Delete loading script

prost.py

@@ -1,85 +0,0 @@
-# Copyright 2020 The HuggingFace Datasets Authors and Cory Paik
-#
-# 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.
-# ==============================================================================
-""" Physical Reasoning about Objects Through Space and Time (PROST)
-  
-  PROST is a probing dataset to evaluate the ability of pretrained LMs to 
-  understand and reason about the physical world. 
-"""
-import json
-import datasets
-
-
-_CITATION = """\
-@inproceedings{aroca-ouellette-etal-2021-prost,
-  title = "{PROST}: {P}hysical Reasoning about Objects through Space and Time",
-  author = "Aroca-Ouellette, St{\'e}phane  and
-    Paik, Cory  and
-    Roncone, Alessandro  and
-    Kann, Katharina",
-  booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
-  month = aug,
-  year = "2021",
-  address = "Online",
-  publisher = "Association for Computational Linguistics",
-  url = "https://aclanthology.org/2021.findings-acl.404",
-  pages = "4597--4608",
-}
-"""
-
-
-_DESCRIPTION = """\
-*Physical Reasoning about Objects Through Space and Time* (PROST) is a probing dataset to evaluate the ability of pretrained LMs to understand and reason about the physical world. PROST consists of 18,736 cloze-style multiple choice questions from 14 manually curated templates, covering 10 physical reasoning concepts:  direction, mass, height, circumference, stackable, rollable, graspable, breakable, slideable, and bounceable.
-"""
-
-_HOMEPAGE = 'https://github.com/nala-cub/prost'
-_LICENSE = 'Apache 2.0'
-
-_URL = 'https://huggingface.co/datasets/corypaik/prost/resolve/main/data'
-
-_URLs = {'default': f'{_URL}/default.jsonl'}
-
-MC_LABELS = list('ABCD')
-
-
-class Prost(datasets.GeneratorBasedBuilder):
-
-  VERSION = datasets.Version('1.0.1')
-
-  def _info(self):
-    features = datasets.Features({
-      'A': datasets.Value('string'),
-      'B': datasets.Value('string'),
-      'C': datasets.Value('string'),
-      'D': datasets.Value('string'),
-      'context': datasets.Value('string'),
-      'question': datasets.Value('string'),
-      'ex_question': datasets.Value('string'),
-      'group': datasets.Value('string'),
-      'label': datasets.ClassLabel(names=MC_LABELS),
-      'name': datasets.Value('string'),})
-    return datasets.DatasetInfo(description=_DESCRIPTION, features=features,
-                                supervised_keys=None, homepage=_HOMEPAGE,
-                                license=_LICENSE, citation=_CITATION)
-
-  def _split_generators(self, dl_manager):
-    """ Returns SplitGenerators."""
-    path = dl_manager.download_and_extract(_URLs[self.config.name])
-    kwargs = {'path': path}
-    return [datasets.SplitGenerator(datasets.Split.TEST, gen_kwargs=kwargs)]
-
-  def _generate_examples(self, path):
-    with open(path, 'r') as f:
-      for _id, line in enumerate(f.readlines()):
-        yield _id, json.loads(line)