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nusaparagraph_emot.py

@@ -2,14 +2,14 @@ from pathlib import Path
 from typing import Dict, List, Tuple
 import datasets
 import pandas as pd
-from nusacrowd.utils import schemas
-from nusacrowd.utils.configs import NusantaraConfig
-from nusacrowd.utils.constants import (DEFAULT_NUSANTARA_VIEW_NAME,
+from seacrowd.utils import schemas
+from seacrowd.utils.configs import SEACrowdConfig
+from seacrowd.utils.constants import (DEFAULT_SEACROWD_VIEW_NAME,
                                        DEFAULT_SOURCE_VIEW_NAME, Tasks)
 _LOCAL = False
 _DATASETNAME = "nusaparagraph_emot"
 _SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
-_UNIFIED_VIEW_NAME = DEFAULT_NUSANTARA_VIEW_NAME
+_UNIFIED_VIEW_NAME = DEFAULT_SEACROWD_VIEW_NAME
 _LANGUAGES = [
     "btk", "bew", "bug", "jav", "mad", "mak", "min", "mui", "rej", "sun"
 ]  # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
@@ -31,7 +31,7 @@ _HOMEPAGE = "https://github.com/IndoNLP/nusa-writes"
 _LICENSE = "Creative Commons Attribution Share-Alike 4.0 International"
 _SUPPORTED_TASKS = [Tasks.EMOTION_CLASSIFICATION]
 _SOURCE_VERSION = "1.0.0"
-_NUSANTARA_VERSION = "1.0.0"
+_SEACROWD_VERSION = "2024.06.20"
 _URLS = {
     "train":
     "https://raw.githubusercontent.com/IndoNLP/nusa-writes/main/data/nusa_alinea-emot-{lang}-train.csv",
@@ -40,12 +40,12 @@ _URLS = {
     "test":
     "https://raw.githubusercontent.com/IndoNLP/nusa-writes/main/data/nusa_alinea-emot-{lang}-test.csv",
 }
-def nusantara_config_constructor(lang, schema, version):
-    """Construct NusantaraConfig with nusaparagraph_emot_{lang}_{schema} as the name format"""
-    if schema != "source" and schema != "nusantara_text":
+def seacrowd_config_constructor(lang, schema, version):
+    """Construct SEACrowdConfig with nusaparagraph_emot_{lang}_{schema} as the name format"""
+    if schema != "source" and schema != "seacrowd_text":
         raise ValueError(f"Invalid schema: {schema}")
     if lang == "":
-        return NusantaraConfig(
+        return SEACrowdConfig(
             name="nusaparagraph_emot_{schema}".format(schema=schema),
             version=datasets.Version(version),
             description=
@@ -55,7 +55,7 @@ def nusantara_config_constructor(lang, schema, version):
             subset_id="nusaparagraph_emot",
         )
     else:
-        return NusantaraConfig(
+        return SEACrowdConfig(
             name="nusaparagraph_emot_{lang}_{schema}".format(lang=lang,
                                                              schema=schema),
             version=datasets.Version(version),
@@ -80,15 +80,15 @@ LANGUAGES_MAP = {
 class NusaParagraphEmot(datasets.GeneratorBasedBuilder):
     """NusaParagraph-Emot is a 7-labels (fear, disgusted, sad, happy, angry, surprise, and shame) emotion classification dataset for 10 Indonesian local languages."""
     BUILDER_CONFIGS = ([
-        nusantara_config_constructor(lang, "source", _SOURCE_VERSION)
+        seacrowd_config_constructor(lang, "source", _SOURCE_VERSION)
         for lang in LANGUAGES_MAP
     ] + [
-        nusantara_config_constructor(lang, "nusantara_text",
-                                     _NUSANTARA_VERSION)
+        seacrowd_config_constructor(lang, "seacrowd_text",
+                                     _SEACROWD_VERSION)
         for lang in LANGUAGES_MAP
     ] + [
-        nusantara_config_constructor("", "source", _SOURCE_VERSION),
-        nusantara_config_constructor("", "nusantara_text", _NUSANTARA_VERSION)
+        seacrowd_config_constructor("", "source", _SOURCE_VERSION),
+        seacrowd_config_constructor("", "seacrowd_text", _SEACROWD_VERSION)
     ])
     DEFAULT_CONFIG_NAME = "nusaparagraph_emot_ind_source"
     def _info(self) -> datasets.DatasetInfo:
@@ -98,7 +98,7 @@ class NusaParagraphEmot(datasets.GeneratorBasedBuilder):
                 "text": datasets.Value("string"),
                 "label": datasets.Value("string"),
             })
-        elif self.config.schema == "nusantara_text":
+        elif self.config.schema == "seacrowd_text":
             features = schemas.text_features([
                 "fear", "disgusted", "sad", "happy", "angry", "surprise",
                 "shame"
@@ -114,7 +114,7 @@ class NusaParagraphEmot(datasets.GeneratorBasedBuilder):
             self, dl_manager: datasets.DownloadManager
     ) -> List[datasets.SplitGenerator]:
         """Returns SplitGenerators."""
-        if self.config.name == "nusaparagraph_emot_source" or self.config.name == "nusaparagraph_emot_nusantara_text":
+        if self.config.name == "nusaparagraph_emot_source" or self.config.name == "nusaparagraph_emot_seacrowd_text":
             # Load all 12 languages
             train_csv_path = dl_manager.download_and_extract([
                 _URLS["train"].format(lang=lang)
@@ -154,9 +154,9 @@ class NusaParagraphEmot(datasets.GeneratorBasedBuilder):
             ),
         ]
     def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]:
-        if self.config.schema != "source" and self.config.schema != "nusantara_text":
+        if self.config.schema != "source" and self.config.schema != "seacrowd_text":
             raise ValueError(f"Invalid config: {self.config.name}")
-        if self.config.name == "nusaparagraph_emot_source" or self.config.name == "nusaparagraph_emot_nusantara_text":
+        if self.config.name == "nusaparagraph_emot_source" or self.config.name == "nusaparagraph_emot_seacrowd_text":
             ldf = []
             for fp in filepath:
                 ldf.append(pd.read_csv(fp))
@@ -167,4 +167,4 @@ class NusaParagraphEmot(datasets.GeneratorBasedBuilder):
             df = pd.read_csv(filepath).reset_index()
         for row in df.itertuples():
             ex = {"id": str(row.id), "text": row.text, "label": row.label}
-            yield row.id, ex
+            yield row.id, ex