Upload emotions_dataset.py

emotions_dataset.py

@@ -3,22 +3,22 @@ from typing import List
 
 import datasets
 import pandas as pd
-from datasets import ClassLabel, Value
+from datasets import ClassLabel, Value, load_dataset
 
-DATASETS_URLS = [{
-    "name": "go_emotions",
-    "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",
-    ],
-    "license": "apache license 2.0"},
-    {
-        "name": "daily_dialog",
+_URLS = {
+    "go_emotions": {
+        "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",
+        ],
+        "license": "apache license 2.0"
+    },
+    "daily_dialog": {
         "urls": ["http://yanran.li/files/ijcnlp_dailydialog.zip"],
         "license": "CC BY-NC-SA 4.0"
     }
-]
+}
 
 _CLASS_NAMES = [
     "no emotion",
@@ -68,6 +68,16 @@ class EmotionsDataset(datasets.GeneratorBasedBuilder):
             name="all",
             label_classes=_CLASS_NAMES,
             features=["text", "label", "dataset", "license"]
+        ),
+        EmotionsDatasetConfig(
+            name="go_emotions",
+            label_classes=_CLASS_NAMES,
+            features=["text", "label", "dataset", "license"]
+        ),
+        EmotionsDatasetConfig(
+            name="daily_dialog",
+            label_classes=_CLASS_NAMES,
+            features=["text", "label", "dataset", "license"]
         )
     ]
 
@@ -88,12 +98,21 @@ class EmotionsDataset(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
         splits = []
-        for d in DATASETS_URLS:
-            downloaded_files = dl_manager.download_and_extract(d.get("urls"))
-            splits.append(datasets.SplitGenerator(name=d.get("name"),
+        if self.config.name == "all":
+            for k, v in _URLS.items():
+                downloaded_files = dl_manager.download_and_extract(v.get("urls"))
+                splits.append(datasets.SplitGenerator(name=k,
+                                                      gen_kwargs={"filepaths": downloaded_files,
+                                                                  "dataset": k,
+                                                                  "license": v}))
+        else:
+            k = self.config.name
+            v = _URLS.get(k)
+            downloaded_files = dl_manager.download_and_extract(v.get("urls"))
+            splits.append(datasets.SplitGenerator(name=k,
                                                   gen_kwargs={"filepaths": downloaded_files,
-                                                              "dataset": d.get("name"),
-                                                              "license": d.get("license")}))
+                                                              "dataset": k,
+                                                              "license": v}))
         return splits
 
     def _generate_examples(self, filepaths, dataset, license):
@@ -130,4 +149,5 @@ class EmotionsDataset(datasets.GeneratorBasedBuilder):
                                             "label": emo_mapping[ce]}
 
 
+temp = load_dataset("ma2za/emotions_dataset", split="daily_dialog")
 print()