Delete OCW.py

OCW.py

@@ -1,186 +0,0 @@
-# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# 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.
-
-"""Only Connect Wall (OCW) dataset"""
-
-import json
-import os
-
-import datasets
-
-
-_CITATION = """\
-@article{Naeini2023LargeLM,
-    title        = {Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset},
-    author       = {Saeid Alavi Naeini and Raeid Saqur and Mozhgan Saeidi and John Giorgi and Babak Taati},
-    year         = 2023,
-    journal      = {ArXiv},
-    volume       = {abs/2306.11167},
-    url          = {https://api.semanticscholar.org/CorpusID:259203717}
-}
-"""
-
-_DESCRIPTION = """\
-The Only Connect Wall (OCW) dataset contains 618 "Connecting Walls" from the Round 3: Connecting Wall segment of the Only Connect quiz show, collected from 15 seasons' worth of episodes. Each wall contains the ground-truth groups and connections as well as recorded human performance.
-"""
-
-_HOMEPAGE_URL = "https://github.com/TaatiTeam/OCW/"
-
-_LICENSE = "MIT"
-
-_BASE_URL = "https://huggingface.co/datasets/TaatiTeam/OCW/resolve/main/"
-_URLS = {
-    "ocw_train": _BASE_URL + "train.json",
-    "ocw_validation": _BASE_URL + "validation.json",
-    "ocw_test": _BASE_URL + "test.json",
-    "ocw_randomized_test": _BASE_URL + "easy_test_randomized.json",
-    "ocw_wordnet_train": _BASE_URL + "easy_train_wordnet.json",
-    "ocw_wordnet_validation": _BASE_URL + "easy_validation_wordnet.json",
-    "ocw_wordnet_test": _BASE_URL + "easy_test_wordnet.json"
-}
-
-
-class OCW(datasets.GeneratorBasedBuilder):
-    """OCW dataset"""
-
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="ocw", version=VERSION,
-                               description="main OCW dataset"),
-        datasets.BuilderConfig(name="ocw_randomized", version=VERSION,
-                               description="Easy OCW dataset with randomized groups in each wall"),
-        datasets.BuilderConfig(name="ocw_wordnet", version=VERSION,
-                               description="Easy OCW dataset with wordnet synonyms replaced with original clues")
-    ]
-
-    DEFAULT_CONFIG_NAME = "OCW"
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "dataset": datasets.features.Sequence(
-                    {
-                        "wall_id": datasets.Value("string"),
-                        "season": datasets.Value("int32"),
-                        "episode": datasets.Value("int32"),
-                        "words": datasets.Value("list"),
-                        "gt_connections": datasets.Value("list"),
-                        "group_id": datasets.Value("string"),
-                        "gt_words": datasets.Value("list"),
-                        "gt_connection": datasets.Value("list"),
-                        "grouping": datasets.Value("int32"),
-                        "connection": datasets.Value("int32")
-                    }
-                ),
-            }
-        ),
-
-        return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
-            description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=features,
-            # Homepage of the dataset for documentation
-            homepage=_HOMEPAGE_URL,
-            # License for the dataset if available
-            license=_LICENSE,
-            # Citation for the dataset
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        test_url = _URLS[self.config.name + '_test']
-        # only test set is randomized for ablation studies
-        if 'ocw_randomized' in self.config.name:
-            train_url = _URLS['ocw_train']
-            validation_url = _URLS['ocw_validation']
-        else:
-            train_url = _URLS[self.config.name + '_train']
-            validation_url = _URLS[self.config.name + '_validation']
-
-        train_path = dl_manager.download_and_extract(train_url)
-        validation_path = dl_manager.download_and_extract(validation_url)
-        test_path = dl_manager.download_and_extract(test_url)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"file_paths": train_path}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"file_paths": validation_path}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"file_paths": test_path}),
-        ]
-
-
-    def _generate_examples(self, filepath):
-        """This function returns the examples in the raw (text) form."""
-        key = 0
-        with open(filepath, encoding="utf-8") as f:
-            ocw = json.load(f)
-            for data in ocw["dataset"]:
-                wall_id = data.get("wall_id")
-                season = data.get("season")
-                episode = data.get("episode")
-                words = data.get("words")
-                gt_connections = data.get("gt_connections")
-                group_1 = data['groups']['group_1'].get("group_id")
-                group_1_human_performance = data['groups']['group_1']['human_performance']
-                group_2 = data['groups']['group_2']
-                group_2_human_performance = data['groups']['group_2']['human_performance']
-                group_3 = data['groups']['group_3']
-                group_3_human_performance = data['groups']['group_3']['human_performance']
-                group_4 = data['groups']['group_4']
-                group_4_human_performance = data['groups']['group_4']['human_performance']
-                yield key, {
-                    "wall_id": wall_id,
-                    "season": season,
-                    "episode": episode,
-                    "words": words,
-                    "gt_connections": gt_connections,
-                    "group_1": {
-                        "id": group_1.get("group_id"),
-                        "gt_words": group_1.get("gt_words"),
-                        "gt_connection": group_1.get("gt_connection"),
-                        "human_performance": {
-                            "grouping": group_1_human_performance.get("grouping"),
-                            "connection": group_1_human_performance.get("connection")
-                        }
-                    },
-                    "group_2": {
-                        "id": group_2.get("group_id"),
-                        "gt_words": group_2.get("gt_words"),
-                        "gt_connection": group_2.get("gt_connection"),
-                        "human_performance": {
-                            "grouping": group_2_human_performance.get("grouping"),
-                            "connection": group_2_human_performance.get("connection")
-                        }
-                    },
-                    "group_3": {
-                        "id": group_3.get("group_id"),
-                        "gt_words": group_3.get("gt_words"),
-                        "gt_connection": group_3.get("gt_connection"),
-                        "human_performance": {
-                            "grouping": group_3_human_performance.get("grouping"),
-                            "connection": group_3_human_performance.get("connection")
-                        }
-                    },
-                    "group_4": {
-                        "id": group_4.get("group_id"),
-                        "gt_words": group_4.get("gt_words"),
-                        "gt_connection": group_4.get("gt_connection"),
-                        "human_performance": {
-                            "grouping": group_4_human_performance.get("grouping"),
-                            "connection": group_4_human_performance.get("connection")
-                        }
-                    },
-                }
-                key += 1