holylovenia commited on
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e4849a3
1 Parent(s): 726feea

Upload nusax_senti.py with huggingface_hub

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  1. nusax_senti.py +17 -17
nusax_senti.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 = "nusax_senti"
15
  _SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
16
- _UNIFIED_VIEW_NAME = DEFAULT_NUSANTARA_VIEW_NAME
17
 
18
  _LANGUAGES = ["ind", "ace", "ban", "bjn", "bbc", "bug", "jav", "mad", "min", "nij", "sun", "eng"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
19
 
@@ -46,7 +46,7 @@ _SUPPORTED_TASKS = [Tasks.SENTIMENT_ANALYSIS]
46
 
47
  _SOURCE_VERSION = "1.0.0"
48
 
49
- _NUSANTARA_VERSION = "1.0.0"
50
 
51
  _URLS = {
52
  "train": "https://raw.githubusercontent.com/IndoNLP/nusax/main/datasets/sentiment/{lang}/train.csv",
@@ -55,13 +55,13 @@ _URLS = {
55
  }
56
 
57
 
58
- def nusantara_config_constructor(lang, schema, version):
59
- """Construct NusantaraConfig with nusax_senti_{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="nusax_senti_{schema}".format(schema=schema),
66
  version=datasets.Version(version),
67
  description="nusax_senti with {schema} schema for all 12 languages".format(schema=schema),
@@ -69,7 +69,7 @@ def nusantara_config_constructor(lang, schema, version):
69
  subset_id="nusax_senti",
70
  )
71
  else:
72
- return NusantaraConfig(
73
  name="nusax_senti_{lang}_{schema}".format(lang=lang, schema=schema),
74
  version=datasets.Version(version),
75
  description="nusax_senti with {schema} schema for {lang} language".format(lang=lang, schema=schema),
@@ -98,9 +98,9 @@ class NusaXSenti(datasets.GeneratorBasedBuilder):
98
  """NusaX-Senti is a 3-labels (positive, neutral, negative) sentiment analysis dataset for 10 Indonesian local languages + Indonesian and English."""
99
 
100
  BUILDER_CONFIGS = (
101
- [nusantara_config_constructor(lang, "source", _SOURCE_VERSION) for lang in LANGUAGES_MAP]
102
- + [nusantara_config_constructor(lang, "nusantara_text", _NUSANTARA_VERSION) for lang in LANGUAGES_MAP]
103
- + [nusantara_config_constructor("", "source", _SOURCE_VERSION), nusantara_config_constructor("", "nusantara_text", _NUSANTARA_VERSION)]
104
  )
105
 
106
  DEFAULT_CONFIG_NAME = "nusax_senti_ind_source"
@@ -114,7 +114,7 @@ class NusaXSenti(datasets.GeneratorBasedBuilder):
114
  "label": datasets.Value("string"),
115
  }
116
  )
117
- elif self.config.schema == "nusantara_text":
118
  features = schemas.text_features(["negative", "neutral", "positive"])
119
 
120
  return datasets.DatasetInfo(
@@ -127,7 +127,7 @@ class NusaXSenti(datasets.GeneratorBasedBuilder):
127
 
128
  def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
129
  """Returns SplitGenerators."""
130
- if self.config.name == "nusax_senti_source" or self.config.name == "nusax_senti_nusantara_text":
131
  # Load all 12 languages
132
  train_csv_path = dl_manager.download_and_extract([_URLS["train"].format(lang=LANGUAGES_MAP[lang]) for lang in LANGUAGES_MAP])
133
  validation_csv_path = dl_manager.download_and_extract([_URLS["validation"].format(lang=LANGUAGES_MAP[lang]) for lang in LANGUAGES_MAP])
@@ -154,10 +154,10 @@ class NusaXSenti(datasets.GeneratorBasedBuilder):
154
  ]
155
 
156
  def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]:
157
- if self.config.schema != "source" and self.config.schema != "nusantara_text":
158
  raise ValueError(f"Invalid config: {self.config.name}")
159
 
160
- if self.config.name == "nusax_senti_source" or self.config.name == "nusax_senti_nusantara_text":
161
  ldf = []
162
  for fp in filepath:
163
  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 = "nusax_senti"
15
  _SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
16
+ _UNIFIED_VIEW_NAME = DEFAULT_SEACROWD_VIEW_NAME
17
 
18
  _LANGUAGES = ["ind", "ace", "ban", "bjn", "bbc", "bug", "jav", "mad", "min", "nij", "sun", "eng"] # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
19
 
 
46
 
47
  _SOURCE_VERSION = "1.0.0"
48
 
49
+ _SEACROWD_VERSION = "2024.06.20"
50
 
51
  _URLS = {
52
  "train": "https://raw.githubusercontent.com/IndoNLP/nusax/main/datasets/sentiment/{lang}/train.csv",
 
55
  }
56
 
57
 
58
+ def seacrowd_config_constructor(lang, schema, version):
59
+ """Construct SEACrowdConfig with nusax_senti_{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="nusax_senti_{schema}".format(schema=schema),
66
  version=datasets.Version(version),
67
  description="nusax_senti with {schema} schema for all 12 languages".format(schema=schema),
 
69
  subset_id="nusax_senti",
70
  )
71
  else:
72
+ return SEACrowdConfig(
73
  name="nusax_senti_{lang}_{schema}".format(lang=lang, schema=schema),
74
  version=datasets.Version(version),
75
  description="nusax_senti with {schema} schema for {lang} language".format(lang=lang, schema=schema),
 
98
  """NusaX-Senti is a 3-labels (positive, neutral, negative) sentiment analysis dataset for 10 Indonesian local languages + Indonesian and English."""
99
 
100
  BUILDER_CONFIGS = (
101
+ [seacrowd_config_constructor(lang, "source", _SOURCE_VERSION) for lang in LANGUAGES_MAP]
102
+ + [seacrowd_config_constructor(lang, "seacrowd_text", _SEACROWD_VERSION) for lang in LANGUAGES_MAP]
103
+ + [seacrowd_config_constructor("", "source", _SOURCE_VERSION), seacrowd_config_constructor("", "seacrowd_text", _SEACROWD_VERSION)]
104
  )
105
 
106
  DEFAULT_CONFIG_NAME = "nusax_senti_ind_source"
 
114
  "label": datasets.Value("string"),
115
  }
116
  )
117
+ elif self.config.schema == "seacrowd_text":
118
  features = schemas.text_features(["negative", "neutral", "positive"])
119
 
120
  return datasets.DatasetInfo(
 
127
 
128
  def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
129
  """Returns SplitGenerators."""
130
+ if self.config.name == "nusax_senti_source" or self.config.name == "nusax_senti_seacrowd_text":
131
  # Load all 12 languages
132
  train_csv_path = dl_manager.download_and_extract([_URLS["train"].format(lang=LANGUAGES_MAP[lang]) for lang in LANGUAGES_MAP])
133
  validation_csv_path = dl_manager.download_and_extract([_URLS["validation"].format(lang=LANGUAGES_MAP[lang]) for lang in LANGUAGES_MAP])
 
154
  ]
155
 
156
  def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]:
157
+ if self.config.schema != "source" and self.config.schema != "seacrowd_text":
158
  raise ValueError(f"Invalid config: {self.config.name}")
159
 
160
+ if self.config.name == "nusax_senti_source" or self.config.name == "nusax_senti_seacrowd_text":
161
  ldf = []
162
  for fp in filepath:
163
  ldf.append(pd.read_csv(fp))