Delete loading script

lsat_qa.py

@@ -1,87 +0,0 @@
-# coding=utf-8
-# 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.
-"""Covid Dialog dataset in English and Chinese"""
-
-
-import copy
-import os
-import re
-import textwrap
-import json
-
-import datasets
-
-
-# BibTeX citation
-_CITATION = """
-"""
-
-# Official description of the dataset
-_DESCRIPTION = textwrap.dedent(
-    """
-    """
-)
-
-# Link to an official homepage for the dataset here
-_HOMEPAGE = ""
-
-_LICENSE = ""
-
-
-import datasets
-import os
-import json
-
-names = ["all", "assignment", "grouping", "miscellaneous", "ordering"]
-
-class LsatQA(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-
-    BUILDER_CONFIGS = [datasets.BuilderConfig(name=name, version=datasets.Version("1.0.0"), description=_DESCRIPTION) for name in names]
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "passage": datasets.Value("string"),
-                "question": datasets.Value("string"),
-                "references": datasets.Sequence(datasets.Value("string")),
-                "gold_index": datasets.Value("int64"),
-            }
-        )
-        return datasets.DatasetInfo(
-            description=f"LSAT QA dataset, as preprocessed and shuffled in HELM",
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        test = dl_manager.download(os.path.join(self.config.name, "test.jsonl"))
-        train = dl_manager.download(os.path.join(self.config.name, "train.jsonl"))
-        val = dl_manager.download(os.path.join(self.config.name, "valid.jsonl"))
-        
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={"file": test},
-            )
-        ]
-
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
-    def _generate_examples(self, file):
-        with open(file, encoding="utf-8") as f:
-            for ix, line in enumerate(f):
-                yield ix, json.loads(line)