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Update files from the datasets library (from 1.8.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.8.0

.gitattributes ADDED
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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.bin filter=lfs diff=lfs merge=lfs -text
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+ *.bin.* filter=lfs diff=lfs merge=lfs -text
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+ *.bz2 filter=lfs diff=lfs merge=lfs -text
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+ *.ftz filter=lfs diff=lfs merge=lfs -text
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+ *.gz filter=lfs diff=lfs merge=lfs -text
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+ *.h5 filter=lfs diff=lfs merge=lfs -text
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+ *.joblib filter=lfs diff=lfs merge=lfs -text
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+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
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+ *.model filter=lfs diff=lfs merge=lfs -text
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+ *.msgpack filter=lfs diff=lfs merge=lfs -text
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+ *.onnx filter=lfs diff=lfs merge=lfs -text
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+ *.ot filter=lfs diff=lfs merge=lfs -text
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+ *.parquet filter=lfs diff=lfs merge=lfs -text
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+ *.pb filter=lfs diff=lfs merge=lfs -text
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+ *.pt filter=lfs diff=lfs merge=lfs -text
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+ *.pth filter=lfs diff=lfs merge=lfs -text
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+ *.rar filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tflite filter=lfs diff=lfs merge=lfs -text
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+ *.tgz filter=lfs diff=lfs merge=lfs -text
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+ *.xz filter=lfs diff=lfs merge=lfs -text
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+ *.zip filter=lfs diff=lfs merge=lfs -text
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+ *.zstandard filter=lfs diff=lfs merge=lfs -text
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+ *tfevents* filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ annotations_creators:
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+ - found
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+ language_creators:
5
+ - found
6
+ languages:
7
+ - da
8
+ - nb
9
+ - lv
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+ - zh
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+ - en
12
+ licenses:
13
+ - other-C-UDA
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+ multilinguality:
15
+ - multilingual
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+ size_categories:
17
+ - 10K<n<100K
18
+ source_datasets:
19
+ - original
20
+ task_categories:
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+ - conditional-text-generation
22
+ task_ids:
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+ - machine-translation
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+ ---
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+ # Dataset Card for "code_x_glue_tt_text_to_text"
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+
27
+ ## Table of Contents
28
+ - [Dataset Description](#dataset-description)
29
+ - [Dataset Summary](#dataset-summary)
30
+ - [Supported Tasks and Leaderboards](#supported-tasks)
31
+ - [Languages](#languages)
32
+ - [Dataset Structure](#dataset-structure)
33
+ - [Data Instances](#data-instances)
34
+ - [Data Fields](#data-fields)
35
+ - [Data Splits](#data-splits-sample-size)
36
+ - [Dataset Creation](#dataset-creation)
37
+ - [Curation Rationale](#curation-rationale)
38
+ - [Source Data](#source-data)
39
+ - [Annotations](#annotations)
40
+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
41
+ - [Considerations for Using the Data](#considerations-for-using-the-data)
42
+ - [Social Impact of Dataset](#social-impact-of-dataset)
43
+ - [Discussion of Biases](#discussion-of-biases)
44
+ - [Other Known Limitations](#other-known-limitations)
45
+ - [Additional Information](#additional-information)
46
+ - [Dataset Curators](#dataset-curators)
47
+ - [Licensing Information](#licensing-information)
48
+ - [Citation Information](#citation-information)
49
+ - [Contributions](#contributions)
50
+
51
+ ## Dataset Description
52
+
53
+ - **Homepage:** https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text
54
+
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+ ### Dataset Summary
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+
57
+ CodeXGLUE text-to-text dataset, available at https://github.com/microsoft/CodeXGLUE/tree/main/Text-Text/text-to-text
58
+
59
+ The dataset we use is crawled and filtered from Microsoft Documentation, whose document located at https://github.com/MicrosoftDocs/.
60
+
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+ ### Supported Tasks and Leaderboards
62
+
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+ - `machine-translation`: The dataset can be used to train a model for translating Technical documentation between languages.
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+
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+ ### Languages
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+
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+ da_en, lv_en, no_en, zh_en
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ #### da_en
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+
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+ An example of 'test' looks as follows.
76
+ ```
77
+ {
78
+ "id": 0,
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+ "source": "4 . K\u00f8r modellen , og udgiv den som en webtjeneste .\n",
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+ "target": "4 . Run the model , and publish it as a web service .\n"
81
+ }
82
+ ```
83
+
84
+ #### lv_en
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+
86
+ An example of 'train' looks as follows.
87
+ ```
88
+ {
89
+ "id": 0,
90
+ "source": "title : Pakalpojumu objektu izveide\n",
91
+ "target": "title : Create service objects\n"
92
+ }
93
+ ```
94
+
95
+ #### no_en
96
+
97
+ An example of 'validation' looks as follows.
98
+ ```
99
+ {
100
+ "id": 0,
101
+ "source": "2 . \u00c5pne servicevaren du vil definere komponenter fra en stykkliste for .\n",
102
+ "target": "2 . Open the service item for which you want to set up components from a BOM .\n"
103
+ }
104
+ ```
105
+
106
+ #### zh_en
107
+
108
+ An example of 'validation' looks as follows.
109
+ ```
110
+ {
111
+ "id": 0,
112
+ "source": "& # 124 ; MCDUserNotificationReadStateFilterAny & # 124 ; 0 & # 124 ; \u5305\u62ec \u901a\u77e5 , \u800c \u4e0d \u8003\u8651 \u8bfb\u53d6 \u72b6\u6001 \u3002 & # 124 ;\n",
113
+ "target": "&#124; MCDUserNotificationReadStateFilterAny &#124; 0 &#124; Include notifications regardless of read state . &#124;\n"
114
+ }
115
+ ```
116
+
117
+ ### Data Fields
118
+
119
+ In the following each data field in go is explained for each config. The data fields are the same among all splits.
120
+
121
+ #### da_en, lv_en, no_en, zh_en
122
+
123
+ |field name| type | description |
124
+ |----------|------|----------------------------------------|
125
+ |id |int32 | The index of the sample |
126
+ |source |string| The source language version of the text|
127
+ |target |string| The target language version of the text|
128
+
129
+ ### Data Splits
130
+
131
+ |name |train|validation|test|
132
+ |-----|----:|---------:|---:|
133
+ |da_en|42701| 1000|1000|
134
+ |lv_en|18749| 1000|1000|
135
+ |no_en|44322| 1000|1000|
136
+ |zh_en|50154| 1000|1000|
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+
138
+ ## Dataset Creation
139
+
140
+ ### Curation Rationale
141
+
142
+ [More Information Needed]
143
+
144
+ ### Source Data
145
+
146
+ #### Initial Data Collection and Normalization
147
+
148
+ [More Information Needed]
149
+
150
+ #### Who are the source language producers?
151
+
152
+ [More Information Needed]
153
+
154
+ ### Annotations
155
+
156
+ #### Annotation process
157
+
158
+ [More Information Needed]
159
+
160
+ #### Who are the annotators?
161
+
162
+ [More Information Needed]
163
+
164
+ ### Personal and Sensitive Information
165
+
166
+ [More Information Needed]
167
+
168
+ ## Considerations for Using the Data
169
+
170
+ ### Social Impact of Dataset
171
+
172
+ [More Information Needed]
173
+
174
+ ### Discussion of Biases
175
+
176
+ [More Information Needed]
177
+
178
+ ### Other Known Limitations
179
+
180
+ [More Information Needed]
181
+
182
+ ## Additional Information
183
+
184
+ ### Dataset Curators
185
+
186
+ https://github.com/microsoft, https://github.com/madlag
187
+
188
+ ### Licensing Information
189
+
190
+ Computational Use of Data Agreement (C-UDA) License.
191
+
192
+ ### Citation Information
193
+
194
+ ```
195
+ @article{CodeXGLUE,
196
+ title={CodeXGLUE: A Benchmark Dataset and Open Challenge for Code Intelligence},
197
+ year={2020},}
198
+ ```
199
+
200
+ ### Contributions
201
+
202
+ Thanks to @madlag (and partly also @ncoop57) for adding this dataset.
code_x_glue_tt_text_to_text.py ADDED
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+ from typing import List
2
+
3
+ import datasets
4
+
5
+ from .common import Child
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+ from .generated_definitions import DEFINITIONS
7
+
8
+
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+ _DESCRIPTION = """The dataset we use is crawled and filtered from Microsoft Documentation, whose document located at https://github.com/MicrosoftDocs/."""
10
+ _CITATION = """@article{DBLP:journals/corr/abs-2102-04664,
11
+ author = {Shuai Lu and
12
+ Daya Guo and
13
+ Shuo Ren and
14
+ Junjie Huang and
15
+ Alexey Svyatkovskiy and
16
+ Ambrosio Blanco and
17
+ Colin B. Clement and
18
+ Dawn Drain and
19
+ Daxin Jiang and
20
+ Duyu Tang and
21
+ Ge Li and
22
+ Lidong Zhou and
23
+ Linjun Shou and
24
+ Long Zhou and
25
+ Michele Tufano and
26
+ Ming Gong and
27
+ Ming Zhou and
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+ Nan Duan and
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+ Neel Sundaresan and
30
+ Shao Kun Deng and
31
+ Shengyu Fu and
32
+ Shujie Liu},
33
+ title = {CodeXGLUE: {A} Machine Learning Benchmark Dataset for Code Understanding
34
+ and Generation},
35
+ journal = {CoRR},
36
+ volume = {abs/2102.04664},
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+ year = {2021}
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+ }"""
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+
40
+
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+ class CodeXGlueTtTextToTextImpl(Child):
42
+ _DESCRIPTION = _DESCRIPTION
43
+ _CITATION = _CITATION
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+
45
+ _FEATURES = {
46
+ "id": datasets.Value("int32"), # The index of the sample
47
+ "source": datasets.Value("string"), # The source language version of the text
48
+ "target": datasets.Value("string"), # The target language version of the text
49
+ }
50
+
51
+ _SUPERVISED_KEYS = ["target"]
52
+
53
+ KEYS = ["source", "target"]
54
+
55
+ SPLITS = {"train": datasets.Split.TRAIN, "dev": datasets.Split.VALIDATION, "test": datasets.Split.TEST}
56
+
57
+ def generate_urls(self, split_name):
58
+ lang_pair = self.info["parameters"]["natural_language_pair"]
59
+ for i, lang in enumerate(lang_pair.split("-")):
60
+ yield self.KEYS[i], f"{split_name}/{lang_pair}.{split_name}.{lang}"
61
+
62
+ def _generate_examples(self, split_name, file_paths):
63
+ print(file_paths)
64
+ # Open each file (one for source language and the other for target language)
65
+ files = {k: open(file_paths[k], encoding="utf-8") for k in file_paths}
66
+
67
+ id_ = 0
68
+ while True:
69
+ # Read a single line from each file
70
+ entries = {k: files[k].readline() for k in file_paths}
71
+
72
+ empty = self.check_empty(entries)
73
+ if empty:
74
+ # We are done: end of files
75
+ return
76
+
77
+ entries["id"] = id_
78
+ yield id_, entries
79
+ id_ += 1
80
+
81
+
82
+ CLASS_MAPPING = {
83
+ "CodeXGlueTtTextToText": CodeXGlueTtTextToTextImpl,
84
+ }
85
+
86
+
87
+ class CodeXGlueTtTextToText(datasets.GeneratorBasedBuilder):
88
+ BUILDER_CONFIG_CLASS = datasets.BuilderConfig
89
+ BUILDER_CONFIGS = [
90
+ datasets.BuilderConfig(name=name, description=info["description"]) for name, info in DEFINITIONS.items()
91
+ ]
92
+
93
+ def _info(self):
94
+ name = self.config.name
95
+ info = DEFINITIONS[name]
96
+ if info["class_name"] in CLASS_MAPPING:
97
+ self.child = CLASS_MAPPING[info["class_name"]](info)
98
+ else:
99
+ raise RuntimeError(f"Unknown python class for dataset configuration {name}")
100
+ ret = self.child._info()
101
+ return ret
102
+
103
+ def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
104
+ return self.child._split_generators(dl_manager=dl_manager)
105
+
106
+ def _generate_examples(self, split_name, file_paths):
107
+ return self.child._generate_examples(split_name, file_paths)
common.py ADDED
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1
+ from typing import List
2
+
3
+ import datasets
4
+
5
+
6
+ # Citation, taken from https://github.com/microsoft/CodeXGLUE
7
+ _DEFAULT_CITATION = """@article{CodeXGLUE,
8
+ title={CodeXGLUE: A Benchmark Dataset and Open Challenge for Code Intelligence},
9
+ year={2020},}"""
10
+
11
+
12
+ class Child:
13
+ _DESCRIPTION = None
14
+ _FEATURES = None
15
+ _CITATION = None
16
+ SPLITS = {"train": datasets.Split.TRAIN}
17
+ _SUPERVISED_KEYS = None
18
+
19
+ def __init__(self, info):
20
+ self.info = info
21
+
22
+ def homepage(self):
23
+ return self.info["project_url"]
24
+
25
+ def _info(self):
26
+ # This is the description that will appear on the datasets page.
27
+ return datasets.DatasetInfo(
28
+ description=self.info["description"] + "\n\n" + self._DESCRIPTION,
29
+ features=datasets.Features(self._FEATURES),
30
+ homepage=self.homepage(),
31
+ citation=self._CITATION or _DEFAULT_CITATION,
32
+ supervised_keys=self._SUPERVISED_KEYS,
33
+ )
34
+
35
+ def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
36
+ SPLITS = self.SPLITS
37
+ _URL = self.info["raw_url"]
38
+ urls_to_download = {}
39
+ for split in SPLITS:
40
+ if split not in urls_to_download:
41
+ urls_to_download[split] = {}
42
+
43
+ for key, url in self.generate_urls(split):
44
+ if not url.startswith("http"):
45
+ url = _URL + "/" + url
46
+ urls_to_download[split][key] = url
47
+
48
+ downloaded_files = {}
49
+ for k, v in urls_to_download.items():
50
+ downloaded_files[k] = dl_manager.download_and_extract(v)
51
+
52
+ return [
53
+ datasets.SplitGenerator(
54
+ name=SPLITS[k],
55
+ gen_kwargs={"split_name": k, "file_paths": downloaded_files[k]},
56
+ )
57
+ for k in SPLITS
58
+ ]
59
+
60
+ def check_empty(self, entries):
61
+ all_empty = all([v == "" for v in entries.values()])
62
+ all_non_empty = all([v != "" for v in entries.values()])
63
+
64
+ if not all_non_empty and not all_empty:
65
+ raise RuntimeError("Parallel data files should have the same number of lines.")
66
+
67
+ return all_empty
68
+
69
+
70
+ class TrainValidTestChild(Child):
71
+ SPLITS = {
72
+ "train": datasets.Split.TRAIN,
73
+ "valid": datasets.Split.VALIDATION,
74
+ "test": datasets.Split.TEST,
75
+ }
dataset_infos.json ADDED
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1
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