Upload nusatranslation_emot.py with huggingface_hub

nusatranslation_emot.py

@@ -4,15 +4,15 @@ 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, DEFAULT_SOURCE_VIEW_NAME, Tasks
+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 = "nusatranslation_emot"
 _SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
-_UNIFIED_VIEW_NAME = DEFAULT_NUSANTARA_VIEW_NAME
+_UNIFIED_VIEW_NAME = DEFAULT_SEACROWD_VIEW_NAME
 
 _LANGUAGES = ["abs", "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)
 
@@ -40,7 +40,7 @@ _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_kalimat-emot-{lang}-train.csv",
@@ -49,13 +49,13 @@ _URLS = {
 }
 
 
-def nusantara_config_constructor(lang, schema, version):
-    """Construct NusantaraConfig with nusatranslation_emot_{lang}_{schema} as the name format"""
-    if schema != "source" and schema != "nusantara_text":
+def seacrowd_config_constructor(lang, schema, version):
+    """Construct SEACrowdConfig with nusatranslation_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="nusatranslation_emot_{schema}".format(schema=schema),
             version=datasets.Version(version),
             description="nusatranslation_emot with {schema} schema for all 12 languages".format(schema=schema),
@@ -63,7 +63,7 @@ def nusantara_config_constructor(lang, schema, version):
             subset_id="nusatranslation_emot",
         )
     else:
-        return NusantaraConfig(
+        return SEACrowdConfig(
             name="nusatranslation_emot_{lang}_{schema}".format(lang=lang, schema=schema),
             version=datasets.Version(version),
             description="nusatranslation_emot with {schema} schema for {lang} language".format(lang=lang, schema=schema),
@@ -91,9 +91,9 @@ class NusaTranslationEmot(datasets.GeneratorBasedBuilder):
     """NusaTranslationEmot is a 5-labels (fear, sadness, happy, anger, love) emotion classification dataset for 11 Indonesian local languages + Indonesian and English."""
 
     BUILDER_CONFIGS = (
-        [nusantara_config_constructor(lang, "source", _SOURCE_VERSION) for lang in LANGUAGES_MAP]
-        + [nusantara_config_constructor(lang, "nusantara_text", _NUSANTARA_VERSION) for lang in LANGUAGES_MAP]
-        + [nusantara_config_constructor("", "source", _SOURCE_VERSION), nusantara_config_constructor("", "nusantara_text", _NUSANTARA_VERSION)]
+        [seacrowd_config_constructor(lang, "source", _SOURCE_VERSION) for lang in LANGUAGES_MAP]
+        + [seacrowd_config_constructor(lang, "seacrowd_text", _SEACROWD_VERSION) for lang in LANGUAGES_MAP]
+        + [seacrowd_config_constructor("", "source", _SOURCE_VERSION), seacrowd_config_constructor("", "seacrowd_text", _SEACROWD_VERSION)]
     )
 
     DEFAULT_CONFIG_NAME = "nusatranslation_emot_source"
@@ -107,7 +107,7 @@ class NusaTranslationEmot(datasets.GeneratorBasedBuilder):
                     "label": datasets.Value("string"),
                 }
             )
-        elif self.config.schema == "nusantara_text":
+        elif self.config.schema == "seacrowd_text":
             features = schemas.text_features(["fear", "sadness", "happy", "anger", "love"])
 
         return datasets.DatasetInfo(
@@ -120,7 +120,7 @@ class NusaTranslationEmot(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
         """Returns SplitGenerators."""
-        if self.config.name == "nusatranslation_emot_source" or self.config.name == "nusatranslation_emot_nusantara_text":
+        if self.config.name == "nusatranslation_emot_source" or self.config.name == "nusatranslation_emot_seacrowd_text":
             # Load all 12 languages
             train_csv_path = dl_manager.download_and_extract([_URLS["train"].format(lang=lang) for lang in LANGUAGES_MAP])
             validation_csv_path = dl_manager.download_and_extract([_URLS["validation"].format(lang=lang) for lang in LANGUAGES_MAP])
@@ -147,10 +147,10 @@ class NusaTranslationEmot(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 == "nusatranslation_emot_source" or self.config.name == "nusatranslation_emot_nusantara_text":
+        if self.config.name == "nusatranslation_emot_source" or self.config.name == "nusatranslation_emot_seacrowd_text":
             ldf = []
             for fp in filepath:
                 ldf.append(pd.read_csv(fp))