holylovenia commited on
Commit
8606638
1 Parent(s): 7aa7386

Upload nusaparagraph_topic.py with huggingface_hub

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Files changed (1) hide show
  1. nusaparagraph_topic.py +19 -19
nusaparagraph_topic.py CHANGED
@@ -4,16 +4,16 @@ from typing import Dict, List, Tuple
4
  import datasets
5
  import pandas as pd
6
 
7
- from nusacrowd.utils import schemas
8
- from nusacrowd.utils.configs import NusantaraConfig
9
- from nusacrowd.utils.constants import (DEFAULT_NUSANTARA_VIEW_NAME,
10
  DEFAULT_SOURCE_VIEW_NAME, Tasks)
11
 
12
  _LOCAL = False
13
 
14
  _DATASETNAME = "nusaparagraph_topic"
15
  _SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
16
- _UNIFIED_VIEW_NAME = DEFAULT_NUSANTARA_VIEW_NAME
17
 
18
  _LANGUAGES = [
19
  "btk", "bew", "bug", "jav", "mad", "mak", "min", "mui", "rej", "sun"
@@ -43,7 +43,7 @@ _SUPPORTED_TASKS = [Tasks.TOPIC_MODELING]
43
 
44
  _SOURCE_VERSION = "1.0.0"
45
 
46
- _NUSANTARA_VERSION = "1.0.0"
47
 
48
  _URLS = {
49
  "train":
@@ -55,13 +55,13 @@ _URLS = {
55
  }
56
 
57
 
58
- def nusantara_config_constructor(lang, schema, version):
59
- """Construct NusantaraConfig with nusaparagraph_topic_{lang}_{schema} as the name format"""
60
- if schema != "source" and schema != "nusantara_text":
61
  raise ValueError(f"Invalid schema: {schema}")
62
 
63
  if lang == "":
64
- return NusantaraConfig(
65
  name="nusaparagraph_topic_{schema}".format(schema=schema),
66
  version=datasets.Version(version),
67
  description=
@@ -71,7 +71,7 @@ def nusantara_config_constructor(lang, schema, version):
71
  subset_id="nusaparagraph_topic",
72
  )
73
  else:
74
- return NusantaraConfig(
75
  name="nusaparagraph_topic_{lang}_{schema}".format(lang=lang,
76
  schema=schema),
77
  version=datasets.Version(version),
@@ -101,15 +101,15 @@ class NusaParagraphTopic(datasets.GeneratorBasedBuilder):
101
  """NusaParagraph-Topic is a 8-labels (food & beverages, sports, leisure, religion, culture & heritage, a slice of life, technology, and business) topic modeling dataset for 10 Indonesian local languages."""
102
 
103
  BUILDER_CONFIGS = ([
104
- nusantara_config_constructor(lang, "source", _SOURCE_VERSION)
105
  for lang in LANGUAGES_MAP
106
  ] + [
107
- nusantara_config_constructor(lang, "nusantara_text",
108
- _NUSANTARA_VERSION)
109
  for lang in LANGUAGES_MAP
110
  ] + [
111
- nusantara_config_constructor("", "source", _SOURCE_VERSION),
112
- nusantara_config_constructor("", "nusantara_text", _NUSANTARA_VERSION)
113
  ])
114
 
115
  DEFAULT_CONFIG_NAME = "nusaparagraph_topic_ind_source"
@@ -121,7 +121,7 @@ class NusaParagraphTopic(datasets.GeneratorBasedBuilder):
121
  "text": datasets.Value("string"),
122
  "label": datasets.Value("string"),
123
  })
124
- elif self.config.schema == "nusantara_text":
125
  features = schemas.text_features([
126
  "food & beverages", "sports", "leisures", "religion", "culture & heritage", "slice of life", "technology", "business"
127
  ])
@@ -138,7 +138,7 @@ class NusaParagraphTopic(datasets.GeneratorBasedBuilder):
138
  self, dl_manager: datasets.DownloadManager
139
  ) -> List[datasets.SplitGenerator]:
140
  """Returns SplitGenerators."""
141
- if self.config.name == "nusaparagraph_topic_source" or self.config.name == "nusaparagraph_topic_nusantara_text":
142
  # Load all 12 languages
143
  train_csv_path = dl_manager.download_and_extract([
144
  _URLS["train"].format(lang=lang)
@@ -180,10 +180,10 @@ class NusaParagraphTopic(datasets.GeneratorBasedBuilder):
180
  ]
181
 
182
  def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]:
183
- if self.config.schema != "source" and self.config.schema != "nusantara_text":
184
  raise ValueError(f"Invalid config: {self.config.name}")
185
 
186
- if self.config.name == "nusaparagraph_topic_source" or self.config.name == "nusaparagraph_topic_nusantara_text":
187
  ldf = []
188
  for fp in filepath:
189
  ldf.append(pd.read_csv(fp))
 
4
  import datasets
5
  import pandas as pd
6
 
7
+ from seacrowd.utils import schemas
8
+ from seacrowd.utils.configs import SEACrowdConfig
9
+ from seacrowd.utils.constants import (DEFAULT_SEACROWD_VIEW_NAME,
10
  DEFAULT_SOURCE_VIEW_NAME, Tasks)
11
 
12
  _LOCAL = False
13
 
14
  _DATASETNAME = "nusaparagraph_topic"
15
  _SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
16
+ _UNIFIED_VIEW_NAME = DEFAULT_SEACROWD_VIEW_NAME
17
 
18
  _LANGUAGES = [
19
  "btk", "bew", "bug", "jav", "mad", "mak", "min", "mui", "rej", "sun"
 
43
 
44
  _SOURCE_VERSION = "1.0.0"
45
 
46
+ _SEACROWD_VERSION = "2024.06.20"
47
 
48
  _URLS = {
49
  "train":
 
55
  }
56
 
57
 
58
+ def seacrowd_config_constructor(lang, schema, version):
59
+ """Construct SEACrowdConfig with nusaparagraph_topic_{lang}_{schema} as the name format"""
60
+ if schema != "source" and schema != "seacrowd_text":
61
  raise ValueError(f"Invalid schema: {schema}")
62
 
63
  if lang == "":
64
+ return SEACrowdConfig(
65
  name="nusaparagraph_topic_{schema}".format(schema=schema),
66
  version=datasets.Version(version),
67
  description=
 
71
  subset_id="nusaparagraph_topic",
72
  )
73
  else:
74
+ return SEACrowdConfig(
75
  name="nusaparagraph_topic_{lang}_{schema}".format(lang=lang,
76
  schema=schema),
77
  version=datasets.Version(version),
 
101
  """NusaParagraph-Topic is a 8-labels (food & beverages, sports, leisure, religion, culture & heritage, a slice of life, technology, and business) topic modeling dataset for 10 Indonesian local languages."""
102
 
103
  BUILDER_CONFIGS = ([
104
+ seacrowd_config_constructor(lang, "source", _SOURCE_VERSION)
105
  for lang in LANGUAGES_MAP
106
  ] + [
107
+ seacrowd_config_constructor(lang, "seacrowd_text",
108
+ _SEACROWD_VERSION)
109
  for lang in LANGUAGES_MAP
110
  ] + [
111
+ seacrowd_config_constructor("", "source", _SOURCE_VERSION),
112
+ seacrowd_config_constructor("", "seacrowd_text", _SEACROWD_VERSION)
113
  ])
114
 
115
  DEFAULT_CONFIG_NAME = "nusaparagraph_topic_ind_source"
 
121
  "text": datasets.Value("string"),
122
  "label": datasets.Value("string"),
123
  })
124
+ elif self.config.schema == "seacrowd_text":
125
  features = schemas.text_features([
126
  "food & beverages", "sports", "leisures", "religion", "culture & heritage", "slice of life", "technology", "business"
127
  ])
 
138
  self, dl_manager: datasets.DownloadManager
139
  ) -> List[datasets.SplitGenerator]:
140
  """Returns SplitGenerators."""
141
+ if self.config.name == "nusaparagraph_topic_source" or self.config.name == "nusaparagraph_topic_seacrowd_text":
142
  # Load all 12 languages
143
  train_csv_path = dl_manager.download_and_extract([
144
  _URLS["train"].format(lang=lang)
 
180
  ]
181
 
182
  def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]:
183
+ if self.config.schema != "source" and self.config.schema != "seacrowd_text":
184
  raise ValueError(f"Invalid config: {self.config.name}")
185
 
186
+ if self.config.name == "nusaparagraph_topic_source" or self.config.name == "nusaparagraph_topic_seacrowd_text":
187
  ldf = []
188
  for fp in filepath:
189
  ldf.append(pd.read_csv(fp))