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  1. .gitattributes +0 -37
  2. amazon-massive-dataset-1.0.tar.gz → af/amazon_massive_scenario-test.parquet +2 -2
  3. af/amazon_massive_scenario-train.parquet +3 -0
  4. af/amazon_massive_scenario-validation.parquet +3 -0
  5. am/amazon_massive_scenario-test.parquet +3 -0
  6. am/amazon_massive_scenario-train.parquet +3 -0
  7. am/amazon_massive_scenario-validation.parquet +3 -0
  8. amazon_massive_scenario.py +0 -176
  9. ar/amazon_massive_scenario-test.parquet +3 -0
  10. ar/amazon_massive_scenario-train.parquet +3 -0
  11. ar/amazon_massive_scenario-validation.parquet +3 -0
  12. az/amazon_massive_scenario-test.parquet +3 -0
  13. az/amazon_massive_scenario-train.parquet +3 -0
  14. az/amazon_massive_scenario-validation.parquet +3 -0
  15. bn/amazon_massive_scenario-test.parquet +3 -0
  16. bn/amazon_massive_scenario-train.parquet +3 -0
  17. bn/amazon_massive_scenario-validation.parquet +3 -0
  18. cy/amazon_massive_scenario-test.parquet +3 -0
  19. cy/amazon_massive_scenario-train.parquet +3 -0
  20. cy/amazon_massive_scenario-validation.parquet +3 -0
  21. da/amazon_massive_scenario-test.parquet +3 -0
  22. da/amazon_massive_scenario-train.parquet +3 -0
  23. da/amazon_massive_scenario-validation.parquet +3 -0
  24. de/amazon_massive_scenario-test.parquet +3 -0
  25. de/amazon_massive_scenario-train.parquet +3 -0
  26. de/amazon_massive_scenario-validation.parquet +3 -0
  27. el/amazon_massive_scenario-test.parquet +3 -0
  28. el/amazon_massive_scenario-train.parquet +3 -0
  29. el/amazon_massive_scenario-validation.parquet +3 -0
  30. en/amazon_massive_scenario-test.parquet +3 -0
  31. en/amazon_massive_scenario-train.parquet +3 -0
  32. en/amazon_massive_scenario-validation.parquet +3 -0
  33. es/amazon_massive_scenario-test.parquet +3 -0
  34. es/amazon_massive_scenario-train.parquet +3 -0
  35. es/amazon_massive_scenario-validation.parquet +3 -0
  36. fa/amazon_massive_scenario-test.parquet +3 -0
  37. fa/amazon_massive_scenario-train.parquet +3 -0
  38. fa/amazon_massive_scenario-validation.parquet +3 -0
  39. fi/amazon_massive_scenario-test.parquet +3 -0
  40. fi/amazon_massive_scenario-train.parquet +3 -0
  41. fi/amazon_massive_scenario-validation.parquet +3 -0
  42. fr/amazon_massive_scenario-test.parquet +3 -0
  43. fr/amazon_massive_scenario-train.parquet +3 -0
  44. fr/amazon_massive_scenario-validation.parquet +3 -0
  45. he/amazon_massive_scenario-test.parquet +3 -0
  46. he/amazon_massive_scenario-train.parquet +3 -0
  47. he/amazon_massive_scenario-validation.parquet +3 -0
  48. hi/amazon_massive_scenario-test.parquet +3 -0
  49. hi/amazon_massive_scenario-train.parquet +3 -0
  50. hi/amazon_massive_scenario-validation.parquet +3 -0
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amazon_massive_scenario.py DELETED
@@ -1,176 +0,0 @@
1
- # coding=utf-8
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-
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- """MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages"""
4
-
5
- import json
6
- import datasets
7
-
8
- logger = datasets.logging.get_logger(__name__)
9
-
10
- _DESCRIPTION = """\
11
- MASSIVE is a parallel dataset of > 1M utterances across 51 languages with annotations
12
- for the Natural Language Understanding tasks of intent prediction and slot annotation.
13
- Utterances span 60 intents and include 55 slot types. MASSIVE was created by localizing
14
- the SLURP dataset, composed of general Intelligent Voice Assistant single-shot interactions.
15
- """
16
- _URL = "amazon-massive-dataset-1.0.tar.gz"
17
-
18
-
19
- _LANGUAGES = {
20
- "af": "af-ZA",
21
- "am": "am-ET",
22
- "ar": "ar-SA",
23
- "az": "az-AZ",
24
- "bn": "bn-BD",
25
- "cy": "cy-GB",
26
- "da": "da-DK",
27
- "de": "de-DE",
28
- "el": "el-GR",
29
- "en": "en-US",
30
- "es": "es-ES",
31
- "fa": "fa-IR",
32
- "fi": "fi-FI",
33
- "fr": "fr-FR",
34
- "he": "he-IL",
35
- "hi": "hi-IN",
36
- "hu": "hu-HU",
37
- "hy": "hy-AM",
38
- "id": "id-ID",
39
- "is": "is-IS",
40
- "it": "it-IT",
41
- "ja": "ja-JP",
42
- "jv": "jv-ID",
43
- "ka": "ka-GE",
44
- "km": "km-KH",
45
- "kn": "kn-IN",
46
- "ko": "ko-KR",
47
- "lv": "lv-LV",
48
- "ml": "ml-IN",
49
- "mn": "mn-MN",
50
- "ms": "ms-MY",
51
- "my": "my-MM",
52
- "nb": "nb-NO",
53
- "nl": "nl-NL",
54
- "pl": "pl-PL",
55
- "pt": "pt-PT",
56
- "ro": "ro-RO",
57
- "ru": "ru-RU",
58
- "sl": "sl-SL",
59
- "sq": "sq-AL",
60
- "sv": "sv-SE",
61
- "sw": "sw-KE",
62
- "ta": "ta-IN",
63
- "te": "te-IN",
64
- "th": "th-TH",
65
- "tl": "tl-PH",
66
- "tr": "tr-TR",
67
- "ur": "ur-PK",
68
- "vi": "vi-VN",
69
- "zh-CN": "zh-CN",
70
- "zh-TW": "zh-TW",
71
- }
72
-
73
- _SCENARIOS = [
74
- "social",
75
- "transport",
76
- "calendar",
77
- "play",
78
- "news",
79
- "datetime",
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- "recommendation",
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- "email",
82
- "iot",
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- "general",
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- "audio",
85
- "lists",
86
- "qa",
87
- "cooking",
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- "takeaway",
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- "music",
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- "alarm",
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- "weather",
92
- ]
93
-
94
-
95
- class MASSIVE(datasets.GeneratorBasedBuilder):
96
- """MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages"""
97
-
98
- BUILDER_CONFIGS = [
99
- datasets.BuilderConfig(
100
- name=name,
101
- version=datasets.Version("1.0.0"),
102
- description=f"The MASSIVE corpora for {name}",
103
- )
104
- for name in _LANGUAGES.keys()
105
- ]
106
-
107
- DEFAULT_CONFIG_NAME = "en"
108
-
109
- def _info(self):
110
- return datasets.DatasetInfo(
111
- description=_DESCRIPTION,
112
- features=datasets.Features(
113
- {
114
- "id": datasets.Value("string"),
115
- "label": datasets.features.ClassLabel(names=_SCENARIOS),
116
- "label_text": datasets.Value("string"),
117
- "text": datasets.Value("string"),
118
- },
119
- ),
120
- supervised_keys=None,
121
- homepage="https://github.com/alexa/massive",
122
- citation="_CITATION",
123
- license="_LICENSE",
124
- )
125
-
126
- def _split_generators(self, dl_manager):
127
-
128
- # path = dl_manager.download_and_extract(_URL)
129
- archive_path = dl_manager.download(_URL)
130
- files = dl_manager.iter_archive(archive_path)
131
-
132
- return [
133
- datasets.SplitGenerator(
134
- name=datasets.Split.TRAIN,
135
- gen_kwargs={
136
- "files": files,
137
- "split": "train",
138
- "lang": self.config.name,
139
- },
140
- ),
141
- datasets.SplitGenerator(
142
- name=datasets.Split.VALIDATION,
143
- gen_kwargs={
144
- "files": files,
145
- "split": "dev",
146
- "lang": self.config.name,
147
- },
148
- ),
149
- datasets.SplitGenerator(
150
- name=datasets.Split.TEST,
151
- gen_kwargs={
152
- "files": files,
153
- "split": "test",
154
- "lang": self.config.name,
155
- },
156
- ),
157
- ]
158
-
159
- def _generate_examples(self, files, split, lang):
160
- filepath = "1.0/data/" + _LANGUAGES[lang] + ".jsonl"
161
- logger.info("⏳ Generating examples from = %s", filepath)
162
- for path, f in files:
163
- if path == filepath:
164
- lines = f.readlines()
165
- key_ = 0
166
- for line in lines:
167
- data = json.loads(line)
168
- if data["partition"] != split:
169
- continue
170
- yield key_, {
171
- "id": data["id"],
172
- "label": data["scenario"],
173
- "label_text": data["scenario"],
174
- "text": data["utt"],
175
- }
176
- key_ += 1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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