Delete loading script

asdiv.py

@@ -1,111 +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.
-"""ASDIV dataset."""
-
-
-import os
-import xml.etree.ElementTree as ET
-
-import datasets
-
-
-_CITATION = """\
-@misc{miao2021diverse,
-    title={A Diverse Corpus for Evaluating and Developing English Math Word Problem Solvers},
-    author={Shen-Yun Miao and Chao-Chun Liang and Keh-Yih Su},
-    year={2021},
-    eprint={2106.15772},
-    archivePrefix={arXiv},
-    primaryClass={cs.AI}
-}
-"""
-
-_DESCRIPTION = """\
-ASDiv (Academia Sinica Diverse MWP Dataset) is a diverse (in terms of both language
-patterns and problem types) English math word problem (MWP) corpus for evaluating
-the capability of various MWP solvers. Existing MWP corpora for studying AI progress
-remain limited either in language usage patterns or in problem types. We thus present
-a new English MWP corpus with 2,305 MWPs that cover more text patterns and most problem
-types taught in elementary school. Each MWP is annotated with its problem type and grade
-level (for indicating the level of difficulty).
-"""
-
-_HOMEPAGE = "https://github.com/chaochun/nlu-asdiv-dataset"
-
-# License declared at https://github.com/chaochun/nlu-asdiv-dataset/blob/master/README.md
-_LICENSE = "CC BY-NC 4.0"
-
-_URLS = "https://github.com/chaochun/nlu-asdiv-dataset/archive/55790e5270bb91ccfa5053194b25732534696b50.zip"
-
-
-class ASDiv(datasets.GeneratorBasedBuilder):
-    """ASDiv: A Diverse Corpus for Evaluating and Developing English Math Word Problem Solvers"""
-
-    VERSION = datasets.Version("0.0.1")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="asdiv",
-            version=VERSION,
-            description="A diverse corpus for evaluating and developing english math word problem solvers",
-        )
-    ]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "body": datasets.Value("string"),
-                "question": datasets.Value("string"),
-                "solution_type": datasets.Value("string"),
-                "answer": datasets.Value("string"),
-                "formula": datasets.Value("string"),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        urls = _URLS
-        data_dir = dl_manager.download_and_extract(urls)
-        base_filepath = "nlu-asdiv-dataset-55790e5270bb91ccfa5053194b25732534696b50"
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "filepath": os.path.join(
-                        data_dir, base_filepath, "dataset", "ASDiv.xml"
-                    ),
-                    "split": datasets.Split.VALIDATION,
-                },
-            ),
-        ]
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, filepath, split):
-        tree = ET.parse(filepath)
-        root = tree.getroot()
-        for key, problem in enumerate(root.iter("Problem")):
-            yield key, {
-                "body": problem.find("Body").text,
-                "question": problem.find("Question").text,
-                "solution_type": problem.find("Solution-Type").text,
-                "answer": problem.find("Answer").text,
-                "formula": problem.find("Formula").text,
-            }