Update DocLayNet-small.py

DocLayNet-small.py

@@ -68,13 +68,12 @@ logger = datasets.logging.get_logger(__name__)
 class DocLayNetBuilderConfig(datasets.BuilderConfig):
     """BuilderConfig for DocLayNet small"""
 
-    def __init__(self, name, splits, **kwargs):
+    def __init__(self, name, **kwargs):
         """BuilderConfig for DocLayNet small.
         Args:
           **kwargs: keyword arguments forwarded to super.
         """
         super().__init__(name, **kwargs)
-        self.splits = splits
 
         
 class DocLayNet(datasets.GeneratorBasedBuilder):
@@ -100,7 +99,7 @@ class DocLayNet(datasets.GeneratorBasedBuilder):
     # data = datasets.load_dataset('my_dataset', 'first_domain')
     # data = datasets.load_dataset('my_dataset', 'second_domain')
     BUILDER_CONFIGS = [
-        DocLayNetBuilderConfig(name="DocLayNet_2022.08_processed_on_2023.01", splits=["train", "val", "valid", "validation", "dev", "test"], version=datasets.Version("1.0.0"), description="DocLayNeT small dataset"),
+        DocLayNetBuilderConfig(name="DocLayNet_2022.08_processed_on_2023.01", version=datasets.Version("1.0.0"), description="DocLayNeT small dataset"),
     ]
 
     BUILDER_CONFIG_CLASS = DocLayNetBuilderConfig
@@ -158,42 +157,36 @@ class DocLayNet(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_file = dl_manager.download_and_extract("https://huggingface.co/datasets/pierreguillou/DocLayNet-small/resolve/main/data/dataset_small.zip")
-        splits = []
-        for split in self.config.splits:
-            if split == "train":
-                dataset = datasets.SplitGenerator(                
+        
+        return [
+            datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
                     "filepath": os.path.join(downloaded_file, "small_dataset/train/"),
                     "split": "train",
                 },
-            )
-            elif split in ["val", "valid", "validation", "dev"]:
-                dataset = datasets.SplitGenerator(
+            ),
+            datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
                     "filepath": os.path.join(downloaded_file, "small_dataset/val/"),
-                    "split": "val",
+                    "split": "dev",
                 },
-            )
-            elif split in ["test"]:
-                dataset = datasets.SplitGenerator(
+            ),
+            datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
                     "filepath": os.path.join(downloaded_file, "small_dataset/test/"),
-                    "split": "test",
+                    "split": "test"
                 },
-            )
-            else:
-                continue
+            ),
+        ]
 
-            splits.append(dataset)
-        return splits
 
     def _generate_examples(self, filepath, split):
             logger.info("⏳ Generating examples from = %s", filepath)