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M4LE.py

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+# 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.
+import os
+
+import datasets
+import json
+
+
+_DESCRIPTION = (
+    "M4LE is a systematic and comprehensive long-context benchmark. It aims to"
+    " evaluate LM performances in five long-context understanding abilities,"
+    " across multiple domains, languages and task types."
+)
+_HOMEPAGE = "https://github.com/KwanWaiChung/M4LE"
+_LICENSE = """MIT License
+Copyright (c) 2023 Wai-Chung Kwan
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE."""
+URL = r"https://huggingface.co/datasets/wckwan/M4LE/resolve/main/data.zip"
+
+
+tasks = [
+    "mnds-news_semantic-multiple_cls+cnt",
+    "news-commentary_global_tran-zh2en",
+    "wiki2019zh_semantic-single_nli+ret",
+    "thucnews_semantic-multiple_cls+cnt",
+    "pubmed_global_sum",
+    "marc_explicit-multiple_cls+ret",
+    "bigpatent_global_cls",
+    "wow_explicit-single_ret",
+    "cepsum_explicit-single_sum+ret",
+    "drcd_explicit-single_ret",
+    "arxiv_global_sum",
+    "nq-open_semantic-single_qa",
+    "triviaqa_global_qa",
+    "booksum_global_sum",
+    "online-shopping_explicit-multiple_cls+ret",
+    "c3_explicit-single_qa+ret",
+    "clts_global_sum",
+    "cnnnews_explicit-single_sum+ret",
+    "wikihow_semantic-single_sum",
+    "news-commentary_global_tran-en2zh",
+    "hotpotqa_semantic-multiple_qa",
+    "duorc_semantic-single_qa",
+    "wikitext-103_semantic-single_nli+ret",
+    "lcsts_explicit-single_sum+ret",
+    "newsqa_explicit-single_qa",
+    "dureader_semantic-single_qa",
+    "mnds-news_explicit-multiple_cls+ret",
+    "tedtalks_semantic-single_tran+ret-zh2en",
+    "drcd_semantic-single_qa",
+    "news2016_semantic-single_sum+ret",
+    "mnds-news_explicit-single_cls+ret",
+    "open-subtitles_global_tran-zh2en",
+    "bigpatent_global_sum",
+    "cnewsum_global_sum",
+    "ncls_explicit-single_sum+ret",
+    "open-subtitles_global_tran-en2zh",
+    "thucnews_explicit-single_cls+ret",
+    "thucnews_explicit-multiple_cls+ret",
+    "tedtalks_semantic-single_tran+ret-en2zh",
+]
+
+
+class M4LEConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super().__init__(version=datasets.Version("1.0.0"), **kwargs)
+
+
+class LongBench(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        M4LEConfig(
+            name=task,
+        )
+        for task in tasks
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "instruction": datasets.Value("string"),
+                "input": datasets.Value("string"),
+                "answers": [datasets.Value("string")],
+                "input_length": datasets.Value("int32"),
+                "total_length": datasets.Value("int32"),
+                "length_bucket": datasets.Value("int32"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+        )
+
+    def _split_generators(self, dl_manager):
+        data_dir = dl_manager.download_and_extract(URL)
+        task_name = self.config.name
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(
+                        data_dir, "data", f"{task_name}.jsonl"
+                    ),
+                },
+            )
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            for idx, line in enumerate(f):
+                key = f"{self.config.name}-{idx}"
+                item = json.loads(line)
+                yield key, {
+                    "instruction": item["instruction"],
+                    "input": item["input"],
+                    "answers": item["answers"],
+                    "input_length": item["input_length"],
+                    "total_length": item["total_length"],
+                    "length_bucket": item["length_bucket"],
+                }

data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c69d03adbc2fcc893a4db61d06f2eba65af901d6c9e5bd9a31614b3436931bff
+size 1090018654