wip

reviews_with_drift.py

@@ -106,13 +106,14 @@ class NewDataset(datasets.GeneratorBasedBuilder):
             features=features,  # Here we define them above because they are different between the two configurations
             # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
             # specify them. They'll be used if as_supervised=True in builder.as_dataset.
-            supervised_keys=("text", "label"),
+            # supervised_keys=("text", "label"),
+            supervised_keys=None,
             # Homepage of the dataset for documentation
             # License for the dataset if available
             license=_LICENSE,
             # Citation for the dataset
             citation=_CITATION,
-            task_templates=[TextClassification(text_column="text", label_column="label")],
+            # task_templates=[TextClassification(text_column="text", label_column="label")],
         )
 
     def _split_generators(self, dl_manager):
@@ -122,29 +123,29 @@ class NewDataset(datasets.GeneratorBasedBuilder):
         # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
-        downloaded_files = dl_manager.download_and_extract(_URLS)
+        archive = dl_manager.download(_URLS)
         return [
             datasets.SplitGenerator(
-                name="training",
+                name=datasets.Split("training"),
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": downloaded_files['training'],
+                    "files": dl_manager.iter_archive(archive),
                     "split": "training",
                 },
             ),
             datasets.SplitGenerator(
-                name="validation",
+                name=datasets.Split.VALIDATION,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": downloaded_files['validation'],
-                    "split": "validation"
+                    "files": dl_manager.iter_archive(archive),
+                    "split": "validation",
                 },
             ),
             datasets.SplitGenerator(
-                name="production",
+                name=datasets.Split("production"),
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": downloaded_files['production'],
+                    "files": dl_manager.iter_archive(archive),
                     "split": "production",
                 },
             ),