Commit
·
d6ee042
1
Parent(s):
23f40ca
add passages
Browse files- .gitattributes +2 -0
- allegro-faq.py +121 -0
- data/passages.jsonl +3 -0
- test.csv → data/test.csv +2 -2
.gitattributes
CHANGED
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@@ -54,3 +54,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.jpeg filter=lfs diff=lfs merge=lfs -text
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*.webp filter=lfs diff=lfs merge=lfs -text
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test.csv filter=lfs diff=lfs merge=lfs -text
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*.jpeg filter=lfs diff=lfs merge=lfs -text
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*.webp filter=lfs diff=lfs merge=lfs -text
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test.csv filter=lfs diff=lfs merge=lfs -text
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data/passages.jsonl filter=lfs diff=lfs merge=lfs -text
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data/test.csv filter=lfs diff=lfs merge=lfs -text
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allegro-faq.py
ADDED
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@@ -0,0 +1,121 @@
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import csv
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import json
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import datasets
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_CITATION = """\
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"""
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_DESCRIPTION = """\
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Allegro FAQ is a dataset for evaluating passage retrievers.
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"""
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_HOMEPAGE = ""
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_LICENSE = ""
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_FEATURES_PAIRS = datasets.Features(
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{
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"question_id": datasets.Value("int32"),
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"question": datasets.Value("string"),
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"passage_id": datasets.Value("string"),
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"answers": datasets.Value("string"),
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"passage_title": datasets.Value("string"),
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"passage_text": datasets.Value("string"),
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"relevant": datasets.Value("bool"),
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}
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)
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_FEATURES_PASSAGES = datasets.Features(
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{
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"id": datasets.Value("string"),
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"title": datasets.Value("string"),
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"text": datasets.Value("string"),
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}
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)
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_URLS = {
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"pairs": {
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"test": ["data/test.csv"],
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},
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"passages": {
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"test": ["data/passages.jsonl"],
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},
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}
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class AllegroFAQ(datasets.GeneratorBasedBuilder):
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"""Allegro FAQ is a dataset for evaluating passage retrievers. """
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BUILDER_CONFIGS = list(map(lambda x: datasets.BuilderConfig(name=x, version=datasets.Version("1.0.0")), _URLS.keys()))
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DEFAULT_CONFIG_NAME = "pairs"
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def _info(self):
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if self.config.name == "pairs":
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features = _FEATURES_PAIRS
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else:
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features = _FEATURES_PASSAGES
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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homepage=_HOMEPAGE,
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license=_LICENSE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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urls = _URLS[self.config.name]
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data_dir = dl_manager.download_and_extract(urls)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepaths": data_dir["test"],
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},
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),
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]
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@staticmethod
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def _parse_bool(text):
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if text == 'True':
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return True
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elif text == 'False':
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return False
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else:
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raise ValueError
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def _generate_examples(self, filepaths):
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if self.config.name == "pairs":
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boolean_features = [name for name, val in _FEATURES_PAIRS.items() if val.dtype == "bool"]
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for filepath in filepaths:
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with open(filepath, encoding="utf-8") as f:
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data = csv.DictReader(f)
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for i, row in enumerate(data):
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for boolean_feature in boolean_features:
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row[boolean_feature] = self._parse_bool(row[boolean_feature])
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yield i, row
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else:
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for filepath in filepaths:
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with open(filepath, encoding="utf-8") as f:
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for i, row in enumerate(f):
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print(row)
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parsed_row = json.loads(row)
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yield i, parsed_row
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data/passages.jsonl
ADDED
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@@ -0,0 +1,3 @@
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|
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|
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version https://git-lfs.github.com/spec/v1
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oid sha256:a0a9a4a1838a93ad9d909c5a9c6cccda98bfedb248d03d87e2937c9559ea0555
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size 369789
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test.csv → data/test.csv
RENAMED
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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| 2 |
-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:4fab4d963db7e57469c2f8c287695ac4995ea41165da8ff37f5b744638b93e0c
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size 427561
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