download and extract urls separately

mlb_data_to_text.py

@@ -222,13 +222,15 @@ class MlbDataToText(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
-        data_dir = dl_manager.download_and_extract(_URLs)
+        train_dir = dl_manager.download_and_extract(_URLs["train"])
+        validation_dir = dl_manager.download_and_extract(_URLs["validation"])
+        test_dir = dl_manager.download_and_extract(_URLs["test"])
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": data_dir["train"],
+                    "filepath": train_dir,
                     "split": "train",
                 },
             ),
@@ -236,7 +238,7 @@ class MlbDataToText(datasets.GeneratorBasedBuilder):
                 name=datasets.Split.TEST,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": data_dir["test"],
+                    "filepath": test_dir,
                     "split": "test"
                 },
             ),
@@ -244,7 +246,7 @@ class MlbDataToText(datasets.GeneratorBasedBuilder):
                 name=datasets.Split.VALIDATION,
                 # These kwargs will be passed to _generate_examples
                 gen_kwargs={
-                    "filepath": data_dir["validation"],
+                    "filepath": validation_dir,
                     "split": "validation",
                 },
             ),