"""
-
-_DESCRIPTION = """
-GAP is a gender-balanced dataset containing 8,908 coreference-labeled pairs of
-(ambiguous pronoun, antecedent name), sampled from Wikipedia and released by
-Google AI Language for the evaluation of coreference resolution in practical
-applications.
-"""
-
-_TRAINURL = "https://raw.githubusercontent.com/google-research-datasets/gap-coreference/master/gap-development.tsv"
-_VALIDATIONURL = "https://raw.githubusercontent.com/google-research-datasets/gap-coreference/master/gap-validation.tsv"
-_TESTURL = "https://raw.githubusercontent.com/google-research-datasets/gap-coreference/master/gap-test.tsv"
-
-
-class Gap(datasets.GeneratorBasedBuilder):
-    """GAP is a gender-balanced dataset.
-
-    It contains 8,908 coreference-labeled pairs
-    of (ambiguous pronoun, antecedent name), sampled from Wikipedia.
-    """
-
-    VERSION = datasets.Version("0.1.0")
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "ID": datasets.Value("string"),
-                    "Text": datasets.Value("string"),
-                    "Pronoun": datasets.Value("string"),
-                    "Pronoun-offset": datasets.Value("int32"),
-                    "A": datasets.Value("string"),
-                    "A-offset": datasets.Value("int32"),
-                    "A-coref": datasets.Value("bool"),
-                    "B": datasets.Value("string"),
-                    "B-offset": datasets.Value("int32"),
-                    "B-coref": datasets.Value("bool"),
-                    "URL": datasets.Value("string"),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://github.com/google-research-datasets/gap-coreference",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        directory = dl_manager.download_and_extract(
-            {"train": _TRAINURL, "validation": _VALIDATIONURL, "test": _TESTURL}
-        )
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"filepath": directory["train"]},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={"filepath": directory["validation"]},
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"filepath": directory["test"]},
-            ),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Yields examples."""
-        with open(filepath, encoding="utf-8") as tsvfile:
-            reader = csv.DictReader(tsvfile, dialect="excel-tab")
-            for i, row in enumerate(reader):
-                row["A-coref"] = row["A-coref"] == "TRUE"
-                row["B-coref"] = row["B-coref"] == "TRUE"
-                row["A-offset"] = int(row["A-offset"])
-                row["B-offset"] = int(row["B-offset"])
-                row["Pronoun-offset"] = int(row["Pronoun-offset"])
-                yield i, row