Upload emotions_dataset.py

emotions_dataset.py

@@ -0,0 +1,53 @@
+from typing import List
+
+import datasets
+import pandas as pd
+from datasets import ClassLabel, Value
+
+_URLS = [
+    "https://storage.googleapis.com/gresearch/goemotions/data/full_dataset/goemotions_1.csv",
+    "https://storage.googleapis.com/gresearch/goemotions/data/full_dataset/goemotions_2.csv",
+    "https://storage.googleapis.com/gresearch/goemotions/data/full_dataset/goemotions_3.csv",
+]
+
+
+class EmotionsDatasetConfig(datasets.BuilderConfig):
+
+    def __init__(self, features, label_classes, **kwargs):
+        super().__init__(**kwargs)
+        self.features = features
+        self.label_classes = label_classes
+
+
+class EmotionsDataset(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        EmotionsDatasetConfig(
+            name="all",
+            label_classes=["anger", "joy", "sadness"],
+            features=["text", "label", "dataset"]
+        )
+    ]
+
+    DEFAULT_CONFIG_NAME = "all"
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    'label': ClassLabel(names=["joy", "anger", "sadness"], id=None),
+                    'text': Value(dtype='string', id=None),
+                    'dataset': Value(dtype='string', id=None)
+                }
+            )
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        downloaded_files = dl_manager.download_and_extract(_URLS)
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": downloaded_files})]
+
+    def _generate_examples(self, filepaths):
+        for i, filepath in enumerate(filepaths):
+            df = pd.read_csv(filepath)
+            for row_idx, row in enumerate(df.iterrows()):
+                yield f"{i}_{row_idx}", row