system HF staff commited on
Commit
9012d0d
0 Parent(s):

Update files from the datasets library (from 1.0.0)

Browse files

Release notes: https://github.com/huggingface/datasets/releases/tag/1.0.0

.gitattributes ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ *.7z filter=lfs diff=lfs merge=lfs -text
2
+ *.arrow filter=lfs diff=lfs merge=lfs -text
3
+ *.bin filter=lfs diff=lfs merge=lfs -text
4
+ *.bin.* filter=lfs diff=lfs merge=lfs -text
5
+ *.bz2 filter=lfs diff=lfs merge=lfs -text
6
+ *.ftz filter=lfs diff=lfs merge=lfs -text
7
+ *.gz filter=lfs diff=lfs merge=lfs -text
8
+ *.h5 filter=lfs diff=lfs merge=lfs -text
9
+ *.joblib filter=lfs diff=lfs merge=lfs -text
10
+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
11
+ *.model filter=lfs diff=lfs merge=lfs -text
12
+ *.msgpack filter=lfs diff=lfs merge=lfs -text
13
+ *.onnx filter=lfs diff=lfs merge=lfs -text
14
+ *.ot filter=lfs diff=lfs merge=lfs -text
15
+ *.parquet filter=lfs diff=lfs merge=lfs -text
16
+ *.pb filter=lfs diff=lfs merge=lfs -text
17
+ *.pt filter=lfs diff=lfs merge=lfs -text
18
+ *.pth filter=lfs diff=lfs merge=lfs -text
19
+ *.rar filter=lfs diff=lfs merge=lfs -text
20
+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
21
+ *.tar.* filter=lfs diff=lfs merge=lfs -text
22
+ *.tflite filter=lfs diff=lfs merge=lfs -text
23
+ *.tgz filter=lfs diff=lfs merge=lfs -text
24
+ *.xz filter=lfs diff=lfs merge=lfs -text
25
+ *.zip filter=lfs diff=lfs merge=lfs -text
26
+ *.zstandard filter=lfs diff=lfs merge=lfs -text
27
+ *tfevents* filter=lfs diff=lfs merge=lfs -text
dataset_infos.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"default": {"description": "\nEraser Multi RC is a dataset for queries over multi-line passages, along with\nanswers and a rationalte. Each example in this dataset has the following 5 parts\n1. A Mutli-line Passage\n2. A Query about the passage\n3. An Answer to the query\n4. A Classification as to whether the answer is right or wrong\n5. An Explanation justifying the classification\n", "citation": "\n@unpublished{eraser2019,\n title = {ERASER: A Benchmark to Evaluate Rationalized NLP Models},\n author = {Jay DeYoung and Sarthak Jain and Nazneen Fatema Rajani and Eric Lehman and Caiming Xiong and Richard Socher and Byron C. Wallace}\n}\n@inproceedings{MultiRC2018,\n author = {Daniel Khashabi and Snigdha Chaturvedi and Michael Roth and Shyam Upadhyay and Dan Roth},\n title = {Looking Beyond the Surface:A Challenge Set for Reading Comprehension over Multiple Sentences},\n booktitle = {NAACL},\n year = {2018}\n}\n", "homepage": "https://cogcomp.seas.upenn.edu/multirc/", "license": "", "features": {"passage": {"dtype": "string", "id": null, "_type": "Value"}, "query_and_answer": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["False", "True"], "names_file": null, "id": null, "_type": "ClassLabel"}, "evidences": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "supervised_keys": null, "builder_name": "eraser_multi_rc", "config_name": "default", "version": {"version_str": "0.1.1", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 1, "patch": 1}, "splits": {"test": {"name": "test", "num_bytes": 9194475, "num_examples": 4848, "dataset_name": "eraser_multi_rc"}, "train": {"name": "train", "num_bytes": 47922877, "num_examples": 24029, "dataset_name": "eraser_multi_rc"}, "validation": {"name": "validation", "num_bytes": 6529020, "num_examples": 3214, "dataset_name": "eraser_multi_rc"}}, "download_checksums": {"http://www.eraserbenchmark.com/zipped/multirc.tar.gz": {"num_bytes": 1667550, "checksum": "7d3364fad630d0949b40cc5c4b9fd7fac0ec9ebb3a31ffa92a491e3883edd826"}}, "download_size": 1667550, "dataset_size": 63646372, "size_in_bytes": 65313922}}
dummy/0.1.1/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6586ebece48eaf697b40cf5a630c45080bcd499649b7d4aaae216e327e16c194
3
+ size 8216
eraser_multi_rc.py ADDED
@@ -0,0 +1,119 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # coding=utf-8
2
+ # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+
16
+ # Lint as: python3
17
+ """Passage, query, answers and answer classification with explanations."""
18
+
19
+ from __future__ import absolute_import, division, print_function
20
+
21
+ import json
22
+ import os
23
+
24
+ import datasets
25
+
26
+
27
+ _CITATION = """
28
+ @unpublished{eraser2019,
29
+ title = {ERASER: A Benchmark to Evaluate Rationalized NLP Models},
30
+ author = {Jay DeYoung and Sarthak Jain and Nazneen Fatema Rajani and Eric Lehman and Caiming Xiong and Richard Socher and Byron C. Wallace}
31
+ }
32
+ @inproceedings{MultiRC2018,
33
+ author = {Daniel Khashabi and Snigdha Chaturvedi and Michael Roth and Shyam Upadhyay and Dan Roth},
34
+ title = {Looking Beyond the Surface:A Challenge Set for Reading Comprehension over Multiple Sentences},
35
+ booktitle = {NAACL},
36
+ year = {2018}
37
+ }
38
+ """
39
+
40
+ _DESCRIPTION = """
41
+ Eraser Multi RC is a dataset for queries over multi-line passages, along with
42
+ answers and a rationalte. Each example in this dataset has the following 5 parts
43
+ 1. A Mutli-line Passage
44
+ 2. A Query about the passage
45
+ 3. An Answer to the query
46
+ 4. A Classification as to whether the answer is right or wrong
47
+ 5. An Explanation justifying the classification
48
+ """
49
+
50
+ _DOWNLOAD_URL = "http://www.eraserbenchmark.com/zipped/multirc.tar.gz"
51
+
52
+
53
+ class EraserMultiRc(datasets.GeneratorBasedBuilder):
54
+ """Multi Sentence Reasoning with Explanations (Eraser Benchmark)."""
55
+
56
+ VERSION = datasets.Version("0.1.1")
57
+
58
+ def _info(self):
59
+ return datasets.DatasetInfo(
60
+ description=_DESCRIPTION,
61
+ features=datasets.Features(
62
+ {
63
+ "passage": datasets.Value("string"),
64
+ "query_and_answer": datasets.Value("string"),
65
+ "label": datasets.features.ClassLabel(names=["False", "True"]),
66
+ "evidences": datasets.features.Sequence(datasets.Value("string")),
67
+ }
68
+ ),
69
+ supervised_keys=None,
70
+ homepage="https://cogcomp.seas.upenn.edu/multirc/",
71
+ citation=_CITATION,
72
+ )
73
+
74
+ def _split_generators(self, dl_manager):
75
+ """Returns SplitGenerators."""
76
+
77
+ dl_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
78
+ data_dir = os.path.join(dl_dir, "multirc")
79
+ return [
80
+ datasets.SplitGenerator(
81
+ name=datasets.Split.TRAIN,
82
+ # These kwargs will be passed to _generate_examples
83
+ gen_kwargs={"data_dir": data_dir, "filepath": os.path.join(data_dir, "train.jsonl")},
84
+ ),
85
+ datasets.SplitGenerator(
86
+ name=datasets.Split.VALIDATION,
87
+ # These kwargs will be passed to _generate_examples
88
+ gen_kwargs={"data_dir": data_dir, "filepath": os.path.join(data_dir, "val.jsonl")},
89
+ ),
90
+ datasets.SplitGenerator(
91
+ name=datasets.Split.TEST,
92
+ # These kwargs will be passed to _generate_examples
93
+ gen_kwargs={"data_dir": data_dir, "filepath": os.path.join(data_dir, "test.jsonl")},
94
+ ),
95
+ ]
96
+
97
+ def _generate_examples(self, data_dir, filepath):
98
+ """Yields examples."""
99
+
100
+ multirc_dir = os.path.join(data_dir, "docs")
101
+ with open(filepath, encoding="utf-8") as f:
102
+ for line in f:
103
+ row = json.loads(line)
104
+ evidences = []
105
+
106
+ for evidence in row["evidences"][0]:
107
+ docid = evidence["docid"]
108
+ evidences.append(evidence["text"])
109
+
110
+ passage_file = os.path.join(multirc_dir, docid)
111
+ with open(passage_file, encoding="utf-8") as f1:
112
+ passage_text = f1.read()
113
+
114
+ yield row["annotation_id"], {
115
+ "passage": passage_text,
116
+ "query_and_answer": row["query"],
117
+ "label": row["classification"],
118
+ "evidences": evidences,
119
+ }